Hello, welcome to the IM Global Telegrology and Quality Control Center. This center was established in 2012, based in Manila, Philippines as part of the Global MHD Support. It provides global radiology support and tele-radiology programs. It aims to standardize and optimize the quality of the radiology service worldwide. In this video, the tele-rad team will guide you through a virtual process and explain to you how this center supports different missions through different activities to optimize the quality of service worldwide. IOM Global Telegrology and QC Center has a team of five technical experts that serves the missions with technical support requests that range from PAX installation, configuration, troubleshoot and assist in configuring X-ray CRDR machines. The center is connected to 75 PAX nodes in different locations worldwide enabling access to tele-radiology. The center uses web-based tele-radiation developed in-house in collaboration with IOM ICT units. The application has built-in workflow engine to auto-distribute workload to available radiologists in real-time. It also has built-in reporting forms specific to the program type, namely US, Australia, Canada, New Zealand and IOM standard form that allows a radiologist to read the X-ray and download the report from the mission site in real-time. Our radiologists use diagnostic monitors with commercial image viewer remote eye to review images. Security and confidentiality is maintained with role-based access in the application. Microsoft Teams and Skype are used to communicate with missions in real-time. But also it directly supports the mission on radiology services like radiology guidelines, templates, tours, also provides training. It can be online, on-site and by organizing workshop. When we go to the mission we do audit visit to the X-ray units and based on the assessment results give feedback for improvement. Here at IOM Global Tele-Radiology Inc. center the team is working closely with its radiologist, technical team and medical support staff in planning the work schedule to ensure that the center provides adequate and efficient support to missions at all times. The center is also coordinating closely with respective departments such as HR, procurement, finance and legal team to ensure the equipment, services and licenses are timely updated. Also in coordination with various missions across the globe the team also conducts tele-radiology users training for panel positions, radiologists, nurses, radiographers and medical support staff. This is to facilitate fast coordination and smooth processing of cases daily. Most importantly as the center values continuous improvement of its services and its team members the center is doing its best to equip all team members with learning opportunities that will expand their knowledge and skills towards professional growth and of course further advancement of tele-radiology systems and its related technologies. One of the main programs provided by the center is primary reading where the X-rays are transferred to us and we read it real-time and the missions get the X-rays' reports in real-time. We are supporting currently more than 52 locations and we are networked more than 75 locations. I think they are enabled for tele-radiology service. This service is real-time, provided real-time and we are working hours per day, Monday to Friday and also Saturday and Sunday. This is to cover all the different times once we do it. IOM tele-radiology is connected to IOM and non-IOM locations globally. What differentiates us from other tele-radiology providers is that we give emphasis to technical preparation, training and support. During the technical preparation and planning we always do our best to customize our services to the needs of each mission in accordance with the IOM-ICT standards. We install packs in all the missions, configure the packs in the X-ray machine, pilot test the system, train the end users and provide continuous technical support. The X-ray images are replicated from the clinics in the mission to the tele-radiology center in less than 5 minutes. The radiologist reading is done right away using the tele-radiology system. All the while, the mission can monitor the status and progress of the study using the same system. The tele-radiology system starts the day for each mission with greetings and asking the focal person in the mission the expected case load on the Skype chat group. The chess X-rays are sent from the mission then initially received in the tele-rad pack system and will replicate in the tele-rad application given it satisfies the set criteria. The tele-rad system automatically assigns chess X-rays to each radiologist on duty for interpretation. In e-medical cases, Australia, Canada and New Zealand, the tele-rad assistants compress and uploads the chess X-ray die-com file in the in-house system which automatically renames and compresses the file with name and e-medical ID. It is very important to cross-check biodata for discrepancies. Same is done for chess X-rays uploaded by the mission. Tele-rad report is then downloaded in the tele-rad application and carefully transcribed to e-medical. Once done and completed, the ready for interpretation box is ticked to inform radiologists that the case is ready for e-medical submission. Upon e-medical submission, the radiologist takes the submitted box and completeness and correctness of e-medical submission is checked. For UK refugees, US and other cases, it is read in tele-rad application only. UK TB e-med grant cases are also read as is in the UK TB S application. Upon confirmation from the mission that all cases are sent, an Excel summary of process cases are then generated in the tele-rad application. It is then applied to the working file and sent via e-mail with a case count summary. We are tasked with interpreting chess X-ray images on a daily basis. We utilize a system that automatically assigns cases to all radiologists on duty. To access a case, we go to the main tab and we click on a particular case. Once we click on the particular case, an image would appear on the screen with a corresponding reporting form. Once the image is uploaded on the screen, we check for the bio data to make sure that this image belongs to the patient that we should interpret. And then we also check for the image quality as this would affect our interpretation of the image. In non-garden variety cases for which additional images are needed for clarification of a finding, we are able to request so through the same tele-radiology software so that the mission could immediately perform the desired request. For any case that needs discussion or further investigation, or any queries from particular mission's panel physician, we discuss the cases with supervising radiologists and address their concerns accordingly. Communication is real-time with Skype. A peer review and quality control system is present to make sure that the highest quality diagnostic work is done. One of the global activities that we do is second opinion service. When we say second opinion service, when the panel physician or radiologist from the missions have any query about just an excellent report, they will send us an email to review or give our second opinion. When we get that, we will import the image from the local mission packs and duplicate it in global packs, then it will be cued in the tele-radiology application and tagged as second opinion. After that, we will review the image and if there is any, we will ask for additional view. If not, we will complete the report, download the PDF report and send that by email. We will give this with one hour as well. We also run a quality control program using tele-radiology. This system is semi-automatic, complex, linking different systems with automatic sampling of the image from local mission fetching the primary reading from MHD's system called MIMOSA and we read the x-rays here and the system compares, analyzes the data and based on the results we give feedback to the user optimization of the quality of tele-radiology service. IUM global tele-radiology center does quality control of 15% of US cases from IUM locations. The systems inter-operates between multiple systems linking local mission packs, global QC packs, mission MIMOSA systems and tele-radiology QC applications. During the technical preparation we assess and coordinate the tele-radiology QC system requirements to the mission. We configure sampling schedule of chess x-ray images from the local mission packs and report extraction from the MIMOSA system. We train the users on the tele-radiology QC system and its regeology process before we go live the QC process. The QC process involves multiple steps and during the QC process there is a continuous technical support monitoring and troubleshooting of issues. The regeograph selected from our partner locations were queued for review by QC1 radiologist. I review the chess x-ray assigned to me and submit the reports using the corresponding chess x-ray reporting form in the tele-radiology QC application. The QC system generates a score based on the degree of discrepancy between the readings of the QC1 radiologist and the primary radiologist. Those with significant discrepancy namely grades 3, 4 and 5 are again queued for review by the QC2 radiologist. The other activities that I do is as quality control monitoring radiologist where when there is a discrepancy between quality QC1 reading and the primary radiologist and there are significant discrepancy it will come to QC2 radiologist. Then as a QC monitoring radiologist I will review the reports and the image of both primary and QC2 radiologist. If I agree with the QC1 radiologist the system will again auto-calculate the score and it will be the final score to be sent to the focal radiologist in the mission. And also if I agree with the primary radiologist the system will recalculate the score and it may not be sent for focal radiologist review. We work a lot on improving our quality of service internally. We review 5% of the X-rays for internal monitoring and in France if there is and we give feedback and review. We have also another new pilot program called Pre-Review. 