It's DK and I'm back today with another video. Shout out to you for tuning in and if you're not subscribed, do me a favor and smash that subscribe button. I will be doing a giveaway when I get 50,000 subscribers. I'm giving away $500. I'm gonna show you how I got my game from a scholar. So make sure you smash that subscribe button so you can earn your chance to win, but it's time for us to go get these dividends. In today's video, I'm going to tell you guys why I no longer really take summer orders anymore, baby. I know I get this question all the time while I'm out here on the grind. I'm going to tell you the real reason why. It just is what it is, baby. Hey, stay tuned to stick around because we ain't playing around on this. Go, order number one. The day has just begun and guess what we going to? Sun runs. You get these funds, son. We are driving 70 miles. We're picking up one bundle of scourge and we'll receive a payment of 149.33. We're about to pull up and get this cheese. Let's go. And just like that, we got our two things. The scourge, scourge. We got these scourge, baby. Put these scourges in here. We gone. That's all we needed. We had to open a new box and everything. And just like that, it's time to hit the road and get our pockets on swole. Let's go. What's going on, boss? Y'all out here working hard? I know, I know. Yeah, y'all got to hurry up and get it done. So how long do you think it's gonna take y'all to do it? 12. Oh, yeah. You grab it, I can grab it. I don't even care about the scourge. I got double. I don't even care about the scourge. I know, I know, I know. And then, where you stay out in the city? I stay at home work here. All right. Yeah. That's an hour and like 40s right there. Dang, so it's gonna take you three hours to get home. Yeah, I gotta try that. I gotta try that to fall asleep. Why not three hours? Like two hours, two hours and 45 minutes? Almost two. Yeah, so you leave from right from here and do you go right home? Oh, yeah. What do you want me to do right here? What's going on with you? Let me follow you, I know those. I forgot that. Who named y'all morning put on here? David, somebody signed real quick.  Yeah, some chicken shawarma. Breakfast last lunch? Yeah, gotta get it while you can. You got to. All right, you guys have a good one. I will. If y'all didn't think else, I'm trying to get some more money. You know what I'm talking about? Order number two, guess what we about to go back and do? We are going back to Sun Run to get some more fun, son. We are picking up 12 panels. We're gonna drive 24.6 miles and we'll receive a payment of 63.28. All we want to do is get cake and be great. Let's go. And just like that, my guy Steve by the pooling so he can go ahead and let me get you to give it in. You know what I'm talking about? Ain't been up here in a good, low minute. A good, low minute. And just like that, it's time we hit the road and get our pockets on the floor. Let's go. Just like that, we are here is the drop off location for those who haven't been able to keep on skating, baby. We're gonna drop these orders, these panels off. So I can get busy and guess what? Someone is not here, baby. We got to do what we got to do. That's why it's a great thing that we only have these 12 panels. I'm gonna show you on my end. Now we got to step back, here's the photo, yard noodle, smack! We gone. Order number three. I'm about to show you on my piece. I'm gonna be honest with you, baby. We're going back to selling one yet again to get some more dividends. Honestly, we would normally wouldn't take this order, baby. We would not take this order because it's kind of low, but sometimes you got to do what you got to do. So you can get that dough in scope. We are picking up some materials and we're gonna drive 19.7 miles for 4409. We ain't stopping until we shine. Let's go. And just like that, we got everything we need. Well, we missing one thing. We missing the scourge, scourge. We missing the scourge, baby. My god, Ken is about to go get the cutter. He about to open the scourge. So we about to get busy. I'm glad you guys are with me. Guess what I'm about to do? I'm about to move kind of splits. And you know what else? You already know what I'm about to say. R.I.P. Nipsey. My god, Ken, get me real some scourge. We got two of them. Just in case. We don't know. Just like that, it's time to hit the road and get our pockets on the floor. Let's go. And just like that, we are here at the drop off location, baby. I'm about to drop this joint and we about to keep on getting busy. And I'm glad you guys are with me. About to move kind of swiftly. Guess what else? R.I.P. Nipsey. Again, we are getting different in. Now we got to step back here with the photo. You already know those smack. We gone. And just like that, at the end of the video, I hope you guys enjoyed the content. Let's get right into it, baby. I know you're wondering right now why I don't really take someone orders anymore. This whole video was of someone orders, but it was through multiple days. What we got to do, we got to do so we can get paid so we can put up a new escalate. Now, the real reason why I no longer really take someone orders anymore is because first off, the payout is not as great as it was. That's the first thing. Secondly, they starting to make so many rules. And I, look, I ain't got time. I don't work for nobody, baby. I work for me. They make all these rules. And before I get into that, I'm about the rules. I do want to say that huge shout out to my guy Ken, huge shout out to my Steve, huge shout out to everybody who work at someone. It has nothing to do with them at all. Any specific person that worked there. But it's all these rules that's being added on to the dispatch app. And I ain't got time to pay no gains. We trying to go out here and do our thing. So now let's get to the rules. Now, the first rule was we can no longer take two orders. So I'm driving all the way from where I live all the way out here to get these orders. And we can't take two orders anymore. So it kind of doesn't really make sense for us to drive all the way there to not really get that much payout and we barely getting the orders and all that stuff. So it really don't make sense for that anymore. Number two, they make it up all these different rules. I literally just got a message from dispatch yesterday. This is what it says. All someone orders need to be stacked on the ground must be a flat service at delivery. So what they mean by that is from now on we cannot lean them up against the house anymore. We now have to lay them flat and they want us to get cardboard or a pallet to put right there and then slay all the materials on top of that. And my issue with that is honestly, it's going to be kind of hard to do that without messing up these panels because it's only one person doing it.  Guess what? Someone don't be there baby. So sometimes they're there and some crews are great and some are not. It just is what it is. So we're going to have to stack all these materials now. So which means it's possible that you're going to have to get some cardboard from the warehouse or bring your own cardboard or you got to take all of the panels off the pallet, put the pallet outside in the grass or in the driveway and then restack them on top of the pallet. Now why would I do all that? For this little bit of money baby. This doesn't make sense. So that's nothing. They also said pallets should be placed on top of cardboard or pallet on the ground glass side up. I just told you guys about that. Leaning the panels. Leaning panels against any structure is strictly prohibited going forward. And if you aren't sure about unloading upon arriving for delivery, reach out to the drop off contact or to dispatch support team for directions. Faries to follow these directions can result in removal from all future someone orders or deactivation for those waiting baby. You can deactivate it for this. Now, dispatch biggest client is someone. It's kind of like they do whatever someone tells them to do. That's pretty much what's going on. But that's the reason why baby. I know y'all be wondering, that's what it is what it is and it ain't one of the ain't. Sometimes we gon' get this money and sometimes we can't. I hope you guys enjoyed this video. Again, smash that subscribe button if you want your chance to win some of these dividends. Also, before we go, comment below and let me know. Am I tweaking or not? What you think about it? Do you think I should take someone orders? Do you think I should follow all the rules? Do you think, what you think I should do baby? But I'll see you guys on the next one. We're going, we're going before you already know it. I'm DDK and I'm on my way.


