What's the word y'all if you're so good to say those words man I've been on the road if you don't follow me on Twitter and stuff We did a live show in San Francisco did a live show in LA with Jamal croff It was a blast But I brought all my equipment because I'm like the NBA season is starting I gotta get out there make the content and I kept running to technical difficulties The mic was trash the Wi-Fi at the hotel head and so that it would take 19 out Just know I'm here and I'm ready to talk hoops So every team has played at least one game And I want to give you all my first impressions of all 30 teams before we do that Let me tell you about our sponsor prize picks hit the link in the description download the price picks app and use code Kenny kids are matching all the pods up to a hundred dollars I love price picks because it's just you versus the numbers pick between two to five different players You look for stuff like points rebounds assist You look at the number and you tell them if you think it's gonna go more or less than the number I put together an entry last night because I'm playing every single day And it was so very close for being five for five But the good thing about a five is that it's always a flex play so since my Tay Morris didn't hit his number I still walk out in the green again I'm playing every single day and I know a lot of people out there are too So hit the link in the description download the price picks app and use code Kenny so they can match your deposit up to a hundred dollars Hey bear with me y'all because we are talking about the first impression some teams have only played one game And I remind you I was on a West Coast road trip We flew into San Francisco and drove all the way up to Los Angeles We're in this big old sprint which was dope, but the Wi-Fi is trash So there are some teams that I've watched a couple minutes of and some teams I've watched complete games. It's a long season. There will be a lot of coverage throughout it Just just bear with me with the Atlanta Hawks the first thing that stood out to me was the fact that John Collins looks good And I was gonna say he looks different, but he has had seasons where he averaged a 20p So it's not like it's too crazy, but it feels like John Collins. His name is always on the tray block And right now he looks really really good It's like why do we even need to trade them the playmaker between Trey and Ajante has been added his world Both of them are killing the the playmaking game and the team just has a different vibe A lot of the times last season when I watched them They were going to fourth quarters with their back against the wall and they collapsed collapsed collapsed And the first few games haven't been necessarily pretty for them But they've been able to pull them out because they have just like this different feel and I would say they're they're Embarking on a different identity the bosses Celtics are still so damn good Like it's just that simple ladies Malcolm Brogdon's come in and immediately put his his stamp on the team He told the world why he picked Boston and why he really liked there and he showcased it Why Boston is really like that Jason Tatum has been really good through these two games I maybe it's a little bit overblown that that Robert Williams might miss X amount of months of the NBA season because the defense looks Really really good. I don't know what the Hornets are gonna do I set this in the offseason where I feel like they should be tanking tanking tanking because this is the year that you Want to tank but then I watched them and the small amount of minutes I've watched them so far this season because of a mellow not playing I'm being honest with you I'm not going out of my way to watch the Charlotte Hornets But what I have watched is that man with Gordon Haver is healthy He looks damn good and I'm thinking about them as a team and thinking about Gordon Haver Like if he can stay healthy for half the season that you can get a little some some form You know I'm saying there's they're gonna be teams out there that if Gordon can showcase that he can be healthy They're gonna be calling for him same thing with Terry Rogier But you do got like the downsides like James Book Knight doesn't even really look like an NBA player I mean I know he's got some other stuff that he's dealing with but boy his minutes have been hard to watch It was hard to watch a preseason. I gave the benefit of the doubt But it's been a game that I've seen and it was just really really rough the bulls a listen We're one on one on the season which is exactly what I expected I expected us to lose the first game of the year against Miami because they're the heat and I expected us to be the Was it was a flip flip way and that's pretty good considering Zach Levine hasn't played his plans tonight Which is dope. I will be in attendance be looking out for me And it's cool that we're one and one and not only two to start the season We're missing an all-star caliber player tomorrow still looks great Which is amazing and most of us through the first two games has been pretty good as well And it's the contract year for boots So you expect him to increase his play because we got to figure out how much you were big fella and a lot of bulls fandom I'm is revolving conversation revolving around Patrick Williams because you know number four overall pick a little while ago Went through the first two games It has been as bad as the numbers say if you look at the stat line The viewing experience is even worse than what the stat line is saying and boy Oh boy, do I want to get from the benefit of the doubt now I was I was one of those guys that mean oh the next kawai. I didn't really think bro was the next kawai So my expectations are not that but I just want him to be a contributing basketball player And as of right now He's not that and even on the broadcast with Stacy King and Adam Amin They're pointing out the fact that Patrick Williams just sits We're for that for a guy that's as athletic as he is He won't be cutting he won't be doing the little things and I thought that that was one of the things We're gonna get from Pat good defense and the little things he not doing those things So I'm luckily we got other players in the roster that could pick up the slack But like a lot of our future and a lot of our now is depending on Patrick Williams taking a step and Basically between the last time we saw him last season these first two games nothing has changed If anything there has been a slight regression and it's not great And I talked to Pat recently and one thing I forgot about him in his draft class is that they didn't really have time They didn't have a summer league. They didn't really have much of a training camp They got drafted in the season started basically like that But like that can't even really be an excuse like this other people within his draft class that has really taken off So I got love for Pat I'm not giving up on Pat, but it is it has been rough Cavaliers I completely missed their first game So I really don't have anything to say and I see Darius Garland's not playing tonight Which is unfortunate because I really like Darius Garland's game and I really love would have loved to watch and play again I think last season I went to two Cavs games And then this year I'm starting off the season by going to a Cavs game either way I did see the Evan Mobley attempted his first two shots with three point