10% of the X-rays are re-read by a secondary radiologist before finalizing the report. We have policies and SOPs in place for all terredology processes including addressing if there are any issues. And the radiologists are asked to consult any difficult cases before finalizing the report and we have regular image review session with all our radiologists to learn from our mistakes on collected image. The other activity we give at the center is consultation our consultant radiologists if they have any queries on the findings, if they have any question on what type of additional to give or if there is any queries on how to classify the findings from the different reporting formats they come and consult and it is a center salute to consult before finalizing the report if there is any query. Every day after every shift 5% of the cases interpreted in the center were randomly selected and reviewed for internal monitoring. If a selected case needs an additional view for clarification or if the interpretation itself requires revision, the mission is immediately notified. A feedback mechanism is also in place to inform the primary radiologist of the revision. The center also works on different other global partners we share we do research work and use it for our performance but also for sharing our experience and collaborating with our global partners in the sector representing IOM. Delirad produces regular statistical reports for both the primary reading and QC reading. This data is generated from Delirad SQL reporting systems. State is used to validate and analyze data for billing, performance monitoring, sharing of experience or other decrees from the missions. In addition, the center also does surveys and research collaborations with global partners. Advances in technology system and infrastructure and the different global support programs and services provided by the center has been highly acknowledged by the resettlement country governments and global partners and has put IOM in a competitive place. The center would like to continue the expansion the quality of service and support is providing and contributing.


Hello and welcome to the session. In this session we discussed the following question which says, evaluate limit x times 2 pi by 2 root 2 minus root 1 plus i max with n upon root 2 into cos square x. Before moving on to the solution, let's discuss the hospital room according to which we have that if s of a upon g of a is of the form 0 upon 0 or infinity upon infinity then limit x times 2 a upon g of x is equal to limit upon g dash x is the key idea that we would use in this question. We are supposed to find the limit, limit x times 2 pi by 2 and this one upon root 2 root 2 minus square root of and this one upon i by 2 this would be equal to root 2 minus 1 plus 0 that is equal to 0 upon 0. For this we would have limit x times 2 a fx upon gx is equal to limit x times 2 a f dash x upon g dash x. The required limit would be equal to limit 0 upon d by dx is equal to limit x times 2 pi by 2. Now d by dx of root 2 would be 0 minus d by dx root of 1 plus i max would be half d by dx of sin x which is which would be root 2 into this is equal to limit cancels this is equal to we get this is equal to 1 by 1 plus sin pi by 2 root of 1 plus 1 into 1 that is sin pi by 2 is 1. So further this is equal to 1 by 2 into root 2 or you can say 1 by 8 that is limit x times 2 this one upon is equal to 1 by 8 session hope you understood the solution of this question.


So, welcome to TechSoup's public good app house demo events, apps for community-based fundraising. So, this event is presented in partnership with Giving Tuesday. Giving Tuesday is a global generosity movement unleashing the power of radical generosity. Giving Tuesday was created in 2012 as a simple idea, a day that encourages people to do good. Since then, it has grown into a year-round global movement that inspires hundreds of millions of people to give, collaborate, and celebrate generosity. Join the movement and give each Tuesday and every day, whether it's some of your time, a donation, or the power of your voice in your local community. I'm delighted to welcome Giving Tuesday's Lexa Wilson to open the event. Lexa works with organizations to bring data and technology initiatives for the public and social sectors to life, coordinating with knowledge management experts, data scientists, developers, and fellow research enthusiasts. She supports efforts to break down barriers to data sharing and collaborative social research initiatives. Thanks for joining us today, Lexa. Hi, thank you so much to TechSoup. I'm so excited to be here with you all today. And as I was just introduced, I'm Lexa. I help manage data and analytics projects within the Giving Tuesday Data Commons team, which I'll mention a little bit more about in a second. And so I know some of you have campaigns planned. I know some of you are just curious to see what happens on Giving Tuesday. For those of you who are just learning about us, what the opportunities are, what kind of work we do, I'll take a few minutes to give an overview of the movement and especially touch on why we're excited about the platforms here today. So, yes, as mentioned, Giving Tuesday was created in 2012 based on the idea that generosity deserves its own day. And over the years, it has grown into a global movement that we believe inspires people to give to collaborate and to celebrate all types of generosity. We are currently present in over 80 countries, each of which have numerous different campaigns and activities going on on Giving Tuesday and year round. And we like to attribute that success to the fact that we've adhered to this core principle that this movement is entirely intended to be co-opted and adapted to any given groups needs. We encourage folks to take it somewhere new and to adopt Giving Tuesday in an authentic way and to innovate and do whatever they want to do with it in order to grow generosity locally. So, as I mentioned, a major piece of Giving Tuesday is the data commons. That's the area that I'm most involved in, which is, for those of you who don't know, we bring together different actors in the social sector, researchers, social enterprise, platforms, nonprofits, foundations, policymakers. In order to find out what they need, how can we bridge practitioners with researchers? How can we increase the value of the data that we're all generating so that we can provide real insights for all the different members of the social sector? So this work is done in collaboration with a whole bunch of partners who are willing to share their data with us, share their methodologies, share their needs. And we're so excited that a lot of those here today are partners of ours who share data around their Giving Tuesday campaigns. And so together we're able to generate insights about Giving Tuesday and its power as a Giving Day, but well beyond that as well. So last year we were able, thanks to those who do share data with us, we were able to find out that $2.7 billion were donated to Social Good in the U.S. alone in the 24 hours that span Giving Tuesday. But we always like to highlight that it's not just a day about giving money. There is so many other ways that people express their generosity on Giving Tuesday and every day. So it's always interesting for us to make sure that all of those different types of generosity activities are being highlighted and that they're being leveraged as well. This is just another testament to the opportunity that Giving Tuesday presents. Donations are on Giving Tuesday are growing faster than consumer spending on days like Black Friday and Cyber Monday. So there is so much opportunity here to take advantage of people's innate desire to be