Tell me something, girl. Did you hear? No, I did not. That the United States of America for the first time ever in its history, returned an artifact to the Palestinians. That was 3,000 years old and was rightfully theirs. We did something good. Is it good if you waited this long? Better late than never. Did we bash their wife's head in? Ha ha ha ha ha! Just! We've done a lot of that in our history, actually.  Leave it to Corbin! To take a beautiful moment and pinpoint something negative about it. Well, if it's about America, there's a lot of negative I could point to. We've done worse than bashing somebody's head in. Ask the Native Americans! Look at the beautiful thing we just did for Palestine. But we nuked Japan! Well, that's true, though. Do we deserve redemption for killing millions? Anyways, Hitler doesn't reserve it, so it... Wow! If you haven't seen our review of the Tamil classic, you don't know what I'm talking about. Yeah, you need to go see the review of Malaram, the flower and the thorn, the superstar Rajadikant. That's all what this is. Today we got a new song from Best Ever Fruit Review Show. This is what? Must Try Before You Die, 10 of Indians' Best Foods. Oh, it's a food video! Awesome. I can have my breakfast. Obviously, we love their channel and love Indian food. I'm going to be very hungry after this video. Not me, I bought my breakfast. Here we go. Their food's way better than your food. That's 100% right. India's top 10 most unique foods. The winds are roaring. The gods are praising us for our great efforts. This is the moment of truth. Here they go. I'm ready to go, so I'm going. I need an ending to this video. India is the birthplace of Hinduism, Buddhism, yoga, chess, and Gandhi. And zero! The great Asian nation is home to over 1 billion people. And my wife. Some of the languages and some of the oldest cuisines that often influence our Wednesday night takeout decisions. Oh. We have over 2,000 named Indian dishes ranging from Indian to South India. Oh yeah, Flaming Pond. Don't worry, on our menu, Best Ever Indian Tours, we've sampled the cuisines and made it super easy for you. I can't even believe that I'm in India right now. I'm at a food truck where they're serving beef. I'm not dreaming. Okay, it looks really good. Here's a list of the top 10 most unique Indian dishes we've come across on our travels. Number 10, Pani Puri. We're in this residential area here in Mumbai. But where? Okay, in Mumbai. These guys pop up out of nowhere. Our Indian countdown begins with a dish called Pani Puri. And some sage advice, when you see a crowd in Mumbai, you follow.  What is special about this place? They're fine. What is the way you taste it? How many do you usually eat? 10 to 15. My kind of snack. I like that. These crispy dough receptacles. They are very unique. We were in the 30 range when we did our eating contest. Where are we? Yeah, trash, Pani Puri. Just trash. Yeah, we had like, if it's like fresh Puri, you can tell looking at the little shell on it. Nice, thin, fresh, delicious. Oh, ours tore our mouths apart. It's only 25 cents a pop, but once your tab is open, like me, building it no longer exists. Maybe I'll stop after 10, or maybe I'll stop when I hate myself. Maybe I'll stop after 10, or maybe I'll stop after I acquire a deli belly. Okay, seriously, I've had like eight or nine already. Last one, last one. Number nine, Veja fried goat kidney. These are not testicles, right? No, not at all. That's kidney? When it comes to Indian food, your hand kidney? No. You have to try everything once before throwing the first kidney stone. I mean, I got my lines mixed up, but anyways, Mumbai is riddled with late night street food markets, hosting vendors with their own unique styles and twists on traditional recipes. Oh, that's so good. It's one of those foods that I'm sad I discovered it so late. We found one with an array of the very best triple O's, Ophuls, Othcuts and Organs. What animal is this from? Roat, Othcuts. This is all the goat organ section that we found. Not the goat's the waist. These guys, these guys guarantee they can make any body part taste like Christmas and we're here to find out. That's a great pickup line. I can make any body part taste like Christmas. These are small pieces. Saute them with a special blend of seasonings and Indian spices. You know, internal organs could taste so good. Mmm, that's good. It just has a nice, organ-y feel about chewing. Number eight, record-breaking vegetarian toddler. You've already done this. You said you ate about 15%. And you ate like this much of one. Yes. Wanna know the perfect date? You and your shorty getting this massive toddler. Ha ha ha ha! Next on our list is a must-have for your trip to India. Specifically, the scientific and the life-stacking party. We had a great golly. Yes, we did. The one of India.  Tell me more about this friend. The scheduling of it was a... We didn't want to share it anyways. I was not told the schedule before. Ha ha ha ha! 52 unique vegetarian selections on one giant platter. Inclusive, a paneer butter masala. A flower curry. Oh! Just play the clip. Oh man, that is the right way to make cauliflower. Spicy... Andrani makes a cauliflower thing that is just... Local co-host Sartor taught me the Bolle Bolle for this very moment. When the meal is so good, you can only express it in Crayat Rap Dance. Bolle Bolle. Bolle Bolle. Bolle Bolle. Bolle Bolle. Bolle Bolle. Bolle Bolle.  The moment you... That's what they do. Bolle Bolle. Bolle Bolle. Bolle Bolle. Speaking of professional dancing, number seven is as incredible as the live entertainment that comes with it. Next up, Daveli in New Life. Hey! Hey! Hey! Hey! Oh, they're going to dance? Is he yelling at me? No. Okay. Okay. Okay. Hey! My dog's name is Seb. But this is not really special. Making this is a Mumbai vendor that Benny Hanna chefs couldn't hold a candle to when it comes to performative cooking. He whips your serving up while doing his odd version of the robot? Is that the robot? It's... Yeah, it's technically dancing. We're in a Bollywood movie right now, aren't we? We are. Oh, it's happening. He's got the bread. Why are you slicing each one? He's not actually that careful. I think he might cut himself at some point. No, he doesn't. It's bally. It'll put some pep in your step, the... Oh, it's delicious. ... and some skit in your junk. Oh. And I don't even know what that means. India has the world's largest number of vegetarians, but here's the good news. Indians are kind of experts at the meatless food taste like, well, actual foods. Seriously. That sounded weird. That is so bad. The most vegetarians... Good news, because that's bad news.  Hamburgers, you would think what? This place couldn't have hamburgers, it does. This Punjab special has the makings of an American burger. The bun, cheese, tomatoes, onions, sauce, and eggs. So, so much grease, but no meat. That looks amazing.  That looks amazing. That looks incredible. Oh ho, money out. It's so good, I actually uttered these words. This makes me think like, ah, I could eat meat less. Well, I probably won't reduce my meat intake anytime soon. It is good to know that there is tasty vegetarian food out there. No better than India. The best. All made in Indian food. Sorry. Number five? That should be number one. That's a very important thing. After going street food stall, after street food stall, nothing is better than a whole coat of meat. Right, it's the life to be number one. The final steps to making the polyp in here. Ah, Palak Paneer, yummy. It's nice enough to bring me home to try her mother's cooking. Trying the stars. I'm like speechless right now. I don't know what's happening. I don't see things in here. Mom starts cooking early and lets me in on some of her secret recipes. After getting all dolled up, I'm greeted with a fantastic spread of deli favorites, polyp paneer, roti, dal, tawa, gashi, kakori, and more. I just realized this is a vegetarian meal. It didn't even dawn on me. Everything's so like hardy and delicious. You can't tell with Indian food, man. Not at all. There's actually no meat here. That's the beauty of Indian cuisine. You have a lot of varieties and vegetables as well. Right, you don't feel like something's missing. Yeah. The other thing that's amazing is how small portions are filling. Meat selection in Indian history. I can't even believe that I'm in India right now. I'm at a food truck where they're serving beef. I'm not dreaming. No. Yeah, it looks really good. The local states across India strictly prohibit the slaughtering of cows for a number of reasons. Luckily, we're in the mood to be crowned upon. My partner in crime for this episode, Jasmine, helps us to track down a food truck in Goa that serves this forbidden meat in a deliciously constructed sandwich. Wow. It's delicious. Look at that. I remember this video. After you check out number three on our list, you will want to throw your stove away and grab a shovel. Oh yeah, I remember this. And cook in the ground. I remember this. Yeah. This is gonna take a while. We're having underground lamb in Jodpur. Yeah, that looks delicious. Prepare your hole. Yeah. First prepare your hole. What's happening here? I'm just gonna mice this a little bit. With the bottom layer of heated embers. So we've got the hot embers coming in. This will be your oven. Take your perfectly seasoned lamb leg. Wrap it in roasted aluminum foil and banana foil. Actually, I'm getting hungry just talking about this. Check it out for yourself. In with the meat. Wrapped in this soaked gunny sack. He's got kind of a wire handle on here. The embers are heating up that wet sack. And now they're gonna cover it on top. I love it when the embers heat up my wet sack. And it's finished. Unravel the best gift you can give yourself in each one. Cheers. Cheers. All right. It's stunning. It's very tender. That's delicious. All those spices working together. But it does nothing sharply. You're right. It is not overpowering at all. Everybody loves good old scrambled eggs. But what if they're from a prehistoric looking bird? Jesus. Guys. Look at this one. Bro, how do your legs even bend that way? Is that even helping you? Number two on our list. Evil Egg Booji. On a random highway between Mumbai and Phune. Humans are known to be the second tallest birds in the world. They're shaggy looking with dark feathers. And a serious attitude. Honestly, at the same time, they are majestic and beautiful. And also completely terrifying. Their eggs are massive. The perfect size for one really, really hungry man. Get the egg liquid out. You just have to, um, yeah. Like what this guy is doing here. Answer that. That was the best sound ever. That looks nice. It doesn't just crack like an egg. Guy. Once dispensed, cook the egg up with a delicate balance of seasonings and Indian Missala spices. So with the last known address of this dish to the side. It's unreal. There's like a depth of flavor where you just didn't realize that scrambled eggs could be like that. Wow. All these ingredients are getting nice and happy together inside. Can I eat it now? Oh, I was joking. But thank you. The village cooking sub-genre on YouTube is huge. Locals, young and old from all over the world are coming together in small villages to create monetizable and engaging content. Usually ending in a massive feast aimed at feeding everyone. How has YouTube changed your life? Yeah. Before you know, nobody respect them like in their village. But now everybody wants to see daddy. Well, today is no different. Our host, Daddy, starts by slaughtering a whole sheep as a sacrifice for today's lunch. Do we eat the balls? People eat it, but I don't eat it. Yeah, I don't like it. Let's ask Daddy. Yeah, camera. He said there we can eat. He makes work of the meat pretty quickly, chopping it into finer pieces, leaving no part to waste. Season it in a huge cauldron and then cooking it down until the angel starts singing. Oh, warm, rich, fatty. Yeah. All of that was gone from inside out. I bet. It just sucked right out. Indian food is legendary and is part of a well connected web of aspects that make Indian culture so influential and popular among many others. If you ever get the chance to visit India, feel free to use this list as a guide for your top tier Indian food. The promise not to just stop there. You can hardly go wrong by trying something only ordinary and unique. For the takeout heroes, instead of ordering your usual chicken tikka masala with rice. Yeah. It might very well surprise you. Oh, this blend of seasonings is just so delicious. It's such a shame that India is not well represented here in their cuisine. This has been the best ever Indian food tour countdown. Until next time. Is that much in good? Yeah. Success. Peace. Another great video. As usual, great video, yeah. And all everything in it, I would love to try. I know you're probably wondering, because you guys are always inquisitive. What I have in my bowl is it's noodles, broccoli, cauliflower, mushroom, tofu, onion, garlic, and some seasonings, and that's about it.  It's leftovers from last night. Now I want Indian food, though. Want some tofu? No. I do not.  Right. Not white people. Yeah. Have you eaten at the place on Topanga in Sherman Way that's connected with the market? Mm-hmm. Oh, we've shopped there, but the food, a lot of North Indian and Gujarati meals in there. Nice. Good stuff. But yeah, oh yeah, they're Punjabi, so they're all veg. So any time we get something like, it's not butter paneer, but it's something like that. Yeah. So I have butter as paneer. Mm-hmm. Anybody I ever bring to it that aren't familiar with Indian cuisine, they think that paneer is tofu. Tofu, always. I'm like, no, it's basically cheese. Yeah. Which I did. I thought paneer was a soft tofu before I found out what it really was. If you've never experienced it before, that's all you know. It looks like tofu and everybody's like, I don't like tofu. Right. Which I've never understood. I love, every time we do a stir fry, I use tofu. Mm-hmm. Yeah. Such a mild, cool, awesome source of protein. Yeah, there's so much, obviously we've only been to four cities in India. Yeah. And we were there for very short amounts of time. But there's so much food I would love to be able to try, especially from this list. Yeah. Like that burger thing. You haven't had any Bengali food yet, have you? Has Andrani cooked anything? Yeah, she's cooked stuff and left it before that was really good. Okay. But once or twice. Did she do an eggplant thing? I don't know. Okay. I don't remember what it was. Anyway, it was delicious. All you need to know is it's got mustard oil in it. Yeah. But fantastic video. Let us know what other food videos we can react to down below.