attempts And I'm excited about that and his ball handling look pretty good Look pretty fluid compared to your number one now again I haven't watched the full game the nugget scared me in that first game in a season I will be honest with you and you know what and even the second game against the Warriors, which is a win Did we jump the gun just slightly and I say we when I'm talking about myself I think I put them as the number one see because I'm just man Jamal is back a microphone He's back I didn't really think about the idea of Jamal Murray sitting out games because he needs to manage his injuries or You know just being on ministry tricks and stuff like that. They still like a good team Game to not so much a gay one either way I'm excited to continue to watch the different oh one thing that's in my notes is Can we stop just letting Michael Porter, Jr. Be strictly spot up? I know he don't move as fluid as other people in the league Especially with 17 back surgeries, but he's a max player. That's job is to sit in the corner. I Mean damn good at it. Don't don't get me wrong He's efficient is it pretty much anybody on the catch of shoe But it's like he should be doing a little bit more on the offense and I'm sure they're gonna incorporate that eventually eventually for the pistons I want to showcase a particular moment in this game And remember Kay Cunningham who we will be talking about is in year two of his NBA career as a former first overall Pig who looked really good at the second half of last season So I'm not jumping the gun or anything But I do want to showcase just one little thing real quick It just if there's something missing in it now again He's a year number two player but like in college he was a not basically a knockdown shooter and it's just so flat with his jump shot Now I'm not overreacting I'm not saying he'll never be a good shooter because I'm sure we will but it's something missing about his jump shot that I that you know it's worth talking about and that's not just me talking I actually saw pisses fans talking about in the timeline That's what made me go go back cuz I would I'm beyond so I wasn't watching Nick's Detroit Especially after the next pulled out very early on I was like, you know what I'll switch up on that one But Jalen Duran is only 18 years old and Jaden Ivy speed is translated so crazily to the NBA I'm excited about their core and game number two of the season Ben Simmons looked at the basketball Now game number one I could not say the same I think he had six points or something like that four point six points Whatever and all of his field goal attempts were like lobs You know I'm saying somebody getting it up to him and I'm like man Will he ever look at the basket and again number two he looked at the basket for exactly one quarter For exactly one court, I'm like Ben bro come on. What is going again? He ain't played basketball miss many months and I understand these type of things. I'm not asking him to be LeBron I'm not asking to be honest At least look like look like an offensive threat. There's even a moment where he passed up a dunk Similar to what he did to Trey young, but he gave it up to Nicholas Klaxer who was amazing yesterday I'm so nobody cared because they actually scored But like he was at the rim and he was in the air and instead of going up and just finishing the layup He dished it off and I mean, I guess this is play style But like you would want him to have that type of aggression Eventually because the dumb down won't always be there, you know, I'm saying sometimes the dumb down list of Matisse Thibault Who gonna get fouled he gonna miss half of his free throws either way They won a very close game probably my favorite game of last night and that's saying something because it was over times It was a lot of stuff between them and the Toronto Raptors and you saw they're like hey Katie and Kyrie kind of nice, you know saying eventually eventually they gonna get it going They were kind of nice knows after Katie's struggling and a lot of it Nicholas Klaxon was huge because the game number one they got dominated in the in the post or in the paint between Zion and Valonichunas and again number two Nicholas Klaxon came out and rebounded the hell out of the ball Especially on the offensive side and it really helped them win that game. I don't know what to make of the heat I've said on this show when we were talking about the NBA standing predictions that I didn't love their roster and through two games They've lost to One of them against a really good team. So you know I'm saying you're gonna win those You're gonna lose those the first one against the Chicago boys who are missing Zach Levine I still don't really know what to make of it. Um Tyler hero coming out as a starter has looked really really good Talk about the Kings real quick. Here's my notes. The Kings gave a 56 points in the paint 56 that was against the Portland Trailblazers who they ain't got no Yanis They ain't got no Zion they went against the Portland Trailblazer gave a 56 points in the paint Which is not great, but through the first three and a half quarters I was like, oh snap. Look at the keys. They are foxes locked in in the second quarter They had a lineup that was like four little guards and subbonus in the second quarter and that team Offensively looked amazing and they didn't go back to it down the stretch And then we got to the fourth quarter and the Aaron clanked a couple shots at the side of the backboard the Montessor bonus Traveled there. It's there y'all. I'm telling y'all it's there They got it They got to get more physical and don't get beat up down low and Keegan Murray got to come back That's sad. That's how I feel. I'm still pretty pretty high on this team Even after their kind of collapse if you want to call it that now I was at the Clippers first game in the season and it was magical man It was magical to see John wall back on the court and listen John wall hit the ultimate green light in his head You know in the offseason. He was like, I'm here to be third fiddle or whatever You could tell him that in game number one because when those first two shots went down He was like, oh, I'm still John wall and he was getting down here You don't have the explosiveness is like the prime version of him but then memories jump shot was really falling and They got they got so many pieces that like Terence man didn't even really play or a mere coffee didn't play it at all They just have so many competent solid guys And I think that's the perfect way you build around Kawhi because he will like tonight not play and the now We got we're gonna see a Terence man appearance or whatever whatever So I really like what they got going on man Zubat was amazing and he dominated the paint against the Laker The Lakers I've been them both of their first games I was there in the ring ceremony with the war used that was a complete blowout and I was there because the clippers where they played Slightly better I'm better enough for like it wasn't a blowout on national TV You know what I'm saying and man and game number two made me feel a little bit more optimistic the game number one And that's saying something but they maintain their position in the game through solid solid defense I know I know I know that that Russell Westbrook shot 0 for 11 from the field But defensively he was doing this thing There was like back-to-back possessors where they were trying to get kawada ball