generous and to leverage that for your own movement's needs or your own community's needs. A few more things just to mention about Giving Tuesday, what we've been able to learn about it. 82% of organizations that participate say that they use it to experiment and try something new, and we love that. We really encourage people to take this opportunity to do something that they wouldn't have done before or to try something and measure the results of it and see how they can integrate those results into their activities later. We know that 80% of those who have heard of Giving Tuesday say that they are inspired to do something generous because of that day. That's incredible to us and that's something that we like to demonstrate to say, hey, take advantage of these people who are excited, ready to do something on this day and then beyond as well. And another thing to highlight is just people like to feel like they're part of something bigger than themselves. And we see that as well in how they report about feeling like they're part of a bigger movement. So definitely, like this is no surprise, right? People find joy in Giving. So make sure to, we like to encourage people to include joy in everything that they're doing and everything that they're promoting. The core of everything that we do at Giving Tuesday is our communities. So much of what we do is driven by what we learn from them. They are the ones who are showing us how to address equity, justice, empathy, and more through generosity. We are in the number of communities that we have is it's constantly growing, which is so exciting for us because that means we get more feedback about what's needed. We get more feedback about what the kind of interesting and innovative ways that they are addressing the topics that are most challenging in their area of expertise or their geographical area. Just want to show the kind of different communities that we have. So you see the squares. These are the types of geographical communities that that we work closely with. But we also have causes or identity based communities. And these are the ones that were so excited about growing and supporting even more. Because what we've seen is that having these approaches, having communities that built that create these coalitions around certain causes, allow those causes to be addressed by people who are involved in them. It's kind of led by them for them. And that's what's so exciting by the platforms that are here today. They are helping build community and inclusion. They're driving change that has to be led by people who are informed of the needs and who are served by that work. The last thing that I'll mention is that at the core of our work, what Giving Tuesday is trying to achieve as an organization is to reimagine a world that's based on radical generosity, which is this notion that someone else's suffering should be as intolerable as our own suffering. And so we believe that if people flex their generosity muscles regularly, we can create a habit out of giving and that there'll be more inclined to participate in all kinds of other pro social behavior. So if there's one thing I want to leave you with, it's just that Giving Tuesday is an opportunity, is a movement that gives us an opportunity to build the world that we're imagining. And especially through the support and the expertise of the platforms that are here today and who are funneling resources to communities that often don't have them or aren't prioritized otherwise. And so we're so, so excited about that. Thank you.


had access to good eviction data, I would use it to strengthen our litigation and advocacy to address evictions as a civil and human rights issue, which is disproportionately faced by black women and other women of color in their families. Better eviction data would help us demonstrate how policies that might seem like a good idea, such as eviction record screening policies or local nuisance ordinances, instead result in the discriminatory and unfair evictions of black families, domestic violence survivors, and people with disabilities. Better eviction data would help us make the case for laws and policies that promote housing security, such as right to counsel in eviction cases. Eviction data, when it respects the privacy rights of tenants, can be a vital tool for creating stronger and more just communities.


One critical task when you're coding in data science is to be able to find the things that you're looking for. And reg X, which is short for regular expressions, is a wonderful way to do that. You can think of it as the supercharged method for finding needles in haystacks. Now, reg X tends to look a little cryptic. So for instance, here's an example of something that's designed to determine whether something is a valid email address. And it specifies what can go on the beginning, you have the at sign in the middle, then you've got a certain number of numbers and letters, and then you have to have a dot something at the end. And so this is a special kind of code for indicating what can go where. Now, regular expressions or reg X are really a form of pattern matching in text. And it's a way of specifying exactly what needs to be where what can vary and how much it can vary. You can write both specific patterns, say I only want a one letter variation here, or very general like the email validator that I showed you. And the idea here is you can write this search pattern, your little wild card thing, you can find the data. And then once you identify those cases, then you can export them into another program for analysis. So here's a short example of how it can work. What I've done is I've taken some text documents, they're actually the text to Emma and to Pygmalion two books I got off of Project Gutenberg. And this is the command grep carrot l dot ve space asterisk dot txt. So when I'm looking for our lines in either of these books that start with L, then they have one character can be whatever. And then that's followed by ve. And then the dot txt means search for all of the text files in that particular folder. And what it found is lines that began with love and lived and lovely, and so on. Now in terms of the actual nuts and bolts of regular expressions, there are some certain elements. There are literals.  You type the letter L, you're looking for the letter L. There are also metacharacters, which specify, for instance, things needs to go here, they they're characters, but they actually really code that give representations. There are also escape sequences, which are something they use to say, Well, normally this character is used as a variable, but I actually want to really look for a period as opposed to a placeholder. Then you have the entire search expression that you create. And then you have the target string, the thing that it's searching through. So let me give a few very short examples. This is the carrot. It's the sometimes called a hat or in French a circle flex. And what that means is you're looking for something that's at the beginning of the text that you're searching. So for example, you can have carrot and capital M, that means you need something that begins with a capital M. So, for instance, the word Mac true, it will find that. But if you have iMac, there's a capital M, but it's not the first thing. So that'll be false. It won't find that. The dollar sign means you're looking for something that is at the end of the string. So for example, ing and then dollar sign, that'll find the word fling, because it ends with ing, but it won't find the word flings because it actually ends with an s. And then the dot, the period simply means we're looking for one letter and it can be anything. So for example, you can write a t period. And that will find data because it has an a a t and then one letter after it. But it won't find flat because flat doesn't have anything after the a t. And so these are extremely simple examples of how it can work. Obviously, it gets more complicated. And the real power is when you start combining these bits and elements. Now, one interesting thing about this is you can actually treat this as a game. I love this website. It's called regx golf. And it's at regx.alf.nu. And what it does is it brings up lists of words, two columns, and your job is to write a regular expression in the top that matches all the words on the left column. And none of the words on the right. And that uses the fewest characters possible. You get a score. And it's a great way of learning how to do regular expressions and learning how to search in a way that's going to get you the data that you need for your projects. So in some regx or regular expressions help you find the right data for your project. They're very powerful. And they're very flexible. Now, on the other hand, they are cryptic, at least when you first look at them. But at the same time, it's like a puzzle. And it can be a lot of fun if you practice it. And you see how you can find what you need.