Welcome to Learning English, a daily 30-minute program from the Voice of America. I'm Ashley Thompson. And I'm Dan Novak. This program is designed for English learners. So we speak a little slower, and we use words and phrases, especially written for people learning English. On today's program, I report on the spread of Islamist groups in West Africa. John Russell has a story on a new study about the mysterious planet Eris. Brian Lin has the science report on an AI robot that could be able to produce oxygen on Mars. Later, Andrew Smith and Jill Robbins present the lesson of the day. But first, Islamist groups linked to al-Qaeda and the Islamic State have been spreading across Africa for years. The groups came from the large area south of the Sahara Desert called the Sahel. They are spreading into wealthier West African coastal nations like Benin. Militants once were believed to want to use coastal nations like Benin, Togo, and Ghana as basis for attacks on Sahel governments. Now the militant groups are strengthening. Benin has been the hardest hit. This year it had more than 10 times the number of violent incidents involving Islamists than Togo did. That information comes from the armed conflict location and event data project. Attacks by militant Islamists, or jihadis, against civilians in Benin went from more than 30 to about 80. The overall number of incidents involving jihadi groups rose by more than 70%. The jihadis' activity in Benin is mostly in the north of the country. There they try to recruit people and create division within local populations. Residents of one small town told the Associated Press recently that civilians can no longer move freely. People in Materi live in fear because of the jihadi threat. The fighters place explosives and carry out kidnappings in the area. They aim to make people lose trust in the government. The government has put in place a curfew and a ban on gatherings. I can't sleep at night. We're not free to travel to move, Materi resident Florence Bhatti said. People are too afraid. People are being displaced from their homes as attacks increase. Some people fear a humanitarian crisis. In August, more than 12,000 people were displaced from their homes in the Atacora and neighboring Alibari states. That is an increase from about 5,000 in March, the United Nations said. The violence is also pushing people from their farms. The UN estimates that tens of thousands of people could face hunger. The government is trying to improve the situation by placing additional security forces along the borders and hiring more soldiers. Local people in the north say they have seen increases in soldiers but say the army is under-equipped and is sometimes late when answering attacks. Neighboring Burkina Faso, Niger and Mali are being overrun by violence. The nations ousted French troops after the militaries there seized power. But Benin is still open to help from its former colonial power, which left in 1960. The French do not have a permanent base in the country. At Benin's request, however, French troops can take part in training programs with Beninese soldiers, a French military spokesman said. People in the north told AP that Benin's government is also trying to hide the level of the crisis. The government has limited freedom of speech and arrested reporters who cover insecurity. Local officials have said the problem does not go beyond the border with Burkina Faso. There is no terrorist, no movement, no organization, no group that has settled or tried to settle in our department said Robert Wimbocasa, the mayor of Materi. Benin is an agricultural nation of 13 million people. It has invested billions of dollars in culture and tourism. It is also building a $1.5 billion industrial area outside of the city of Kotenu, aimed at creating 300,000 jobs by 2030. The lack of information has left people in other parts of the country unaware of the security problems in the north. People in Kotenu said they did not know about the jihadi problem. They did not believe the news or said that it was a problem limited to neighboring countries. Rights groups say the government is attempting to control information while arresting people believed to be working with the jihadis. The groups say the government is pushing people into the militants' hands. Ares, a very small planet similar in size to Pluto, has remained a mystery since its discovery in 2005. The American Space Agency, NASA, explored Pluto in 2015 using its spacecraft New Horizons. Ares, about 40% farther from the sun, has never been visited. But scientists are gaining a fuller understanding of Ares and its differences with Pluto. A recent study provides details about the little planet's structure and composition based on its relationship with its moon Dysnomia. Ares, researchers said recently, appears to have a rocky inside under a level of ice. Pluto also has an icy outside with rock below, but has a higher ice content and is thought to have an underground liquid ocean. We already knew that Ares is more rock-rich than Pluto but what we didn't know was whether Ares had separated the rock from the ice said study lead writer Francis Nemo of the University of California, Santa Cruz. The study appeared in the publication Science Advances. Nemo said Ares got hot enough at some point in history to melt and all the rock sank to the center. The ice is not motionless but is experiencing a slow churning motion driven by leftover heat from the inside. Most likely there is no liquid ocean inside Ares, Nemo said. Ares has a diameter of about 2,326 kilometers. Pluto's is a little bigger at about 2,370 kilometers. Both are smaller than the Earth's moon which has a diameter of 3,475 kilometers. Because of the greater amount of rock which is denser than ice Ares has about 25% more mass than Pluto. As I like to think of it, take Pluto and add every single asteroid in the asteroid belt and you get Ares, said study co-writer Mike Brown, one of the three scientists who discovered Ares. Ares orbits at an average of about 68 times further from the Sun than Earth. It completes a full turn around the Sun in 557 years. The moon, dysnomia, is about 700 kilometers in diameter and made up mostly of ice.  This process has gone to completion. Ares and dysnomia always present the same face to the other, Nemo said. Pluto has this same system with its moon Sharon, while the Earth-Moon system differs. The moon always presents the same face to the Earth, but the Earth does not return the favor, Nemo said. Ares and Pluto are located beyond Neptune, the outermost of our solar system's eight bigger planets. The International Astronomical Union, which sets definitions for planetary science, recognizes five very small planets known as dwarf planets, Ceres, Helmia, and Maki Maki, in addition to Ares and Pluto. Ares is the most massive of them. The new findings fill in some questions about Ares. Each of the largest dwarf planets is unique, and we should be cautious about inferring too much from what we know about Pluto, Brown said. I'm John Russell. Chinese researchers say they have built an artificial intelligence, AI, robot, that can carry out chemical reactions to produce oxygen from water on Mars. The system could be another way for space travelers in the future to make much needed oxygen on Mars. Humans visiting the red planet will need oxygen to support life. The gas could also be used to make rocket fuel, which is difficult to transport to space. Scientists have already established from multiple studies that Mars contains large amounts of water. Most of the water exists in the form of ice. Developers of the new robot system in China say it can be used to release oxygen from the planet's water supply. Scientists at the University of Science and Technology of China in Hafe led the research. The team explored whether an AI robot could use materials found on Mars to produce catalysts to break down water and release oxygen. A catalyst is a substance that permits certain chemical reactions to happen. Experiments were carried out on meteorites that either came from Mars or contained materials similar to the Martian surface. The researchers said the robot chemist first used an acid and chemical mixture to separate and examine materials contained in the meteorites. It identified several different metallic elements including iron, nickel, magnesium and aluminum. The machine then worked to identify different molecules that could be produced from meteorite materials. The team said the system found more than 3.7 million possible molecule combinations. The robot used that data to predict which catalysts would be able to split water molecules to produce oxygen. The catalyst chosen as the best fit was able to operate at minus 37 degrees Celsius. This temperature is similar to current conditions on Mars. A press release announcing the experimental findings said