in the post and Russell was like nah I'm not having it. He literally said no I'm not having it after a timeout was called like he was doing this thing defensively. Obviously 0 for 11 is never good no matter the caliber of player But they're just not shooting LeBron said it everybody that watched these games saying they're like we got to the fourth quarter And they had already missed a hundred three-point shots. They had stopped taking them and now I don't blame them You know they missed so many but it was like driving kick to nothing driving kick to nothing driving kick to nothing Yeah, they talking about we gonna maybe make some trades around Thanksgiving, bro Y'all might be in a big hole by Thanksgiving, you know, but the but I'm gonna say this about another team They've gone against two of the best team two teams that people are assuming are gonna make title runs and the Clippers and the Warriors So let's see what they look like against a mid-tier team and we'll talk But like not having shooting around LeBron is ultimately ill the Madness gave a big game against the Phoenix sons But one thing we can't take away is that Christian Wood as a pickup look pretty pretty good And that was one of those games that I wasn't able to watch in real time Memphis's scouting department. I tweeted about it is some of the best in the league They'll find somebody and you're number one He'll just sit on the back of the bench and their development department gets them to some decent like Salty Aldama And that first game against New York Knicks where he could not miss and he's playing good defense And then again number two Jake LaRavia came off the bench And I think it was David Roddy came off the bench It gave them very quality minutes, but deeper than that John Moran is just a different kind of monster It's all we really need to say you watched it you saw the stat line He's a beast the box managed to beat a really good 76er team without Chris Middleton and would you holiday having a bad offensive game in a game that was like 90 total points That's one of the reasons why I like them. They're resilient and they're good I like what what do you want me to say about my first impression about a team that I was already Saying it was gonna win the championship. You know what I'm saying. All right Spurs fans beyond switch Have not watched have not watched. I have not watched. I have not watched I've been checking the box scores Haven't watched you the pelicans have so many different options the Zion hasn't given us a great performance just yet And it hasn't even mattered. It hasn't even mattered. You know, I'm saying big valve coming and give was a 30 and 17 Brandon Ingram's gonna get you a dub CJ's gonna get you a dub and they got trade Murphy off the bench and yesterday I was expecting more Jose Lvarado than what we got But they have depth on his roster that wins Zion is actually, you know Shooting more efficiently like he has never bad game don't get me wrong He has a shot officially whatever once he decides to really put it together together This team is gonna be really really scary The one thing I'm a little bit afraid of about this team defensively is once they go against the team that moves that ball Because so far they haven't done that they haven't gone against a team that is really ball movement heavy until we got to like the Second half of yesterday's game and it starts to swing around and I was like, oh The defense get kind of cracking a little bit in due time. We'll see Jalen Brunson was earth every single pinion In fact, he has zero turnovers. They had this graphic. Oh my god. Let me find this graphic These are all the starting point guards in recent Nick's history. Are you kidding me? I knew it was bad But this bad is crazy and now Jalen Brunson comes in and he is he is undoubtedly the best Point guard that they've had starting point guard they had over a decade. Palos first game was Insane and you know who also had a very good first game That was Jalen sucks and in game number two against the Atlanta Hawks train young was struggling And I'm giving a lot of credit to Jalen Suggs his defense on that then Jalen Suggs goes out with an ankle injury Which is unfortunate. I think it's just a sprain so he'll be back and then immediately tray young turned it up right after Jalen So like it's not a coincidence. You know benedict matherin or is it methoron? I still don't know Um told the world after he was drafted that LeBron got to show me he the best in the league His mindset is carried over tremendously This man is so so fearless get into the basket that he's him and Tari's are making Pacers games Super fun. I'll be honest like yesterday was a blowout until we got to their fourth quarter They almost put a 50 points in the fourth quarter. I hate that already that Jalen Smith kind of is losing his spot You know like um, he started the game struggled and then in the second half I think they went to goga and then one jalen once jalen smith got off the bench He immediately got hit and now he was out for the rest of the game But like I hate that he has such small of a leash in that starting spot There was like a game in the couple minutes either way Um benedict is enough to turn on the indiana Pacers It was so very good to see a real good damien lilor game in the off season I was part of it. I was like, I don't know what to think about the scene I really like to start in five But I was questioning about the rest of that the lineup when we get to the bench and through the first two games It hasn't hasn't mattered too much. I mean, I mean they got a real damien lilor game 28 points going into halftime was absolutely insane and game number one I love that they went small ball. It was only for a couple minutes It was half of a quarter just as windsaw at the five. He was guarding some bonus.  He already is a stud He's gonna be more of a stud But it's trying to figure out the rest who else added this young cord that we believe in I love the jabar smith junior in his first game was like i'ma shoot every shot I saw In the second game the shots weren't falling. He decided to steer back I want him to stay aggressive even if he's shooting it efficiently because we spit this pick on you We want you to get your reps out and I see a lot of rockets fans like man. Nobody talks about jalen green Nobody talks about this. I think that's completely okay Because once is once it comes down to it Once jalen green continues to showcase this talent in this talent. It's going to be impossible to ignore So let him continue to do his thing in the shadows People will notice y'all people will I promise you the 76ers are owing to Now they were my team to come out or to win the most games in the eastern conference Not the greatest start and their defense they played against two top teams also But you have to beat the top teams to be the top teams now I don't like the way I way I've seen the body language and the productivity from joel and b through the first two games And him going up and not talking to the medium af media after gate number two is kind of crazy It's a second game in a season bro. He seems out of shape The good thing is that james hard and looks great So if we could get them on the same page where you know joel is back in shape and james still look asyle Everything is going to be smooth. I like that the suns are incorporating deandre aidenmore That's pretty much all I got for them so far through the first two games