What's up nerds? Avengers Infinity War is finally out in the world, which means it's time to talk spoilers! Specifically, juicy third act spoilers! Today I'm joined by celebrity guest Dave Grohl to discuss the ins and outs of what happens at the end. Why does it happen and what can we expect for the future of the franchise? Let's find out, shall we Dave? Oh, I think we should. Okay, should I probably start using your name, right? This is not actually Dave Grohl, his name's Justin. Hey guys, Justin. Just wanted to get that out of the way, straight for anyone who was still confused. So the ending of Infinity War, what happened?   And one by one we see many of our favorite heroes slowly crumble to dust. Star-Lord, Groot, Drax, Mantis, Bucky, Black Panther and the list goes on and on. So Justin, what the f*** happened?  I think the film should have finished at the snap. I like the dust thing. Yeah, I like the dust thing, but I think for me is it. So then, okay, then that's the one thing I don't like. I don't like the dust. I don't like how half the characters have turned into dust. I think it would have been much more interesting for Thanos to snap his finger, cut to the end, end sequence that he goes through, and then Black. No dust, no anything, no freak out, no anything. And then we would have come into Avengers 4 and gone, wait, what? So that's what happened. But so at Avengers 4, everyone's already dead? Everyone's already gone. Yeah, no, the dust thing would have happened. But it would have happened. We didn't see it.  What did Thanos do when he did that? Yeah, for me, I think you lose so much without that. Like when you lose all the emotion you've got. You do lose the emotion. Spider-Man emotion? Yeah man. Spider-Man, he was bombing the tears.   Like, oh my god. I'm still weepy from that. It's time to hold on.  He was very good. Yeah, so I think you would have lost all of that. You've also got these people that don't know enough about the, about this old mate. Yeah. The Gauntlet and the Stones. That that might leave that dramatic feeling, a massive cliffhanger feeling that all these characters are dead. Where are they going to go with the next movie? Except if you went the other way around and you just had to click, you don't know who's dead. You don't know what you're coming back to and you lose that cliffhanger-ness. You just kind of, you've just seen him click his fingers. But did he get away with it? But was there actually, was there a, the cause and effect? Like the effect of him doing that. What was the cause of it? Seeing the cause. Yeah, sure. That does make sense and emotional sense. But I think as a cliffhanger, it might have been more powerful. And I almost, if I was cutting it, I would have tried it and seen it and tested it with an audience to see if they go, wait, what just happened? That's an unsatisfying cliffhanger. Whereas this ending that we have, it's probably the satisfying cliffhanger. We've got Thanos. He's on his, back on his home planet. Or in his, is this his home planet? Is that a planet? He's at a nice hut to planet. He's on Arcto. He's on the other side of Arcto. Luke Skywalker's island where the, where more grass is. But yeah, that, that's where he is. He's on the original Jedi temple island. But all the adventures are gone, except for the original Avengers. Iron Man, Captain America, Black Widow, Thor, Hulk. So, but how cool is it going to be? Because you've still got Ant-Man, you've got Wasp, who I have a feeling will dust at the end of Ant-Man and the Wasp. But you've got Rocket. I think Rocket being with the core Avengers would be pretty fun to see. But we don't know. Hulk doesn't want to come out. Hulk is scared to be Hulk right now.   And even the last shot where Thanos threw him on the ground was almost like a shot remake of Hulk's final shot of Loki being slain to the ground. So that was a nice callback. And yeah, look, I see it. I see it all going down to Captain Marvel. You've got a Captain Marvel movie coming out just before the next Infinity War movie. Two months before that. It's actually going to be called that. Yeah.  You know, some comics are saying that she's more powerful than Hulk, more powerful than Thor. She has super speed. She has super strength. She's got super agility. She can fly. Yeah. She can fly. She has unbelievable power. I think it's honestly a appearance in front of Thanos. Whips off the glove, disappears.  Better boom. Things are happening and everyone's back alive. Absolutely. Something like that. Something you can very simple like flip it around. So guys, what do you think will happen in Avengers 4? Now we've seen Avengers Infinity War. What do you guys think what's going to happen in the future? So don't forget to like this video, subscribe to the channel, hit the notification bell with your fingers. Or something. And follow us on Facebook because we've got a bunch of really cool stuff there as well. We do. Well, until next time, we'll see you next time on The Movies.


Because we're going to open up some stuff we got in the mail. This is not a mail video, it's not from my viewers. Just, uh, we're going to open up some stuff that we ordered for the tractor. And, um, we still have, I got four out of the five things we ordered, so, that's good. Yeah, very quick. So, the big one first. You want the big one. Yeah. So, we're just going to do a mail-opening vlog. This is fragile. Fragile! Must be from France. You're supposed to say, I think that says fragile honey. Bonjour. No, you're supposed to say, I think that says fragile honey. It says fragile. What movie reference is that? Really? Yeah, it's a movie reference. How do you remember this stuff? Because that's from the all-time best movie in the world. Well, I've seen lots of movies, and ten million times, each one. The Christmas story, when he gets his leg lamp. I still can't remember that stuff. So, this, I know what all these are, but you guys don't. Oh, there's a gasket. Now, the gear heads, yeah, we'll know what they are. Yeah, I know what they are. These are the gaskets. For the lawnmower. Who's video is this? That's just Elfin. These are the gaskets for... The lawnmower. Her, her, John Deere. Yeah, the one that won the race the other day.  So, we've got some seals. We've got some valve seals. We've got head gaskets. We've got exhaust gaskets. We've got carburetor gaskets. We've got sump gaskets. We've got gaskets. So, you won't run out of gaskets? I will once I put it together, yes. So, this is going to be interesting. So, there's this. Well, I should use most all of these. Yeah. A couple of them I will not use because that, that also fits other different engines. That may have something different, but it's the base engine. Like, a couple of the exhaust gaskets. Say for instance, I'm not sure yet, but they may be, they give you a couple of different ones. Like the carburetor gaskets, there's like three or four different ones because it can fit three or four different engines that carburetor kit. So, all right. Let's do the white one. And we have, we have this here. Yeah, that's what I was trying to avoid. Yeah, she spent a long time the other day trying to get the address off the thing. Off my video.  Don't want to make it easy. You can't get much easier than that. So, so I know what this is. You guys don't, but you'll see here in just a second. I try to save these bags, but to re-send out for eBay and stuff like that. Sorry it's so windy. Nice breeze, very bad storm this morning. Yes, we did. It was crazy. I was going to live-stream it, but, but it was very early. So, my friends out West would still be asleep. And then, okay, you don't get this. You don't get that stuff. She likes the bubbles. That's part of it, man. Oh, you might need it for packing. Yeah, exactly. She'd be pausing or plopping these bubbles and I'm like, what are you doing? I need that for packaging. Okay, so we're going to open this up here and I'll show you what we've got. Clamps. I am. Stop. Okay. Oh, no. Okay, so we've got new hose clamps for the fuel line for the new filter. Nice and clean. Yep. Nice and clean. We've got two new spark plugs. Oh, it's nice of them. My fire went out. Bear with me. Okay. Yes, that was nice of them, honey. And we've got the new filter. Oh my God, my truck doesn't even look that clean. Actually, her truck filter does look pretty good. And the way it says, spongey filter. This is called the pre-filter. Pre-filter? Yeah, it goes in like this. Air comes up through here and then it leaves here, comes up through here and then leaves here and the top part is on it and it leaves here and goes down into the air intake. Not good. I'm glad you're doing it. Yes. So that's basically your tune-up. Interesting. Okay. Very well packaged too, by the way. Great job. Just another one. That one. There's a reason for doing this, okay. Here's another one. We're going to open this up. See, there's a pattern going on here. Yeah, it surprised me. I said, when I said I'd do my video, she goes, oh, I thought I was going to help you. Like, oh wow, because you like got a beggar. And she was like, pretty much asking. I'm like, cool. Okay, so we've got this. Okay, so we're going to open. This is also poppy snappy stuff. So let's get this open, which we need some more of this poppy snappy stuff. We're sending out things. So, wow, they package it like I do.  