the AI chemist was able to complete the whole process without human involvement in just two months. The release claimed such an operation would take 2,000 years for a human chemist to finish. The publication Nature's Synthesis reported the full results of the study. The study's lead writer, Jun Zhang, told the website space.com that as a boy he often dreamed of being able to one day travel in space. So when we finally saw that the catalysts made by the robot could actually produce oxygen by splitting water molecules, I felt like my dream was coming true. I even started to imagine that I myself will live on Mars in the future. The researchers said they plan next to test whether their AI system performs well under a series of other conditions besides temperature found on Mars. A report explaining the study's results in Nature notes, Zhang suggests that for every square meter of Martian material, his group's system could produce nearly 60 grams of oxygen per hour. The researchers say this level of production could remove the need for future astronauts to transport oxygen from Earth. The robot can work continuously for years, Zhang said. Zhang told Nature he thinks his team's robotic system could also be used to produce other useful catalysts on Mars. This could include processes for making substances to support the growth of plants that could be used to produce food for astronauts. Different chemicals can be made by this robot, Zhang said. He noted that Mars might also not be the only place where it could find other uses, suggesting the moon as another possibility. I'm Brian Lin. Brian Lin is here now to talk more about his science report. Thanks for joining me, Brian. Sure, Dan. Glad to be here. This week you described an AI system scientists say can produce oxygen from water without any human help. The research centered on this system being used in the future on Mars. Are other oxygen-making technologies also being developed for use in space? Yes, so we learned that the AI system created by Chinese researchers could provide enough oxygen to support astronauts spending long periods on Mars. But there are other systems under development. Earlier this year, for example, we reported on a device shown to be able to convert carbon dioxide from the Mars atmosphere, essentially from air into oxygen. And this system has been tested on NASA's Perseverance rover on Mars. So far, the testing has involved very small amounts of oxygen, but developers are confident such a system can be scaled up to provide much larger levels. Always interesting having you on, Brian. Thanks for joining me. You're welcome, Dan. Thank you. My name is Anna Matteo. My name is Andrew Smith. And my name is Jill Robbins. You're listening to The Lesson of the Day on the Learning English Podcast. Welcome to the part of the show where we help you do more with our series Let's Learn English. This series shows Anna Matteo in her work and life in Washington, D.C. In Lesson 37 of the series, Anna finds a backpack outside her office building and tries to find the person it belongs to. Let's listen. You know, I am from the country. And sometimes I miss it. But I really like life in the city. I love the city. Oh, look, someone lost a bag. Maybe it's theirs. Excuse me. Is this bag yours? No, it's not mine. It might be hers. Thank you. Hello. Is this bag yours? Yes, that's mine. These are all my travel things. Thank you. Thank you. Luckily for this traveler, Anna found his bag and brought it to him. Anna was thinking to herself.  I don't know. Anna was thinking to herself. I wonder whose bag this is. That's whose, spelled W-H-O-S-E, which refers to possession. That means to whom the object or idea belongs. Right. So if you find something and you're not sure whose it is, one thing you can ask is, Whose is this? Remember that this word, whose, is spelled differently than the contraction of the two words, who is. Those two words form a subject and verb, like this. Who's the President of the United States? The contraction and the possessive adjective both sound the same. They are both pronounced with the sound of the letter Z at the end. Whose bag is this? Who's the President of the United States? And when we talk about to whom something belongs, we use possessive pronouns. We heard these when Anna was trying to find out whose bag she found. Oh, look. Someone lost a bag. Maybe it's theirs. Excuse me. Is this bag yours? No, it's not mine. It might be hers. Thank you. Excuse me. Is this bag yours? No, it's not mine. It might be his. Thank you. Hello. Is this bag yours? Yes, that's mine. These are all my travel things. Thank you. Thank you. You'll notice that these possessive pronouns sound almost the same as possessive adjectives. For example, the adjective form of the pronoun you is your. Like when we say this is your bag. And then for the possessive pronoun, we just add the letter S. For example, this bag is yours. But notice that the S at the end sounds like the letter Z. Yours. If you listen carefully, you can hear a bit of the sound of the letter S at the end of a word like yours. So the sound of Z is not as strong or as long as in a word like zero. Instead, it's more like a Z with a little S at the end. Yours. Now listen to these five possessive pronouns. Yours, his, hers, ours, theirs. We'll listen to a chant at the end of today's lesson of the day to give you a fun way to practice saying these possessive pronouns. Oh, we will. Whose idea was that? That idea was mine. Well, I'm not surprised. Let's go back to lesson 37 and see what the owner of the bag and Anna talk about. Are you okay? You seem nervous. Well, this is my first visit to Washington, D.C. I'm from a small town in the country. I feel a little lost. I'm from the country, too. And I understand when I first came here, I felt lost all the time. So do you like living in the country or in the city? I like to live in the city. Why? The city is exciting. It has more culture than the country. There are many museums and restaurants. Every night there's theater and music. And there are more jobs. That is why I'm here. Well, I agree. There is more culture in the city. And there might be more jobs, but the country has more nature. It's peaceful and beautiful. There are more trees and mountains. The air is clean. You can go hiking and camping. The city is not beautiful. It's noisy and dirty. I disagree. I think all the different buildings are beautiful. And I like to watch all the different people. Anna and the man from the country. And we should note that when the man uses the word country, he means he is from a rural area, not a city. It does not mean he's from a foreign country. Good point. Anna and the man from the country are talking about which kind of place they prefer. Prefer is a verb. It means to like something more compared to another thing. Anna prefers the city, while the man prefers the country. So they are talking about their preferences. Preference is a noun. It means the thing or the choice that you like more. And we can use it or the verb form to form a question. For example, we can ask, Which do you prefer, the city or the country? Do you already know or have mentioned the choices you can just ask? Do you have a preference? Or you can ask, Do you have a preference between the two? Anna and the man prefer different things. In another lesson of the day, we'll listen to more of lesson 37 of Let's Learn English and find out if Anna and the man continue to disagree or if they share some preferences. And here's a question for our listeners. Do you have a preference between living in the city or the country? You can let us know which you prefer by writing to us at LearningEnglishatvoanews.com. So Andrew, we're almost out of time. How about we listen to that chant with possessive pronouns? Okay, let's do it. And special thanks to my friend Jennifer, who helped record the chant. Here it is. It's mine. It's mine. Is everything yours? Not everything's mine. This one's yours. And that one's hers. And those are his. But what about these? These are mine. But what about those? Those are mine. Are you gonna share? Of course I'll share. Whenever we share, It's not just yours. It's not just mine. It's yours and mine. It's yours and mine. It's yours and mine. It's yours and mine. And together, it's ours. I'd like the ending of that chant. It can feel good to share with others. And if you enjoy the lesson of the day on the Learning English podcast, we hope you will share it with other people. You can do that by finding us on Facebook, YouTube, and Instagram. And you can find all of the Let's Learn English series on our website, learningenglish.voanews.com. Thanks for listening. I'm Dr. Jill. And I'm Andrew Smith. And that's our program for today. Join us again tomorrow to keep Learning English through stories from around the world. I'm Ashley Thompson. And I'm Dan Novak.