of the season Deandre aiden is getting more touches than he did last year and that's great for not only my fantasy team But for him and I think for the overall team because he is so very good once he's five feet away from the rim Those bunny boom boom boom still easy bucket bucket bucket He didn't miss the free throw down the stretch yesterday, but still I love that he's being incorporated more If i'm not mistaken the thunder if only played one game against the timbles and they play again tonight I have not been able to watch them. My apologies thunder fans. I really don't have an opinion right now The wolves are one in one which is terrible considering what their competition was for the first six or seven games of the season I mean, I guess the jazz is better than we expected, but still They they have way more talent than that jazz roster And it went into overtime and they completely went away from what was working down the stretch It was a lot of anthony ours and carltony towns. I love him He's he's a great person and a great player, but I get these moments where he's extremely frustrated to watch We're like in this game They went away from from ant was like, okay carltony towns is a top tier player in this league too So I understand going to cat But like after a couple misses of him's fortunate and after a couple turnovers You're like, can we do the other thing maybe go back to the angelo russells He's a clutches man over the last two seasons of basketball go back to anthony ours because that's what was working You know, they still have a lot to figure out as a team that added a new piece So it will come together, but that last loss wasn't very good. Pascal siakam is is good man I mean what more can I say he said he wanted to be top five and I love the idea of having A higher up goal. He probably won't end up top five But he looked like top five in that game yesterday We're like nobody could guard him and and for a year or so when they were down in tampa One of the running jokes on Pascal siakam was like, oh if he ain't spending he ain't scoring And that's that's not the case. His bag is so very deep. You know, I'm saying we talk at Euro steps We talk at step backs. We're talking mid-range. We talk at three point shots at least last night He the the spin move is still effective. Don't get me wrong. He just has so much in his bag Um, and and they were they were lacking bench production the other night. The jazz are too good They're too good for their own good now. They have 12 picks or 15 picks for the future But this is the year where where your pig matters most I mean, I gotta pick up the phone and try to figure out who to get my colony to I gotta pick up the phone to get Jordan Clarkson out of here because they went in too many games And I love that larry markon is getting as many touches as he wants But they gotta chill they gotta chill and this is probably a hot start and eventually they're going to take a loser's league But man, they look damn good through the first two games The words are the defending champions and I still believe that they have championship pedigree They're still going to be a tinker peter for championship Um, and I don't really have much to say similarly similarly to what I said with the bucks It's a team that expect to be good and first two in two games They they've been good and I know they're one in one But they've been good enough for me not to be like, oh, let's panic or oh, let's overreact They they eye they got it and the wizards I I enjoyed watching yesterday's game against the wizards not not because we lost But because that wizards throwback jersey is so damn beautiful And I must say they were surprisingly good through the first two games of the season Kyle Kuzma has been lights out. He killed us last night and bearded Chris stops is is handling the ball doing great things and of course, Bradley Beal Had another good game against the bull. So I I'm happy about the jerseys and that's the team that's going to be in the running for sure I think that's all 30. I swear. I might have skipped over some my apologies. This is already going too long Leave a like more green caps as we continue the season. Thank you so much for watching


Do you hear me? Actually, yeah. Excellent. Well, ladies and gentlemen, hello again. Well, we'll be having a session, a brief panel session actually, that will be occurring for one hour about upgrading medical practice with Wikidata. So this is a part of the project, Wikimedia Research Funded Project. You can scan actually the report for that project on the right. And that project is a collaboration between Wikiproject-made data engineering at Semantec's research unit from Tunisia and the University of Virginia School of Data Science from the United States. Yeah, so that's the name of the project, just for your information. And well, just to reveal how the panel session will be occurring, actually we will have 20 minutes to present with the state of the art of medical Wikidata and then we will have the 35 minutes of discussion between the panelists regarding the state of the art of the usage of Wikidata in healthcare. Yeah, so now we will have a brief tour of introduction of the panelists. So we were supposed to have Daniel Michen, but he was not here due to some circumstances, but we have myself, Laine Raspberry, Thomas Shafi, James Heyman, and Mosa Bennett. So we'll get everyone to have a brief introduction of himself, we'll start with James. Perfect, James Heyman, I'm the chair of Wikiproject Med Foundation and I've been involved with working on Wikipedia's medical content since 2007. I'll hand it over to Mozab. My name is Mozab, I'm a medical doctor. I am also part of Wikimedia Medicine. I'm a membership admin and I have been contributing to Arabic Wikipedia since 2013, mostly in Arabic content, medical. Yeah, so my name is Thomas. I've been contributing, I guess, since about 2014. I don't have a medical background. I'm a biochemist originally and subsequently a bioinformatician and data scientist. But my interest is in, I guess, academic Wikipedia collaboration and ways to bring in Wikimedia contributors from those sorts of demographics that don't normally contribute, but could. My name is Lane Raspberry. I'm a Wikipedia at a university in the United States. I do medical information and content related to LGBT people and LGBT topics. Yeah, so I am a husband in Turkey. I used to be a medical student. I am still a medical student at my home city in Sfax, Tunisia. I'm also involved in Wikimedia research, particularly computer science research and have been involved in creating our Wikimedia research structure at my university, data engineering and semantics research unit. So I have served in several positions, including the Wikimedia CUT of last year, the board of Wikimedia Tunisia as well. So, all right, after this introduction, let's go straight to the point. Yeah, so as you have seen, we are all Wikimedians, but not only Wikimedians. So we should benefit from every single open resource within our movement. And this is not what many Wikimedians think. Well, why we should actually look at Wikidata? Well, it is structured ontological database. Having statements in the form of triples, it has a multilingual support, semantic unlimited to external resources, plenty of tools for a person at a rich data base, and it is linked to Wikipedia. So we can play with it in a variety of shapes. So, it is a rich network of