Because we all know what the snail mail does to our packaging. If you saw a monkey's video and I did one, wasn't my divorce papers one. Yeah, that's going back a while back. Mm-hmm. Had perfume spilled all over. Yeah. So, which mine was still usable. I feel sorry for the person who ordered that expensive perfume because you could smell it, man. That stuff was... Yeah. It wasn't no, you know, like timeless or something.  Yeah, sure they weren't too happy when they got that. Well, they probably didn't get it because it would have broke, you know. Mm-hmm. It probably broke in the package and leaked out.  Okay, I gotta cut this, just the way around. I guess they wanted to make sure it didn't get broken or stolen. Very well packaged, again. These companies that I ordered from... That's a good thing, though. One of these may say grease monkey, small engines on it. Oh, yeah? It might be the headlight, yeah. All right. Yay, finally. Gotcha. I still use that stuff, so... Mm-hmm. All right, this... Gear heads will know what this is. This is a ring compressor. When you put your... Your rings on... And you go to put your piston down in your cylinder, your rings are sticking out. If you try to jam it down in there, you're gonna bust your rings. What this does... It's a ratchet type.  It doesn't break your rings. Now, when you wanna put your rings on your cylinder, they gotta spread out a little bit. Now, if you're real careful, you can do it without breaking them. Put that in there. It'll still break sometimes. I know this because I've done a lot of ring jobs and not rim jobs, ring jobs. And... So, when you... You guys will see, when you open up the ring to slide it down over the piston, get in the piston grooves, well, sometimes they'll break, no matter how easy you are. So that's what this is for. You put your ring in here and this opens it up. So you can slide your ring down into whatever groove you want and release it and it goes in. So there's that. So I had to have them two items. Now, this has nothing to do with that stuff. It's just something we needed. See, so that's why it won't bounce back and forth because I'm anal like that. That means... Moving on is our new sound card to make for my microphones to work right. This was $3. I think the last one we gave like 9, 4 or something. The last one... Well, since we've had the computer lasted a couple of years. But this one was $3. But what happened to it was I was having trouble with it, but I couldn't get the mic to work. So I had to plug the mic into the headphone jack to get the mic to work. Well, then I couldn't use my headphone jack for the speakers. So I had to plug speakers into the regular speaker jack. Because them all in ones don't have a separate port. They just got the single port. So you can either use your microphone or you can use external speakers. But they figure you're going to use speakers on the system itself and I don't because they suck. It sounds like an old AM radio. So that's why I needed this. So this seems to be pretty decent, but we'll see and we'll hook that up and we'll try that out. Which will be the next video just a test mic video. Will be the video following this one because why? Because I like uploading videos. So there's our stuff. Wednesday, tomorrow or Wednesday, well it's I said tomorrow or Wednesday. But it's still saying Thursday but it's already here in Florida. The headlights the headlights and corner lights for the truck which are called parking lights but they're called cornering lights whatever.  So sometimes it can take a little longer. So it'll come either tomorrow, Wednesday, or Thursday. So that'll be a video. We'll unbox them, check them out, make sure they're the right ones. Then we'll do a how-to video maybe even live. We'll have to see. I may do it live. Replacing the headlights and this ain't just the ball replacement. We're going to do the whole nine yards, casings, everything. So anyway we're going to go put this in and I'll talk to you for a few minutes with the mics. We'll try different mics, make sure everything's working properly with this unit. Because they do have a return policy on these so if I have to return it, I'll return it and get another one. I never when I buy something I've only had one issue since we've been together and that was our GoPro camera. It wasn't a GoPro. It's like a GoPro. An action cam to call. Just one of them cheap ones still. It was like 18 bucks. Get it home. I plugged the USB cable into it. The charging and the USB thing plopped inside. We tried to get a hold of the guy. He avoided us. Avoided us.  What he was doing was eating up the time that we could return anything. I said, look dude, I don't want my money back. I'll send the camera back. Just send me another camera. I mean, I don't if I buy something, I buy it because I need it or I want it. I'm not going to send it back. Okay? Unless there's an issue with it. Finally, yeah, he was digging. He says, well, let me check this out because I still got the emails. Actually emailed us and said, because I think you're lying. Yeah.  You know, I can see him suspecting that. Number one, you don't talk like that even if you suspect it. But I can understand him suspecting it. Maybe I changed my mind. I just want my money back. But I didn't ask for my money back. I just wanted an exchange. And he didn't make it right. So I bought a bag of wires and stuff for five bucks at the flea market one day. And there happened to be a charger in there that I made work with the battery for the action camera.  I mean, the camera still worked. It was just I had no way to charge it. And it's a good thing it takes a memory card because I would have no way to transfer the data over to the PC. But we're going to try this out. So anyway guys, I'm very happy with the way everything's packaged. And there was only one thing which was this well this that was supposed to be in today. The rest of this stuff here was supposed to be in tomorrow. So it all came a day early. Very good job. So I'm not sure what companies would or I'd give them a shout out, but I'm going to give them all a good review on eBay. So that being said you got anything funny to say?  Last night was in bed. She was asleep. She rolled over and she barely tapped my elbow. And she goes, oh, I'm sorry, honey.  And she was like, oh my god, are you all right? And I said, yeah. Made me mad. I rolled over my back. She's like, seriously? She rolled over the other way. Good night. Late so So anyway, you got, what do you say? Huh? What do I say? Yeah. She bears a myth of man legend.  Monkey says she's out for now. Hi y'all. She's off today so you know. The brain's not there. All right guys, thanks for watching. Bye bye. Don't forget to check out Monkey 1000 BXX32 Nate Jones and nothing edited and I could go on and on. Ben? Yeah, that's BXX32. All right, Ben. They'll be typing in Ben. 15 million Ben's will pop up. Which one, dumbass? I can see the comments now. BXX32 He's awesome guys. Hell of a good guy. And also I want to give a special shout out to JP Productions. Justin. He's one that won our our vacuum cleaner. There was a YouTuber that passed away at, he was pretty good friends with though. They never met in person but he had passed away and he's feeling pretty down about it. But remember Justin, we've got friends, a lot of friends on here. We care about you and things will get better dude. Just remember, hang tough and make some videos. Make sure you're happy. Well, yeah, but you know I know what it's like when I get depressed. You know, I had a hard time making videos after my neighbor over there because we were getting to be pretty good friends and I was actually filming when that happened if you guys remember. It's kind of hard too but yeah, make some more videos buddy. We'll be looking forward to them.  Appreciate it. And bye bye for now. Bye y'all. Have a good day. Bye guys. Take care. Bye.