Hello everybody, I'm EvilRabbit. We're here on a set of Corsa and We are in box cam. We are in stereo box cam and We're going to be trying to drift in this camera view I'm feeling this is gonna be bad. We're on the mountain roads of the Deals gap or tail of the dragon. Let's make sure you guys follow me on all social media. I'll just find the description box below Let's get to it Not sure how this is really gonna work because this is going to be very weird with camera We do have the mint green and neochrome og energy innovations. We'll back out This is gonna be very weird. Oh Yeah, oh This is gonna be super weird to do. I'm probably very challenging hip in the toe I Cannot see where I'm going on some parts of this turn. So this is not good We are in one of my street BMWs I do love this car. This car is so nice. I mean we're in it. Oh a little little tire drop This is super weird. I feel like oh All those people that drift in first person all so lean. Don't know how to drift in third I feel like this is exactly how they feel trying to drift in third. Oh my god, this is extremely challenging I have not sure if we're gonna be able to totally survive a whole Because this whole weird camera Looks a great, you know thematically for drifting and like replay angle But actually driving in this view My heart and I'm oh And I'm quite good with this M this M Cannot Get over the weird rotational feel of this No, we are going way off because I can't have a hard time of judging bead with this and this is just a little bit of Challenging to say the least I think we're gonna go until we die that we may Go into a normal view And see what it looks like Actually drifting correctly with the box cam overlay. Oh my god It's so hard to judge angle and stuff in this view Slowly starting to get it. I think as I say that we go off course. Nope Where's the dirt? Oh, wow So do I recommend drifting in? Box cam definitely not I should feel like I'm just beginning so we're gonna go back The pits and we're gonna actually drive in the correct view And we will have the box cam obviously up and running Much more smooth forgot where I was for a second. See when you're in the proper view And what you're used to driving On roads are quite fun to drive in this is the Course that I would know pretty well actually Drifted it handfuls of times in the game driven it in real life numerous times Get all the fancy feet. We're going in now. I should have popped in the fourth Didn't want to send ourselves into the dirt. Oh Yeah See this is going to look so much better In the box cam view after the fact just blowing Through the mountains right now this BMW definitely one of my favorite cars. How did we? I think we may have hovered that front wheel over Definitely killing it right now. We have really hot tires though. Definitely tell Little tire drop there. I think this is the smoothest I've ever done heels gap Drifting before this testament to these street cars. Oh, we got it. Oh, that's a little bit of a tire drop We're good. We're good Definitely you feel the tires getting really slippery. I thought that was gonna be our first mess up, but we're not Over yet. We got this. We're coming up close to the end of this Run here Next low-down section, but we're Doing this right. Oh That's not off. I Forgot that corner tightened up way quicker. We have no tires. So In my defense, we are able to throw this thing in fourth and lose traction. Oh, yeah, we are out tires We are definitely out of tires I smoked through them So if you guys like this again, why can't you see more like make sure you let me know down the comment section As always, I thank you guys for coming back and watching. I'm evil rabbit. I'll see you guys On the track


Hi everyone, Sean with jaspyscasebrinks.com here doing 2020 Panini Spectra football four box break pick your team number six This is the second half of the case that we did for pick your team number five So we've got everything set up. We got one random number block in here So here is The final list You can see three random number block teams the Lions the Rams and the Buccaneers here That is represented right here Sure, most of you or at least the people that are in that know how the random number of block break works but if not I've never seen that before stick around you'll see Hopefully right so four box break all card ship release date awesome stuff This is my first in person look at it. So four autographs six member ability cards per box on average One rookie patch autograph for box on average as well incredible looking cards Stop at them. How are you? That's pretty much told as soon as I walked in today that we had pulled a one-of-one Justin Herbert that apparently I Need to make a move on Jared got spectra Number to sixty going to the Rams random number block spot zero Skyler and Max impact Rob Gronkowski relic for the Patriots and Marius Goats 51 out of 75 nice three color patch here monumental relic Darrington Evans for the Tennessee Titans and Steven That is numbered six out of ten very nice short print there for you Steven and our first auto On-card auto Brian Bosworth the boss illustrious legends Seattle Seahawks Scott Marshall nine out of fifteen Anybody remember when he got a ran over by Bo Jackson? He tried to stop Bo Jackson at the goal line It didn't work well for him You've never seen it go watch it Awesome looking card nice green to go with the Seahawks colors Gardner Minshew for the Jaguars and Colton 54 out of 75 very nice rookie aura Chase Claypool My brother's a Steelers fan, so when I was golfing with him earlier today He was telling me that Chase Claypool is pretty much guaranteed two touchdowns every game 33 out of 75 Going to the Steelers and Michael Guluchi Congrats Michael nice triple relic building blocks Clyde Edwards Hilaire For the Kansas City Chiefs and Jeff Keneshiro That is numbered 29 out of 75 a couple off the jersey number there and I Think somebody was waiting for this right? Radiant patch auto Jaylin Hertz 1 2 3 4 colors For the Philadelphia Eagles and Aaron Salinas You go Aaron Congrats, man That is numbered 11 out of 35 nice patch there. Oh nice rookie CD lamb Dallas Cowboys Josh Bruce 49 out of 75 Cowboys Josh Cruz Championship gear Bobby Wagner for the Seattle Seahawks Scott Marshall, and that is 16 out of 75 Now do we think that that's Possibly Super Bowl Jersey? I guess not because he's wearing a white jersey So by the rules of elimination Let's say no Looks like we have a randomizer here Respectra Michael Thomas Adam Thieland dual relic Minnesota Vikings is Patrick Cologne New Orleans Saints Eric John So we're gonna have a randomizer between that that is numbered 38 out of 50. I like that too Nick I think it's incredible and Auto Bradley Chubb For the Denver Broncos going to Bailey McClacklin Eight out of 25 You got to pay the Mitchell Travisky Mitch biscuits For the Bears Michael Coontz 43 out of 99 Nice die cut here Cooper Cup Little green die cut For the Rams, which is a number block That is one out of 30 going to R&B one mark Cool design there mark Congrats Another nice rookie triple relic Michael Pittman, Jr. Building blocks, but then Indianapolis Colton John Turner That is number 25 out of 75 Triple color rookie patch auto Devin Devernay. I don't know what's going on with the pink ink there So it skipped a couple on the first Don't know what's going on with that signature overall, but nice patch auto Devin Devernay Baltimore Ravens Aaron Billingsley That is four out of 25 you're going Congratulations Box two. I didn't see you. Did you text me back? What up, dude? How are you? Good starting off with Nick Bosa for the 49ers and Lee Cheeseman 27 out of 99 Look at this Rise above AJ Dylan, that's an awesome looking card. I like the photography on there Green Bay Packers going to Greg Bynan That is 14 out of 25. How about a nice championship gear Terry Bradshaw? Going to the Michael Gallucci and the Steelers That's Mike And that is numbered 19 out of 25 aspiring two-color patch and auto Kansas City Chiefs Jeff Kandashira Clyde Edwards E. Lair And that is numbered 53 out of 60. Yeah, of course always looking out Kyle Dugger for the Patriots Marius Goats numbered 51 out of 75 Brian Edwards monumental relic for the Las Vegas Raiders and Arik 44 out of 75 Chase Claypole nice patches here two-color dual relic rising rookie Michael Lucci Steelers number nine out of 15 Two off the jersey number there I have not Carlos. I'll have to go check it out But another 140 Michael Jack Ham championship signatures Very nice 58 out of 75 another Kyle Dugger for the Patriots Marius Goats 49 out of 60 Sam Darnold Dicut New York Jets Tom Guidos 43 out of 50 dual relic For the Tennessee Titans Derek Henry and AJ bound Brown dynamic duos Titans go into Steven Susan 28 out of 50 and our auto Bernie Kosar a Little tie-dye effect coloring in the background, which I think means really low numbered Cleveland Browns Glen Campbell And that is numbered four out of four Congrats Glen Devontae Parker Neon Marvel, that's what it's going. I like that 13 out of 15 Going to the Dolphins and Rich Farrottis High voltage two-color relic Chris Carson for the Seahawks and Scott Marshall 22 out of 25 Roll the ankle Sunday spectacle relic for the Cincinnati Bengals Joe Mixon Bengals going to Shawn Matic Eight out of 99 Another one for the Cleveland Browns Grant Delpit rookie auto Glen Campbell box three Let's keep it going Let's keep it grooving Let's find some of those big rookie quarterback names. Maybe You've lost two boxes. I will say now that I'm Looking at it close up and touching them quality Great look exceptional overall It's a 10. What are your score cards at home say? I think even the Russian judge would give this a nine Russian judges are notoriously rough Brandon Iuk rookie silver for the 49ers and Lee She's been I like to look at this rookie aura Little green scope T Higgins Cincinnati Bengals Shawn Matic That's 15 out of 30 That Brandon Iuk was numbered sorry that was 51 out of 99 Joe Borough relic next era for the Bengals Shawn numbered 61 out of 199 and Four color patch and auto Jake Frong for the Buffalo Bills and Ryan 35 out of 35 Reduce your fractions. You got yourself on eBay one of one The ends is saying my scarf a score card is over a 10 a lot of gold vinyl cards in the product The ends. You'll never be an Olympic Score you can't go over a 10. It's a max score. You'd automatically be eliminated David Johnson For the Houston Texans King D. Dornkennig 38 out of 75 Christian a coye The Nigerian nightmare, I believe right can't see the chiefs Jeff can assure 64 out of 75 We're getting the rookie quarterbacks Jordan love monumental patch Green Bay Packers Greg Bynan What's up, Ben? How are you five out of 99 on that for you Greg? and Very nice patch here three colors you get a little bit of white in the top corner there Patch and auto T Higgins for the Bengals and Shawn Maddock. I agree Jensen. Let's do that six out of 25 for you Shawn low numbered there DJ Dallas for the Seahawks Scott Marshall Thank you, Ben 46 out of 60 We love doing it JJ Watt die cut for the Texans Doran King D 28 out of 50 Another dual relic for the Titans. This one's got multiple colors on it Henry Brown again Titans Steven Susan Steven just ends up. I felt it when I was putting it like when I pulled the card See the little split there on the corner It's hard to kind of get that So you can see it. I'm not sure what happened if it was gouge or what There's that on the corner But that'll go you can start the rainbow on that that now and Damon Arnett little green scope rookie auto for the Raiders and arc That is number 23 out of 50 talking about rookie quarterbacks To a Taga Viola Beautiful looking card there The colors in the background with the little trip Going on matches the team colors perfectly It's like it was made to go with dolphins and that is numbered three out of five Congratulation rich That's a hell of a card there.  