medical knowledge and it can be easily extensible to cover new topics. For example, during the COVID-19 pandemic, there was nothing by the early month of the disease, but just in four months, look at that. We have actually a whole taxonomy about COVID-19 related topics. We have the three pillars of the graph, the COVID-19 pandemic, the disease COVID-19, and the virus, which is SARS-CoV-2. And we have all these three items, actually major items, are related to themselves and actually they are related to variety of medical classes and non-medical classes. We have genes, proteins, taxons, actually humans who contracted the disease, kind of symptoms, vaccinations, drugs, et cetera. And that just in a few months. However, although this is a huge achievement, actually, UkiData, mainly when we talk about medical information, has several limitations. And that's why it did not go to the next stage of using it in developing medical applications. The first limitation is that medical statements and UkiData have limited number of references. Some statements are not imprecise. For example, in this example, you have the sign of appendicitis as abdominal pain. It did not show which part of the abdomen actually is the place where the pain is. And actually it should be the right lower side of the abdomen or at the early stage it can be gastric pain. So that lack of actually precision can actually let people not take seriously the database. Also, we have seen that a lot of external resources are not fully important. And when we talk, for example, about OBU ontologies, the open biomedical ontologies, we find that 40% of these ontologies are mass important to UkiData. Although they are open-licensed and there is no legal constraints to actually download, upload this information to UkiData. Yeah, several types of information are still not supported. For example, where diseases are located. For example, for the Ebola hemorrhagic fever. We have them up on Wikipedia, but actually this is not converted into statements in UkiData. Also, several medical classes do not support actually validations schemes. For example, we have no entity schema, no data model, and no entity schema for many important medical classes in UkiData. For example, we have no entity schema for surgical therapists, for example. And this will lead people to define the thing in a different layout leading to some scattering, some inconsistency, and so on. Also, some kind of relation types are misused. For example, Besheh disease has phenotype uveatus. Probably this is because there is no, the relation type that should be used is not in UkiData. So there are a number of cases that are misused in UkiData. So there are a number of cases that are misused in UkiData. This is not in UkiData. So they are doing some approximative work to actually get the closest relation type and use it instead. So here are the problems. So we need a plan for action. So what we can do, actually we can raise awareness about UkiData as an open medical resource, and you can arrange and validate medical knowledge in UkiData. Finally, we can create tools to reuse medical knowledge in UkiData. How to raise awareness about UkiData? That's pretty simple. Actually, there are several works in this context. So first, we can make UkiData useful for the UkiMedia community. For example, doing like supporting info boxes for medical articles in UkiPedia, kind of for travel guides for UkiVoyage project, if they are traveling to epidemic countries, et cetera. Also, we can share UkiData with the scientific community and show in how UkiData can be a flexible hub for the semantic research and how they can be useful actually for scientists to develop their ideas, et cetera. Now, let's show how to arrange and validate UkiData in a variety of paths. Yeah, so actually one of the main ideas that we propose to do is actually to make a framework of interaction between UkiData, open biomedical ontologies, and PubMedMesh keywords. For those who do not know, mesh keywords or medical subject headings are controlled keywords that are existing in PubMed. So the association of mesh keywords in a single article can mean that the two words that are co-occurring are related. And so using this combination, we can actually generate semantic relations just by leveraging PubMed. Concerning open ontologies, many ontologies are aligned to UkiData. We have now 15 ontologies that have operational UkiData properties. And so they can play on that, actually ameliorate the coverage of these ontologies, and work more of that. As well, we can actually use PubMed to get references to unsupported UkiData statements. We can verify several relations in UkiData by comparing them to external resources, et cetera. So all kinds, actually, of interaction between these three sources is possible. And we can play more and discover more things and actually develop that, et cetera. Yeah. Finally, concerning the creation of tools for reusing medical nodes in UkiData, well, this is mainly not done actually to take the place of the physicians. Many people actually understand biomedical informatics wrong. Actually, it is there to help physicians to do the dirty work, the dull work, the dangerous work, the dear work, et cetera. So what we mean here is that physicians have serious work in conditions, and they need to go through night shifts, et cetera. Lots of information to handle at the same time. Patient data are not like in the book, as we may say. So that thing actually cannot be handled by the doctor without any help. So he should have some resources, some tools to help him around this mission. And even artificial intelligence will not take over the physicians even in 100 years because there is even machine learning models will not deal with rare diseases where data is not available. So we will always need physicians at medical specialist. Yeah. So a few examples about how actually to use UkiData in this context. Actually, we can use UkiData actually, mirrors of UkiData, to actually annotate electronic health records and actually for doing some medical reasoning about the patient's status to do some prognosis or to revere drugs, et cetera. So that's the first application. The second application is that we can actually give UkiData kind of some information, anonymized information about patients. And UkiData can provide us the answer about how to deal with the patient. For example, if we give the list of the drugs for a given patient, it can return to us the drug interactions, the symptoms and you will have the medical diagnosis or the complications, et cetera. So this tool actually is called medicine. It exists. We have developed it. And if you scan the QR code on the right, actually you will get into the URL. You can test it yourself. It is multilingual and that's an advantage about clinical decision support based on UkiData by contrast to the ones that are on the market and that are unproperatory and mainly monolingual. And if you click, if you actually scan the QR code on the left, actually you will get all the source code and it is open source and you can easily figure out how it works. Yeah. There is also the COVID-19 dashboards. I think most of you have learned of that. Actually, what we do is that we enrich UkiData with real-time information about COVID-19. And actually, we have some predefined Sparkle queries. And what the dashboard does is that it gets the information as soon as you access the tool, the dashboard, at