The Benin State Governor, Reverend Fahda Isens Aliyeh, also lamented the kidnapping of his commissioner for information culture and tourism, Mr. Matu Abo, and former Council Chairman of Okumlaka Government Area. Now, Alawashima Iruka, among others, saying that those embroidered in it will be allowed to continue to perpetrate it as long as it remains governor of the state. Now, Governor Aliyeh spoke while addressing a mammoth crowd outside IVB Square, according to the Governorship Election Petition Tribunal Victory Celebration, organized in his honor by the all-progressive Congress APC in Benin State. Inevitably, his victory at the polls and its recent affirmation by the elections petition tribunal is the will of God and that of the people of the state. Longer what was happening before May 29, Benin State is never a dumping place for criminals, for bandits, and for killers. For those who kidnapped our commissioner for information, art, and culture have limited hours to bring that gentleman back. On behalf of all the security apparatuses we have in the state, let everyone homegrown terrorists, banditry, in others, you are no window, not top notch, or less of room in Benin State. Farah was out of the state when this happened and when he chose to come back today, the escort said, this is a matter which we cannot just ask him to go to the continent alone. Fatima Elyse and supporters should be aware that he has gone back victoriously. This is why we're here. Father, we are proud of you. We support you and you can trust that we hope and pray that you will lead us forward the movement in this. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates. Thank you.


Thank you. Thank you for the introduction, Mike, and this is a really good introduction. It saves me time because I even removed the slide about me from the presentation, and I'll just directly jump to the contents. So today we're going to be talking about sharing cyber threat intelligence. First, an intro, what is cyber threat intelligence? You probably know, you might think you know, but hopefully you'll learn a bit more. What are the challenges of sharing CTI, or short for cyber threat intelligence, and then one example. And the examples that I'll be providing here in the use case, it's based on true stories, so to say, but of course many details are abstracted away. And so first we're going to talk about a kind of naive example, naive but still very useful of sharing CTI with confidential computing. And then another example, which is more work in progress, but also has very concrete applications about more privacy preserving aspects of sharing CTI. And then of course some thoughts about the road ahead. So what is CTI? So it might be straightforward to think that it's like, okay, it's some sort of specific information about attacks and so on, but that it's actually a very broad concept and very nebulous, just data. So specifically cyber threat intelligence, it's a subset of threat intelligence, so threat intelligence is a very broad domain. But here in this case, we're specifically focusing on digital threats and cyber security, so we don't care about physical threats and so on. And normally it includes whole lot, and it includes like anything from very detailed things like network logs and activity logs about processing, running on individual workstations, servers, networks and so on, malware reports. It also contains all sorts of unstructured information from hacker forums, all sorts of reports from government agencies and other agencies. So it's a whole lot and it's a funnel. So all the way from the top very unstructured information discussions, ideas, gossip and so on, all the way down to specific, I don't know, processes running on a specific workstation. And it can be used in different ways, it can be used to kind of understand the trends. It can also be used to understand the tactics, techniques that adversaries or specific attackers are using today, are developing, are working on and so on. And it also allows to identify quickly enough the specific malware strains, vulnerabilities and known exploits. So just like viruses in the real world, in the biological viruses that attack us, malware also evolves all the time, but this time it's like people actually working actively to evolve them. So that's actually where the similarity ends. So in most cases, this kind of data involves sensitive, either personal data or business critical data, which makes the whole subject really touching. And also because in many cases cyber threats either indicate that a specific attack has happened or when was successful perhaps, and then nobody wants to really talk about that or some enterprise or some organization has been targeted, even that is additional information. So it's really, really difficult to work with. But in the same time, organizations need to share this and need to collect this from others and share and so on because this helps prepare incident response, helps them be ready, helps improve their capabilities and so on and also eventually reduce the impact of cyber incidents when bad things actually happen. And so also knowing emerging threats helps them make informed decisions instead of just say like, okay, let's keep investing in cybersecurity endlessly, nobody ever said that. But at least this helps argue why specific measures need to be taken and so on given the trends and the developments in let's say new malware strains. And so it's an ever-evolving threat, as I said, things are not static, things change from day to day. And so that's why organizations, even though they are even competing perhaps, those all sorts of security organizations, they might be competing, but they also need to collaborate. And then there's even another model where there might be, I don't know, organizations that are not directly competing such as let's say the region of Bilbao or actually Basque, I don't know, the exact region here. And then another region in a different country might want to exchange information about what is actually happening to their networks because if there's an attack on a public administration in Spain, there might be a similar attack coming up in Belgium or Italy or any other country. But then here you come to a different type of difficulties because then this means transferring potential personal information over borders, which adds a whole lot of new challenges. So sharing city eyes far from straightforward. In the same time, it's really, really necessary. As I mentioned, organizations prefer to keep it secret because this often risks damaging the public images, nobody wants to look like they had some sort of incident. They prefer to keep things nice and easy.  Because as I said, it's a problem that is difficult to solve not only technically, it's not only about the data model of specific, how do you share this information. And for that you have this OECS defined standards. But it's also about other aspects, about data protection, about getting the OECS from the data protection officer in the organization to share this potentially business critical or personal information across organizational borders, across national borders. It all becomes like a multi-dimensional problem, which is different from other, let's say, settings when you have the, I don't know, bunch of IoT sensors and you need to protect that data from adversaries. And then, of course, now everybody talks about AI and machine learning. And the issue with this is that this really helps improve things because the issues so far with the threat intelligence analysis is that it's a human issue. It needs to be analyzed by humans, by SOC operators, like security operations centers operators. And the single biggest issue with that is burnout. People just get burned out. There's so much information they need to react really fast and so on. It's still necessary. But then, of course, you have machine learning and deep learning to help that as a tool and perhaps reduce the amount of information and help their decision. So it's a very good decision support tool. The thing with it is that, given that the threat is ever evolving, they need a lot of data all the time. So this even further highlights the need to share data. And sharing data is difficult, as I mentioned until now. So in summary, sharing big amounts of CTI data is complex. Why? So first of all, data is heterogeneous. There's all this stack from, from let's say, process information all the way to discussions on all sorts of forums. Potentially, it's very sensitive. It's business sensitive. It's personal information sensitive and so on.  