I'm gonna say it's a ten-way auto It's all the top ten picks of the draft. I don't even know if they have that but how cool would that be? Bogey saying Jefferson or young Yenza saying Tyler Boyd Skyler saying cam acres Trends saying Kenny Galladay a dual to a and burrow John saying we got a second vote for young Let's see the picks are in Sky high signatures neon orange card 12 So sky high does not mean that it's going to be a rookie. Maybe it can be T R O Why oh my god Is this gonna be one of my favorite people of all time? I think it is Troy Polamalu the flying Hawaiian What's neon orange numbered out of who is the flying Hawaiian Pittsburgh Steelers that's gonna be numbered out of 15 Congrats Michael the one and only Troy Polamalu it's out of 15. It says oh wait. No I'm looking at the base neon orange is numbered out of 10. You are correct Caden and Travis Thank you guys So numbered out of ten neon orange parallel or less it does say the base is numbered out of 15 So actually I think this is gonna be less because His base card is numbered out of 15 the neon pink Is the parallel which is numbered out of 15 and this is 10 or less So this is probably this is at most 10 Troy Polamalu's base card In this is numbered out of 15. So It's gonna be really short short numbered on that one. Congrats Michael and our last box who did a Teddy who did Polamalu jump over the line of scrimmage of to tackle was it running back or quarterback? You remember what I'm talking about. How did that just come out? Oh, cuz of the Hawaiian connection. I got you I got you. I know you're going with that either way Troy Polamalu he's incredible Jalen hurts nice rookie silver here for the Eagles and Aaron Salinas. I Mean who deserves it more? Polamalu or Shane Victorino 69 out of 75 Another nice to a rise above green scope For the dolphins and rich for Otis. Congrats, Rich 26 out of 30 Next era relic Clyde Edwards Hilaire For the Kansas City Chiefs and Jeff Kanashiro That is number six out of 199 mine Yeah, you want some Nice JK Dobbins aspiring patch autos to color patch and auto For the Baltimore Ravens Aaron Billingsley, are you gonna open them? Cooper Cup green scope Going to the Rams, which is random number block team That is numbered 23 out of 35 going to Victor Zamora and spot three on the random number block High voltage for color patch and auto for the dolphins going to rich for Otis again Devonte Parker five out of 50 No color, but dual relic rising rookie Jalen hurts Philadelphia Eagles Aaron Salinas Jersey and auto rookie Tyler Johnson aspiring aspiring patch autographs Tampa Bay Buccaneers random number block And that is numbered 38 out of 99 going to spot eight Jonathan Griffin Van Jefferson Silver rookie for the Rams also random number block spot nine Justin Shaw Kyler Murray die cut for the Cardinals and Derrick Melanson Number 20 out of 50 Number two overall pick dual relic rising rookie for the Washington football team Jerry Bennington 145 out of 149 is this one of the last products that will actually see that word printed on stuff and For my chargers Joe Reed rookie auto Richard for Otis and the chargers Mitchell Trabisky silver going to the Chicago Bears Michael Coons 43 out of 75 The numbering was on that Joe Reed, but it was 57 out of 199 for you rich Nice Sunday spectacle Relic Robert Woods for the Rams and the random number block That is 94 out of 99 spot for Jeremy Anderson staying with the Rams max impact Relic Going to the random number block spot six and Caden Mendoza six out of 35 Cooper cut relic for you and we got another redemption Last redemption guys get your picks in John saying Orlando Pace. What's up deporter? How are you? Jefferson are young Which Taylor Adam? Porter is going young You got two votes for young Skyler saying just bucks Rams Lions spectra sky-high signatures no parallel on this Card number 12, which I think we just hit card number 12. Didn't we or am I wrong? T-r-o-y Troy Polamolo So that one's Also Pittsburgh Steelers Michael Goluchy and The base no parallel for this for the Troy Polamolo is numbered out of 15 so that's a Now you get you got two out of you get you got to go for the rainbow now You already got two of them this one's number out of 15 the other ones ten or ten or less so You are you've been picked to do the rainbow Randomizer before we put this break in the books guys between the Vikings and the Saints For this dual relic Michael Thomas Adam Thielen So let's go back over to the randomizer so Minnesota or so saints and Vikings boom so dice roll team on top after three takes the relic one Two and Third and final time. Good luck staying with the Saints and Michael Thomas So that goes to Eric jock Congratulations Eric and guys that was the break some very nice stuff 2020 Panini Specter football four box break pick your team number six Jaspies case breaks calm. I'm Sean and we'll see you next time


So, hey everyone, thanks for coming along. I'm going to be talking about a project of mine called intertube that aims to explore London undergone Open Data and ended up getting rather deep into the weeds. So, standard, who am I, slide? Hey, I'm Eater, my pronouns are she, her. I live in London, I have done for all my life. I'm not just incredibly curious about the tube from afar, although that's cool if you are. I like trains, not as much as some actually, but I do appreciate a good train and my day job involves rewriting tour and rust, so absolutely nothing related to what I'm going to talk to you about now in case you cared. So, the origin story for intertube starts with one of these. This is one of those, like, next train indicators you see waiting for a train on the platforms, if you're not familiar. You generally get a list of what trains there are and their destination and estimated time to arrival. This is not actually the right kind of next train indicator for the story. This is one for the Northern Line, and these generally work with no problems. The experience I was having was more like this. This is Bow Road on the district line, and the boards on the district line were frequently complete garbage, often displaying nothing, sometimes just displaying the word district line, or sometimes only filling in when the train arrived, and so on and so forth. So, my experience with poor information quality at some stations led me to look at what APIs were available to get data on the tube. There are two here, the unified API and TrackNet, and from a first glance it might seem like the unified API might be a better idea. TrackNet uses nice modern new technologies like JSON and Swagger, whereas TrackNet uses XML. If you go and look at the PDFs for TrackNet, you have this lovely document with pages and pages of stuff that is still marked as a draft, despite being last evased in 2010. But, despite this, it turns out the unified API gets its data from TrackNet anyway, and then just gives you less of it. So, I ended up using TrackNet and having to pass lots of XML. This is what using TrackNet ends up looking like. You put together a URL that looks like this, this asks for TrackNet's view of a particular station in details mode, there's also a summary mode, but that is not as useful for my purposes, and you give it a three-letter code representing the station you want, along with the tube line you're interested in. These are given in tables inside the massive PDF, which you have to copy out yourself. So, you put together this URL, and you hit it with your HTTP client of choice, and you get a page of XML. The HTML has this massive text disclaimer about how you shouldn't use this to make safety-critical decisions. So, if you work for the underground, you shouldn't use TrackNet to tell you whether the line is clear, and you get some metadata and train information. The really interesting parts are these individual little train elements, though, which you get describing all the trains near the station. I won't make you read XML, this is the plain English overview of the data you get from TrackNet, use some identifiers, destination time to arrival, an English language description of where the train is, and a track code. So, the destination time to arrival is really how you are supposed to use this API, this is just an electronic form of the next train indicator, and that's kind of the point. But, if you look past that, there's this extra bit of information called a track code, and I was like, hmm, what's that? To explain this, let's imagine a hypothetical tube line with five stations A to E. So, a signalling system at the London Underground might represent this by splitting up into nine distinct bits of sections. So, you might have, you know, the bit of track at station A, and then the bit between A and B, and so on and so forth. If you have a very simple signalling system, we might say that each train can be in any one of these sections. You can't have two trains in the same one, that would be known as a crash. TrackNet gives each section its own little track code to identify the sort of bit of track, and that is what you get through the API exporter as a track code parameter. If we put some trains on our line, red, pink and green for simplicity, we're assuming our line is unidirectional and only goes from A to E. In real world, tube lines are on both ways, but, you know, the different colors here actually correspond to different train identifiers from the API. That's just the way I'm choosing to represent that here. And if you ask TrackNet for the predictions for station B, the bit everyone normally uses is the how far away is this train from the station? The red train arrives in two minutes, the pink train arrives in one minute, et cetera, et cetera. However, it will also tell us that the red train is in track section T001, and the pink one is in T002. You do get an English description of where the train is as well, so it will return at A, brackets T001, and between A and B, T002. If we ask C for the predictions, we get much the same thing, except the green train can be kind of seen by C because B couldn't see it because it already passed by B. So we get the same results, plus the green train being at track code T004. So I got thinking, and I kind of realized this opens up a new possibility for us. Originally, we wouldn't, you know, we wouldn't really be able to combine information from multiple stations to departure boards. It's all, it'll be at the station in this amount of time. You could kind of do some clever stuff to mesh it together, but that's, you know, difficult and kind of, you know, not very useful. But if we use the track code information, we get the same track codes reported for each train, no matter what station we ask. And because the trains have unique identifiers that are also the same no matter what station you ask, we can actually go ahead and merge the information we get from multiple scrapes together into one view of what the line looks like. This is pretty useful. All we need to do is make sure we're looking at enough stations to departure boards to cover the whole line, and then we can get a picture of where all the trains are. We can also keep doing this over time. So if we say we do one set of scrapes at 9am in zero seconds, and another three seconds later when you can see things that kind of moved around a bit, then you can note down what track codes we saw at all the trains at various points in time and build up this little history of where each individual train has been. So to recap the last sort of confusing diagram bit, TrackerNet seems to divide the line into track sections, which are given track codes to identify them. Asking any station for its departure board will return, you know, a departure board, but also each train's current track code. Given that trains share their identifiers and track codes across stations, we can build up a track code history for each individual train. But only if we actually know what the codes mean. We need an idea of how they're connected together and what stations in real life they correspond to. If you recall this diagram I presented to you a few minutes ago, we need a way to generate this that showed how each track code mapped onto something useful. And we don't get this. TrackerNet only literally gives you the stuff I said earlier. Maybe the English language description of where the train is might be useful, but it turns out that multiple track codes can actually have the same description. So we can't just use those. And the descriptions aren't really structured enough to be useful. They do do the nice thing of if a track code represents a station, they'll usually say at station and then maybe the platform number. And actually you can also ask the API if I kind of lied earlier that you can ask the API for these, but everything that's not a station, you're kind of screwed. In practical terms, it's as if you have a line from A to C, the information you get lets you kind of correlate, okay, maybe these red track codes are station A and the blue ones are station B, the pink is station C, but there's this massive orange stuff where you don't really know the structure in between. So we've got a vague idea of what track codes correspond to what stations, but not really that order. I mean, what order the station is in the line, but also what order are the little track sections between the stations. So to help us model the structure of a tube line, we can use this thing from computer science called a graph.  