this actually information is updated in near-lead time. This means as UkiData is updated with new information. And by this fact, actually you don't modify your tool but actually as it gets information all the time from UkiData, you will have it there and it will be updated automatically to give you all the consistent information and recent information that can be used by physicians or by any person who is interested in medical code topics. Yeah. So these are all the references that I have used for this research. Most of them are developed by us, the panelists. So you can see in both our names in some of the papers. Yeah. And now, actually, let's jump to our panelists actually to discuss more about actually how to move forward with the application and the use of UkiData in medicine. So the question number one, what are the good examples of UkiData benefited in patient care or public health on a local or global level? Anyone to answer? Okay, Hassan. So during our session, we talked about medicine. If you remember the previous slides, medicine is a tool that is used to see the drug interaction. Most of us, like even physicians, there's hundreds of drugs. Not every physician can remember or memorize by heart every single interaction. So, for example, if you go to the tool and you put, for example, reef and basin, a drug used to treat TB, tuberculosis. If you press to find the interaction, you will find that it interacts with paracetamol, for example. So this is one of the fees that UkiData can help physicians in finding out what's the drug interaction. Other thing that we work together with our friends and panelists and also Hassan, we worked in the association between signs and symptoms and disease manifestations using UkiData items. So this is also another example. After making signs and symptoms more specific like the example Hassan gave about appendicitis and lower quadrant pain, this will help, for sure, it will not replace the physician because medicine is not one plus one equal to two. It's more complicated relationship. But for sure, when we give the computer or give the database a bunch of symptoms, it will help us to find at least a smaller list of differential diagnosis that will help the physician to then figure out the correct and exact diagnosis. So this is two points that I can make to this question. Anybody can think of something? So this is not necessarily an example of what's being done exactly right now, but it's an extension of what you were just talking about. So the way that UkiData handles drug interactions is not fundamentally different from the way in which it can handle other interactions. So for example, there are certain drugs that interact poorly with the parasite of humans called pregnancy. But also there are other conditions that can interact with drugs. For example, sleep deprivation can have effects on some drugs or even certain things like talking therapies or talking therapies interacting with other types of talking therapies. So the way in which UkiData is modeling drug interactions is extensible to a wide range of other relevant interactions outside of just the narrow scope of pharmacology. Exactly. And for those who are not from a medical background, I want to explain that why is pregnancy is called a parasite in a medical point of view because the fetus is dependent on the mother. He takes the food and he shares the blood with her. That's why in a medical point of view, we look at the baby as a parasite. Yeah, for sure, in the future. Thanks, Moza. So, you know, one of the other common uses of UkiData within the Wikipedia world is the use of UkiData items within info boxes and that allows a bunch of languages to collaborate on keeping certain topics up to date. You know, one of the unfortunate limitations of that is that, you know, the English Wikipedia hasn't bought into the use of UkiData at this point in time. And some of the concern around that is, you know, we don't quite have good mechanisms to feedback changes that occur within UkiData to the Wikipedia's themselves. And, you know, they're still working on efforts to allow UkiData to be used outside of the Wikis run by the Wikimedia Foundation. So hopefully, you know, from what I understand, the Wikimedia Deutschland, which is running Wikidata, is working on both of those problems and hopefully they'll expand the potential of these info boxes to be powered by Wikidata items. Yeah, I think so. Yeah, the question, member two. So what are the main pros and cons of UkiData as a central medical knowledge hub versus the traditional databases we discussed earlier? The advantage of traditional databases is the authority behind them, the control, the high quality that you get of not letting anyone edit. Of course, the problems with these kinds of things, they come with traditional values like closeness, inability to export and reuse to adapt to do translation or to move into other platforms to remix in different ways if it's a traditional database. Sometimes it's not positioned to remix and combine with other databases when that's necessary. When you have something like Wiki, anything's fair game. You can combine these things. You can translate them. You can remix them. You can export them into other products. Disadvantage with Wiki, of course, is maintaining the quality control. But in every talk that you hear at this conference, people are going to say something about quality. Quality is definitely a big concern for the Wiki community and in my opinion, it gets much better every year. I mean, another thing that a lot of people in this audience can talk to a lot better than I can is the interlingual aspects of it. I'm a native English speaker and as such, I only speak English, so I can't really talk about that. But I am interested in interdisciplinary research and one of the limitations with a lot of existing databases, they're hyper-specialized. You go to a medical database. It's only got information about medical topics. You go to a biochemistry database. It's typically only got biochemical topics. You go to an evolutionary database. It makes it hard to ask interesting interdisciplinary questions like which genera of animals tend to produce peptides that tend to interact with receptors that are associated with pain. Which is an interesting research question from the point of view of, which animals should I be testing to try and find new painkillers? That's the sort of question that is already actually still quite narrow in scope. There are far more interdisciplinary questions and asking questions across multiple topics. The WikiData is, to the best of my knowledge, the only database that even comes close to being able to have these sorts of hyper-diverse questions asked of it. Yes, and also other point is that the accessibility. WikiData for sure is a free and accessible database, but for other specialized databases, you need to pay monthly or yearly a certain amount of payment to get access to this. This is another thing. Also, it makes our work on Wikipedia easy because if I edit on Wikipedia and WikiData, a number, for example, a statistical number or I added some symptoms, it will be reflected on more than 300 languages, which also makes it a broader audience than some sort of special databases. Next question. Indeed. The next question is, what is WikiData's role in enhancing situational awareness for emergency responders and medical teams? That's a question. I will read the question