However, they rely on blind trust. Just close your eyes, like, yes, sure, things are good. Of course, they can also rely on very long legal negotiations that are absolutely unenforceable because you can never ever actually prove something went one way or another. So in that case, only legal stuff wins because they get a lot of budget. Or in some other cases, nothing is happening. And then we get less information. We don't know what's happening. We cannot keep up with the new tactics of the adversaries. So in brief, the way I see it right now, there are no good solutions. There are workarounds. There are better or worse workarounds, but it's all workarounds. Quite often, like, blind trust is the winner. Like, we see blind trust everywhere. And so if we look at it on a higher level, let's imagine some sort of hospital or whatever provider of network logs or like the public administration of the city of Bilbao, they need to collect information from their networks and so on. And they do that, but they don't really obviously have the expertise to extract threat intelligence from that. And they collaborate usually with some sort of a security provider with a managed security service and so on. And here we care about privacy because in many cases or in most cases, let's say they have some sort of monitoring tools on their workstations, on their networks, and these monitoring tools are installed on the, let's say, laptops or workstations of individual employees. And if you are able to see all the processes that are running, all the tabs that are open and so on, well, it kind of contains very sensitive information, you know, who's sort of from Facebook instead of working and so on. So it's very touchy. You cannot just like send it over to a managed security service provider, potentially located in a different country. And here we care about the collection phase. So we care about input privacy. When the data is collected, what kind of data is collected? And then it's somehow processed. Right now we abstract from like where it's processed, who is processing. It's somehow anonymized. And I put it in quotes because anonymization is such a topic that, yeah, it's, yeah, there's, we could call it pseudo anonymization. And then there's the sharing phase, which is more about the output privacy. What do you release? What kind of views or what kind of queries do you allow and what kind of views of data you allow based on the process information? And this really like the, let's say, the setup and how this is solved really depends on where the organizational boundary is. Is all this processing and pre-processing and pseudo anonymization happening on the side of the managed security service or on the side of the data owner service? And so here, this organization boundary can be shifting. And depending on this setup, you have very, very different trust relations. And I know we have a trust, machine trust expert in the room. I'm reading your book right now, Mike. And this really affects how things are set up, negotiated, and so on. And so how confidential computing can be solved in one case? Well, of course, using confidential computing, we can agree that a certain software with a certain configuration would be processing the data. And then a certain, let's say, subset of information from that data would be released to the managed security service. And then both organizations can verify and use some sort of attestation service. In this case, well, the service that we have, but it could be project amber from Intel or others, in order to validate that certain software with a certain configuration that has been whitelisted and agreed upon with certain policies and so on, is processing the data and is releasing a certain type of information that is anonymized, pseudo anonymized, and has been given an OK by the data protection officer. So this is, let's say, a simple implementation which is still useful and it raises the bar. And most importantly, it raises the, let's say, the chances that the managed security services provider can convince their potential customer, the city of Bilbao, that they will not gain too much information about the too much private data about the employees of the public administration.  So this is, let's say, a canonical, almost example of using computational computing to protect, on one hand, the data, but also potentially the algorithms or even the configuration data of the software. And the software that does the processing can be proprietary, can be an open source project that has been configured in some way and so on. So yeah, here, the same thing. Again, it depends on where this processing is happening. It can also be used, the same model can be used to place this preprocessing software created or configured by the managed security service provider on the network of the administration, because then it would also help them reduce the amount of data collected. Because a big issue with collecting cyber threat intelligence is that it's a lot of data, it's petabytes of data. And these guys here who are collecting and processing the cyber threat intelligence, they don't need all this data. It's costly, it's a lot of trouble protecting it and so on. They would rather have the pure information that they need. On the other hand, if they place their potentially proprietary algorithms to detect attacks on the networks of their customers, well, they might lose control over it because they don't trust these networks actually. So computational computing can help in this sense. But then there are, okay, so this basically summarizes it. But there are more complex scenarios. So in this case, the first conclusion here that confidential computing is not magic, but can help. And even if it helps here, there are still very complex trust relationships that are still involved between the data owner, let's say the public administration of the city of Bilbao, the managed security service provider, and whoever runs the, let's say, attestation service, the policies for this attestation service and so on. But then you might have other cases, as I mentioned, where several public administrations, for example, might want to collaborate in order to collaboratively train a machine learning model for threat intelligence collection and so on. And here we have an example of what Sven mentioned of combining or stacking the technologies of confidential computing with some other pets. And in this case, of course, federated learning with homomorphic encryption or secure aggregation based on the homomorphic encryption helps address this. So this is an example where the two technologies are stacked. And I'll explain very soon why we need to stack them. So the example here is that we have two example organizations, organization one and N, we can have many, but in this drawing there are just two. And the organizations collect these logs. And these logs, as I mentioned, can contain very sensitive information. And usually they do. And they need to be protected both due to business reasons and due to personal data protection reasons. And then very different people decide on these issues. And these two organizations generally trust each other on sharing cyber threat intelligence information, but don't really trust each other on sharing data. And they cannot even trust each other. They're prevented by law or by regulations from trusting, from sharing personal information simply due to GDPR or other regulations. Yeah.  