In our case, they have arrows, so it's called a directed graph, but they don't always. We can use graphs to represent the connection between bits of track. If we make a new blob for each piece of track and label it with its track code, we can then draw lines between blobs that are connected to each other. Most of the time, this will result in us drawing things that look like straight lines, which is good, but it should also let us represent sort of train tracks splitting up and joining injunctions, which does happen. A computer together with a bunch of graph algorithms in theory can use the graph to answer important questions for us, like, I'm at this track code, which station is this, or what station is my between? And if I wanted to go to another station from here, what track codes would I cross over? To build the graph, though, we need to know all the connections between the track codes. So how do we discover this, given we're not really given it? How about collecting a bunch of data and then using the order we get from that? So to give you an idea of what that means, if we've recorded our history of two coming after one and three coming after two, you could just link one to two and two to three and so on and so forth. So from this amount of data here, we could generate a graph like this and build the following links. Since two became after one, we link one and two together. And maybe we get some more data hypothetically, and then we can even discover the original structure, which is, you know, a straight line from one to five. So I ran something to save logs of each journey on a line for a few months. By scraping track in it, as we've discussed before, you know, you take the departure boards at various stations and sort of note it all down and combine it together and then extract all the track codes from each train in our journey log and link them together based on observation order. In simpler terms, track code links go into our mythical graphomatic and out we get a graph. Remember the fancy computer science version of the graph, not the sort of x and y axis thing. Hopefully. So we run it and we get something like this.  Like, I appreciate that very little of what I'm going to present to you is going to look like a tube line in a way that you can empathize with, but this isn't it. Like, this is no good. We can zoom in and you can kind of see, you know, the mess maybe up close. It has linked together some of these track codes in like a vaguely sensible way. Like, yeah, I guess, you know, Paddington is after approaching Paddington, but the structure is like horrifically messy. You can't really get much out of it. So yeah, it turns out that data quality isn't high enough for you to just log data and link it together. We do need to be a bit more clever. Now, why does this happen? Well, there are lots of issues, but there's one of them that the district line specifically really loves doing. So, we have a train with a given ID here, red, going along its merry journey, you know, doing train things. Dumbly dumb. Everything's normal. It suddenly disappears for a few scrapes. And then we mysteriously get another train under a new identifier, conspicuously just where the red train would have been had it continued. I can only assume this is just the same train, and track isn't actually good at keeping track of things despite its name. Trains don't just appear out of thin air, question marks. And, by the way, this probably explains why my experience was so bad with the district line. Like, the underlying signaling system turns out to be very disjointed and patchy. This has now changed, by the way, asking about that later. But yeah, there is actually some data issue here. So, this isn't really as simple as I thought. We're going to need, like, sort of slightly better quality data to feed into our mythical graphomatic blob. So, one thing we can do. If you read the TrackNet documentation, everywhere it claims that data is cached in the Microsoft CDN for 30 seconds. You only get a new departure board every 30 seconds. You look at the TFL Open Data Guide, definitely 30 seconds. Now, the previous information I've given you, can you guess how frequently the feed updates? You are? No, it's two to three seconds. It looks like that layer of caching has been removed. I have no idea whether this is accidental or deliberate. If it's accidental, TFL, if you're watching this, this is really useful. Please don't remove this functionality, because my entire website kind of depends on it. But, like, there's a problem here, because I don't think they know. Like, if you ask them, you know, how frequently can I hammer your API with a request? They go, oh, well, I only update every 30 seconds. Why would you want to hammer it frequently? And I'm like, so, in terms of services, you should, you know, limit yourself to 300 requests per minute. So, I'm like, I'm just going to limit myself to 300 requests per minute and hope no one notices. So, yeah, scraping more frequently, we can make our track code links a little bit better. We get more links, and the links we get are also more accurate, more than that in a bit. But also, we can keep account of how many times we saw a given pair of track codes come after one another and feed that information into our graphomatic as well. So, basically, we can exclude links that look like they sort of don't really happen very often and are likely due to some sort of data issue. I won't go into the exact details, mostly for time reasons, and this, you know, wasn't really what I ended up using in the end. But it's a bunch of statistics like quartiles and stuff. And so, with this information, we can make a hopefully improved graphomatic 2.0 that maybe will give us better graphs. And so, you know, we feed this new information in and we get this. Now, this might not look like it, but this does look like a tube line. If you don't believe me, here is a nice pretty annotated version that you might not be able to see, but you can kind of see, you know, on the left-hand side, there's like the eastbound leg, and then it comes back up with a westbound leg. You can see it's kind of figured out that you can turn around at Tower Hill, Barking and Upminster. There's like Elscourt, which is a mess, but it's a mess in real life. There's Ezra Road, Eileen Broadway, Richmond, you know. Surprisingly good if you zoom in. Some parts are perfect. This is a straight line between Acton Town and Chiswick Park, which is how it actually looks. It's kind of cool how zooming in, you can see it's kind of figured out some stuff on its own. If you look to the tube map, you might not think that trains can reverse at Tower Hill, but they can, and it has managed to figure this out, because you can go from between Monument and Tower Hill to reversing in Platform 2 to between Tower Hill and Monument. That's kind of cool, but it's not all great. This was Temple mentioned House, etc., etc., before they upgraded the signalling system mind, and it is a bit of a jumbled mess still. This bit might look fine, but there's a more insidious kind of problem here. Really, there should be a straight line between Tower Hill and Allgate East, but it's not. It's pointing in the vaguely right direction, but if you were to use some of those graph algorithm stuff that I sort of discussed earlier, you would probably just go and miss out a whole bunch of track codes, which is not really great. In summary, our graph is nice to look at, and it has broadly the correct structure, but it's not really the quality we need to make a lot of decisions. It still doesn't facefully represent the actual order of the track codes. There are kind of extra links about the place, and the extra links mean we can't really use this for rooting between two stations. So if you kind of think about why this happens, it's somewhat of a fundamental problem with the way this works. We are pulling the departure boards every few seconds, currently every 11 seconds for complicated reasons, but because we're not getting every single movement, we're always going to catch the train at sort of snapshots of where it is. So if the green train moves, or both of these trains move from A to E and stop at every station, we might only sort of get a snapshot, like A and then between B and C and then a D, or between A and B and then C and D and then E, because we're taking snapshots. So if you try and build a graph out of this information, we get something jumbled on the right. Even though it's supposed to look like what's on the left, a straight line, you end up sort of these piecemeal links we get from only polling every now and then, we don't observe every movement, and so end up with a jumbled mess of links. So I looked around for things that might help here. I don't have a degree, so Wikipedia it is, and it turns out this is a problem other people have had. There's this thing you can do called topological sorting, which is basically saying, okay, I have a graph. Let's find a way to list it such that if A is linked to B, then we put A before B in this list that we're going to make. You can see some examples here on the left. These are both valid sorts, the graph on the right, hopefully, and you can see, for example, the blue sets of links, A, C, C, C, C, C, E, B, E, etc, etc. So this is kind of useful, right? And there's an algorithm for doing this called Khan's algorithm. You can just copy it down and implement it. That's not very interesting. So this is pretty useful. If we know a specific bit of the graph is supposed to be straight, we can use topological sorting to straighten it out. So, for example, station platforms are generally known as being straight lines. If you're station platforms split into two midway through, you might be in for a fun ride. So if we take Tottenham Court Road, platform three on the northern line, and the set of data I collected for this, well, first of all, we run into a problem immediately because we have cycles.  So if you've got A linked to B and B linked to A, you can't really sort that such, you can't really have both of those things. So we need to get rid of the cycle somehow. If we go back to our original graph, omatic, and the source of use for that, there's something that could come in handy here. We can add the number of times we saw each link to our graph. And then it kind of becomes clear which ones we should break. So, for example, going from TN30061 to the one ending in 63, it goes in that direction. 