again. What is the WikiData's role in enhancing situational awareness for emergency responders and medical teams? Okay. I will try to answer this question as best I can. As far as, to my knowledge, when we deal with sometimes with emergency situations, one of the things that we want to know sometimes when there is a poison, for example, was the antidote. And when there is some medication taken, what is if there is a medical interaction? For example, like sensitivity reaction, like anaphylactic shock and these things. If I think this is an area that WikiData can help if it is developed in a more simple way, for example, emergency and the first aid sometimes are provided by a layperson, not even a specialized person. So if our tools become more simplified, that would help people because when we are talking about coma or losing consciousness, there is sometimes medication as the cause, sometimes there is blood pressure as the cause, there are differentials. But if it is medication, for example, we can use WikiData to find out what's the antidote or if it's a scorpion bite, WikiData can tell us there is something called antiscorpion. If it is like, for example, drug toxicity, it can tell us what to do. Is it like activated charcoal? Is it like lavage? Is it like a certain antidote? So I think this is an area that WikiData can help. I'll answer the question. And also, I guess there's been an ongoing topic throughout the whole of this conference around the increasing role of AI, and I suspect that this is exactly the sort of situation that there's going to be an increasing reliance on AI in emergency situations, asking some AI assistance, not necessarily for entirely what to do, but maybe for some of the details of what to do, particularly from non-specialists or people coming across a particularly complex situation for the first time. A classic problem of current AI models, they hallucinate, they come up with false information, but they present it very confidently. And there's a lot of interesting work going on around how do you anchor those large language AI models to reality, and this is a more complex topic than just WikiData, but WikiData, I think, is a part of that that allows you to anchor some level of reality into these sorts of models. There's something else that's relevant to this conference, relevant to interdisciplinary multi-linguality. So many things are happening so quickly, it's amazing. I'd like to call out, disasters always happen, crisis always happens, it can happen for weather or epidemics or any other kind of disaster that you can imagine will never be done with these. And you need all kinds of diverse data every time a disaster happens. There's people at this conference from a project called OpenStreetMap. They make free and open maps. And if you have a crisis somewhere, you need high-quality open maps of the region. And this starts with interconnectedness with Wikipedia. So outside of our movement, but very much related, there's something called the Humanitarian OpenStreetMap team, and every time there's a crisis, people map out the region where the crisis is so that medical responders can go in. And often this starts with something seemingly silly and unrelated in the Wiki movement, like what is the public art? Children of natchoos are the artworks in the places when the crisis. But if a crisis happens, that artwork and those Wikipedia articles about the monuments, those become landmarks for other people to use to orient other things. In an OpenStreetMap, in the same way that Wikipedia has collaborative editing, OpenStreetMap will say where are the grocery stores, where are the buildings, that we can house people in case of a big storm, where people suddenly need housing? And this interconnects. OpenStreetMap in so many ways interconnects with Wiggy data. you've heard of this conference this is just a fraction of it because we're working with so many other open data communities and this is getting very complex and developing very rapidly. And actually just to add to that I don't do a huge amount of work with open street maps one of the things that is really impressive is also the speed at which it's updated you come across disaster scenarios well the map that you were relying on a month ago may not be accurate anymore you know this bridge no longer works these roads are no longer traversable this landsliders taken out a particular a particular road a particularly important other piece of infrastructure and the speed at which that information is updated is exactly like you know our wiki movement it's highly relevant and highly timely. Yes and also for wiki data we are talking about wiki now but what about the future we always hear about image processing for example in medical field radiology there is a there is like a saying that nowadays says after maybe five ten years the radiologist will be replaced by you know AI because imaging process by computer to a certain existence can help like for example lay people to know what is what is happening in this picture is it for example ebidural hemorrhage is it is it like you know berforated bowel what what what is the situation so it can give us information yeah next question yeah as James James you know just one one extra addition on the open street maps topic one of the wonderful things about their project is it functions so amazingly well in an offline environment and you know that that is key for a disaster is you know people need you know because during a disaster often people lose their telecommunications infrastructure they lose their electricity power infrastructure so having offline functionality which wikipedia does which open streets maps does but which all the for-profit organizations out there simply don't so we will head to the next question and yeah so the next question is in what ways does the utility of wikidata differ between common and rare diseases okay so for example for the common diseases information are plenty we are talking about rare diseases the information are markedly less than common diseases also the language difference is very big so when we are we are searching about rare diseases in for example in English we will find good information in comparison with like when we search about this the same rare disease in arabic so i think wikidata role in in in the trans lingual translations can help to bridge this gap because even when you talk about signs and symptoms um if we search in arabic for for a rare disease it's it's it's sometimes there the content is zero and that's what we are trying to do in in rich arabic content on wikipedia to to make this data accessible to wikidata and to make it in different languages that will help bridge the gap i mean even though the question is phrased in terms of common and rare diseases i think there's also a similar issue that comes up with diseases of the rich and diseases of the poor and the same sorts of biases exist in terms of the amount of content that is out there how in depth it's documented how accessible it is and you know the multilingual aspect as well so these are kind of very linked topics it's not just a question of the common versus rare aspect there can be extremely common diseases or common conditions that are treated very differently one of the things that wikidata still also doesn't do particularly well is treatments outside of uh pharmaco interventions so so drug interventions when we're talking about other sorts of interventions