And we went through many of them. We chose one. We found that it's very scalable. But then it has quite a lot of constraints because it only supports additive operations and it has other constraints. And then we realized like, hey, actually, we don't need scalability. Because many of these secure aggregation schemes, especially based on federated learning, they are built for scalability. But if we have, let's say, 10s of organizations, we don't care about scalability. Yeah, perfect. We don't care about scalability. We can trade scalability for, let's say, for performance or for other security properties. And so in this case, we designed a different secure aggregation scheme. And this comes back to the point of using, let's say, NPC and other pets that Sven was making. And one issue with this is that it's brittle. It's brittle. And it quite often needs to be fine tuned to the use case. And it's quite a lot of fiddling there. So that is a big challenge to their more massive adoption. But in any case, they are very useful. However, however, this is great. But homomorphic encryption has one very big massive Achilles heel is that it only provides confidentiality. It takes good care of confidentiality and great everything is encrypted, but integrity is not there. And this is exactly the case where we also need integrity because we want to be able to rely on this information and know that not only it's protected at all times, but it's also trustworthy that, of course, the organizations might trust each other to provide correct information, but will they trust the aggregator, whoever runs the aggregator? How is the aggregator running? And this is another case where confidential computing can help. And this is the case for stacking up the technologies where confidential computing can be used to protect the aggregation service for the federated learning model in this case, combined with homomorphic encryption that is used for secure aggregation of the model parameters. Yeah. So in summary or looking ahead, I would say that, well, I think there is not yet the realization. I think it will still take time, but I think blind trust should no longer be an option. Well, I think it's still quite a lot an option, especially when we look at all the services that we use and even enterprise services that businesses use. Blind trust is still an option, and it works remarkably fine. But I think the regulations that are coming up are slowly catching up with this, and especially we see regulations in different fields, especially Europe is very much a leader in regulating things. But finance is having some really nice regulations coming up where blind trust is no longer an option. And confidential computing is a really, really powerful tool. But as I mentioned before, it's not magic. It can do a lot if it's used right. It's not necessarily easy to use it right. And it needs to be combined well stacked or even blended with other pets. And on the other hand, protecting privacy, the other aspect of this talk is also a moving target. And this is the other nice or funny or challenging aspect of of using confidential computing. It's not like we designed a solution, confidential computing, we're good. No, because even what is privacy and how it needs to be protected is evolving. It evolves you to regulations. It evolves you to interpretations of regulations, which is a funny funny thing. But every every nation state even within Europe and elsewhere as well, of course will have their own interpretations of this. And even the interpretation or understanding of local data protection officers in every organization, you know, might evolve over time. Whatever was fine today, we just told them like, we use confidential computing. So it's okay. Today is fine. And then tomorrow, the DPO will read into the, you know, we'll read some some article that was published about vulnerabilities and whatnot and say like, no, it's not not fine anymore. Like you need to do more. So this is also a moving target. So which makes the whole problem quite challenging and fun. But it's also a good challenge for the confidential computing community to keep, you know, evolving and improving and not just, you know, rely on the comfortable realization that we have confidential computing. This is this is perfect. We're done. No, we're not done, but it's a very, very good tool to work with. And that's, that's about it. Yeah. Get in touch for demo. Thank you very much indeed. Nothing's, nothing fun about confidential computing. No, you know, that's all good. Very sad topic. Any questions? I'm sure there are. It's who wants to start? Because I can, I can always come up with questions. I know. So, okay. So you've chosen your, your other PET to stack. Where are you with choices in terms of the confidential computing piece of your stack? In terms of what you're offering? Yeah. So I wonder how I should answer this question without going into details of any specific provider, because it's a very, well, not provider, but vendor, because a very, you know, vendor specific technology. But we, due to performance issues, I think this is a good way, due to performance issues, we realized that we need VM based solutions. And I see this also basically all the feedback that I've had through, from all sorts of discussions, there are some organizations that are for whatever reason, very attached to process based.  And ultimately, performance trumps security in most use cases. And even, even no matter how stringent the security requirements, performance is still necessary. Of course, there will always be niche cases where, where security will trump performance and say like, well, we, we are fine. We are going to use just, you know, very secure stacked or amalgamated solutions. And we don't care about performance or cost. Yes. But those, those are very niche. And, and that's why we saw that VM based approaches are, let's say, more accepted. So that's a, which leads you to a whole bunch of other questions. I don't think it's time to go through. But I think I'm just going to raise here, which is that often when, when people come to us, the industry and ask about performance, they, they think it's all about how fast something runs. But actually, we've had a couple of talks which talked about IO performance. And that's really, really important.  So I'd love to see some more talks about those sorts of things in, in future ones of those, if anyone's interested. Any final questions for Nicola? I'll have my language question, if no one else. What language are you using? Rust. Yeah, that's a correct answer. Always the correct answer. So I'm a, I'm a rust convert. Excellent. Well, thank you very much indeed. Next is


You all can say leave lot or loop, but can you also say feel tall or pool? Perhaps you think you can, but are you really sure that you're producing a true so-called dark L in these words? Or do you say feel tall or pool like you do in German? If this is so then let's do something about it The problem is that the dark L that we need in words such as feel is not an alofone of the L phoneme in German German has an L phoneme But in all positions we produce a clear or palatalized L alofone for example in feel and leaf Thus many Germans only use the clear L when they speak English So what can we do about this? Well mainly practice the dark L first in isolation and then in context As a starting point we've got to develop a feeling for our tongue position which looks like this So let's move from a clear L to a dark L using L between two vowels and here we go Again Can you feel how the back of your tongue is raised when you articulate Allah? If you can that's fine, and you should now produce words that contain a dark L That is words where the L follows a vowel Here we go peel pale pal Paul pool pearl and so on and By the way, we should not forget words that contain a so-called syllabic L as in bottle rattle or poodle They also involve the dark L Well, and for those of you who know Cologne and the colonial or ripuaerian variety of German What's the favorite type of beer in Cologne? Well, it's colch Which tastes well, but also exhibits a dark L in this variety of German again colch Okay, I hope my advice helps and you will no longer find it difficult to produce present-day English words with a post-vocalic or a syllabic L