3066 times is all that happened. And the inverse direction we saw once. So I think it is safe to assume here that the one is probably bollocks. And in fact, you can basically make an algorithm that does this. And it's like, okay, well, the really small ones, let's just get rid of those and see whether we can do it. We can sort it then. And yes, you can. So you move all the links that look like they probably shouldn't exist. And then you sort it and you get a straight line, which is good. So, our top logical sorting works. If we know something should be straight, we can straighten it out. So how do we actually use this to fix our graph? Well, one way that we might do this that I had an idea for, go with something like this. First, we find something to group together bits of track with, like we need some way to identify bits that should be straight lines. And then we can turn the bits that should be straight lines into straight lines and then link together the groups. And what do I mean by link together the groups? Well, if we have a graph containing two separate groups, say, you know, a bit that's a platform and a bit that's immediately asked the platform, we know that it shouldn't be possible to teleport from midway through, you know, midway through the platform to midway through after the platform, you know, generally laws of physics. So what we can do is we can take all the links between those two groups and just collapse them into a link between the last item of the first group to the first item of the second group. So we can link together groups and top logically sort. The question remains as to what we should choose to group by. Well, I was like, okay, we could just use the English English descriptions for now. They have a whole bunch of issues that I sort of laid out earlier, but, you know, let's give it a go. You end up with a graph that looks like this. This is the northern line. This is vaguely the right shape, ish, kind of. It's not really that usable. It's very bunched up in the center for one. This is the Victoria line, or maybe, which even doesn't, even better job of showing off what the problem is. It's vaguely a circle. I mean, it makes sense, but there are rather too many errors. Everything's a bit bunched up. We change our visualization software to sort of undo the bunching a bit so we can actually read the text and zoom in. We can see the problem. The descriptions are too broad, as I said. Seven sisters has two platforms going two different directions, but they're bunched up into one big out seven sisters blog for both directions, and same for many other things. So, yeah, the vague descriptions are kind of hurting us here. As you could probably have guessed, they're not the best grouping. Quality varies between lines, but we're always going to have this problem with the English language descriptions. So we need to do something different. So the solution is, thankfully, rather simple. You just split each description into its subgraphs first. So if you say you have this description called description, you can kind of visualize it, and you can write some codes to this as well, and be like, oh, there's actually two separate graphs inside this. Then we just split that up into two separate groupings, and I'm going to label the first one as slash A and slash B, and you'll see that in the visualizations later. So, yeah, we can take the English language descriptions, but split them up first, run the same algorithm, and we get this for the northern line. This is already a lot better than what we had previously. You can see the graph is mostly straight lines that only connect to each other at junctions instead of a big bunched up mess. Let's take a close look at some parts of this to examine the quality again. Some parts of this are beautifully straight as before. This is mostly good. You can see, you probably can't see, in fact, but at the bottom, we've got approaching south Wimbledon slash A, so it's identified that there are two bits of track that are called approaching south Wimbledon, probably for the two different platforms, and split it up into two different sections as it should be. So, that's good. We also have a lot of intermediate blobs. So, for example, between tooting Broadway and Collier's Wood, we have between tooting Broadway and Collier's Wood, and approaching Collier's Wood, we don't really need that level of detail. They're just the bits between those two stations. It would be nice to group that together. Looking at another part of the graph, this is also mostly straight, but there is a small issue. Stockwell and Clapham North are next to each other, and there is no junction there, but somehow it thinks there are multiple ways to get between these two stations. This is not correct. So, in summary, the strategy produces pretty nice graphs. In general, our strategies seem to be making things incrementally a bit nicer and cleaner, which is good, motivating. There are still problems, though. We have too many bobs now. We have to combine them, and we also have to deal with the multiple paths problem. And, actually, I have multiple ways to get between these things where there shouldn't be problem is actually somewhat familiar. This is the same problem we had earlier with the track codes with a very similar solution. So, here's a sort of slightly crazy thing I came up with to deal with this. So, we want to simplify paths between stations. We start by looking at each station in turn and finding all the paths from that station that end in other stations here in red. We consider each path in turn, so I'm just going to take this red blob and examine it separately. And looking at each path, and this is just the red bit, we take all the blobs between the start and end station blobs and just smush them into one new blob, representing that whole path. Now, you might think, well, what if there are a lot of them, and what if they're linked together? This is where we use the topological sorting. We topologically sort the removed blobs and links and then shove all of their track codes in that sorted order into the new one. This wasn't a problem in the previous graph, just to make things simple, but it happens in real-world ones, so it's nice to have that in there. But, basically, after applying this process, we can go from a graph like this, for the paths between A and B and C, to one like this, where the intermediate nodes represent paths between stations in a much more useful and interpretable way. So, we can add, run the graph through our freaky topo sorting machine to our strategy, and rerun the graph generator one more time, and we get out something that actually looks pretty great. This is the northern line again. We zoom in a bit. We can see that, actually, this is done a pretty good job at representing the line faithfully. The intermediate blobs have been made from collapsing things nicely. The green arrows here, you can see we've got into 2835 between Angel and King's Cross and 2842 between Houston and Mornington Crescent. You might think, well, there's that pink blob in the center. That looks complicated and ugly. But, no, actually, this is the Camden Town Junction tunnels. This is actually really complicated in real life. So, actually, I think it's pretty cool that it's managed to figure that out in a way that it can actually use to make decisions without me having to tell it that, and without me necessarily knowing that this was the thing that existed underground. So, yeah, we've managed to go from just making observations about trains, from scraping the API and noting down everything, to having a mostly complete model of the network with tricky junctions and everything represented pretty well without having to input any of this manually. I, for one, think it's pretty cool that you can just write some code to figure all this out. And that's pretty cool. But it's not all roses. The district line is still an ongoing issue. We can do this for all lines except the district and other subsurface lines, but the district is really quite bad.  This is not very usable. It probably can be fixed eventually. I used to do a bunch more thinking, but it's more work that I haven't gotten around to yet. Talking of stuff that is more work that I haven't gotten around to yet. This scraping stuff is kind of not great. It would be nice to be able to poll a bit more frequently in the 11 seconds, but I have to do a whole bunch of other stuff to enable that. And there are a whole bunch of other data quality issues, like the train destination that's shown on the website often flaps back and forth, which isn't great. It's a lot of time and effort to track these down and squash them. I have a day job. This is not what I do full-time. I don't necessarily always have time and effort. But this has been packaged up into a nice, lovely website, which you can use on your phones, which is actually mobile responsive and on desktop. You can click on each individual line if it's not the district line that is. And you can get a nice display of the line and all the trains on it, which is kind of cool in many different directions. And you can click on each individual train and you get this history of where exactly it has been, how long it has been there for, and it even updates live with web sockets, which is pretty cool. Some brief notes on what this has actually built in. The back and in front end are both written in common list, which is a strange weird esoteric programming language that I actually quite like. All the live data gets stored in Redis. And historical data is archived both on disk and in click house more recently. The main goal is, this is something I'm working on in my free time, make it easy to hack on it without much faff. If you like diagrams, here is a diagram of Intitube. We're getting data from TrackerNet. There is a service called Intitube scraper that does a lot of the processing and sort of the modeling and stuff, and solves all of its stuff in click house and Redis, and Intitube web can read out of that display to users.  One idea I had was, you know how TFL give like minor delays, or maybe you don't. TFL give updates on the state of the lines like minor delays, severe delays, et cetera, but this is all manually input. It would be nice if you can actually, I've got a whole bunch of historical data, you could figure out the average running time at a particular time of day, and then compare it to that to figure out whether it's actually delayed. Actually, some other people have this idea, and they beat me to it, and I'm really mad. I'll get around to it at some point. In general, it would be nice to do a whole bunch more stuff with the historical data that I have, like maybe rewinding the whole web page to an arbitrary point in time. I'd like to build maybe some sort of funky live map visualization of trains moving around the network. I know there already are funky live map visualizations of trains moving around the network, but those are mostly like lying, and being like, well, let's say it would arrive in two minutes, it's probably going to arrive in two minutes. I have the actual data, I could build on this more reliable, and there's a whole bunch of other stuff. Talking of having actual data, do you want this? I have months of tube data. Quality cannot be guaranteed, but if you want to run some sort of cool analysis on historical tube journeys, please do get in touch. I'm more than willing to give this to you. I also have a private beta real-time API that is much easier to use, and hopefully much more prominent than TrackerNet, mostly because a friend of mine was like, hey, I really want your data. Can you build an API for it? And I was like, yeah, sure. So yeah, get in touch. But yeah, so that is basically it. Thanks for listening. Hope you found that interesting, and feel free to try it out on your phone or whatever, and if you want my data, please feel free to find me afterwards or contact me using the link.