surgical interventions as an example that's come up but also various different types of talking therapy for psychological interventions right if you look at a wikidata item on a pharmacological intervention for severe depression those items are going to be far more in-depth than the equivalent items on a talking intervention and in part that's maybe because the the structure of the information and the data on a talking intervention is maybe a bit more complex it sometimes requires um more subtlety more nuance um more qualification in the way that that information is put up but it's also a reflection of the existing data that's out there and the current interests of the the community so i don't think it's a fundamental problem it's something that's going to improve over time i'm gonna say this from a perspective of kindness this is a non-medical perspective and i i i'm going to tell you something about the wiki community so if somebody shows up and they have a rare disease and they come to wikipedia or wikidata and they say i'd like to get more information about it they're going to be approached by wiki community members who are not have no background in healthcare who don't know anything about the disease i've never really even care about the disease but we have a community of people with library skills and they want to help people answer any kind of questions and i tell you tell you truthfully and i mean mean this sincerely in all kindness they will make a game of the rare disease these wikipedia editors are very proficient in library research and they will go out into the world and they will try to find every source of information that has ever been published on this rare disease and when they do this they will feel pleasure from this they will think it's fun they will think it's a game to find all available information so if you're talking about a very common disease it's less fun because there's tens of thousands of papers and tens of thousands of sources of information but if you're talking about a rare disease in our wiki community people get a great amount of pleasure to find the 10 sources in the world that talk about this and then deliver those to the person so that's something unusual that you will see in the wiki community and you can't play these kinds of games if you have a closed database or a closed community yeah so the last question actually how can healthcare providers be motivated to contribute to creating wiki data and maintaining data quality all right well I guess I've got a few things to say about that I mean one of the things is as many people have mentioned visibility within wikipedia wikipedia has huge visibility there are very few people who you'll come across who haven't interacted with wikipedia in some way and even though the reputation of wikipedia used to be extremely poor amongst academics researchers physicians clinicians I think that that reputation has been improving pretty rapidly and that's you know due to concerted work of the community in terms of quality referencing timeliness in-depth thoroughness etc etc all topics you know about in terms of wiki data it's not well known I mean people at this conference will typically know about wiki data but I think it's pretty knowledge about it is pretty limited outside of our community and so part of what can be done is I guess a boring answer of awareness raising under you know reaching out to practitioner communities who could find contributing to or drawing from this sort of data useful and interesting but simply don't know about it yet and the other aspect I think is working out systems of reward for it so people who know me know that I do a lot of work with a project called wiki journals now this is mostly focused on the wikipedia pros type content it's a way to try and draw in more academic expert professional etc communities into contributing content that can be put into wiki media projects by effectively effectively rewarding them with peer reviewed citable publications now that model currently works well for pros type content but I don't think it's impossible for it to eventually also work for curating a subsection of wiki data type content so you can imagine a scenario in which some expert on a particular drug class is asked the question hey we'd love you to go through subset of wiki data to do with this drug class is the information up to date are the references the best references to use are there other interactions that you've come across that will be interesting are there are other qualifiers that could be added that we're not including you're an expert in this topic but not an expert in wiki data so we can pair you up with someone who works in wiki data and we can work with you to write up the improvements that you made the observations that you made in a small mini paper few you know a few pages long but the ability to then publish that get it peer reviewed get it get a citable object means that you can put that on your CV and justify the time that you've spent you know that then means you can justify that time to your institution to your promotions committee to the next job you're applying for for the next grant you're applying for so those systems of reward can be really important for people who have extremely limited time and unfortunately the the systems that are set up currently have very strict definitions of reward for different types of activities and if your activities don't fit within those particular categories I'm sorry there's no reward for doing that so I think there's an extent to which we can make that interface between the wiki media world in general and wiki data in particular compatible with the ways of working that some other expert communities of potential contributors work but but don't yet exist and you know to add on that point as as a non-technical expert wiki data is difficult you know I think in pros as a physician I don't think in structured data so you know my work on wiki data always generally requires collaboration with someone who has the technical expertise to run scripts to you know upload the the data that I want uploaded to wiki data to you know when I propose new properties to make sure of you know I've structured it correctly so you know if we're wanting to pull an academia we need to form these partnerships between those who have the technical expertise and those who have the conceptual conceptual and and subject matter expertise and this is going to require pairs of people and I think that keeps a lot of academics away you know we within wiki data within the wiki media movement you know I know who to poke and who I can whose arm I can twist to get me you know get what I want into wiki data but as a new person to the movement it takes a lot of time to build those relationships and find people who are willing to help you on these technical projects and you know having a place within wiki data where people who are willing to volunteer and join experts in in solving their issues I think would be would help our movement grow over the lane so these two have talked about telling organizations during our reach about wiki data I'm gonna have a different perspective on this don't tell organizations about wiki data at all don't get them to engage what we really need to do and where the better fight is is just convincing people to have open content period because if people will use open access licenses for their papers apply open licenses to their data sets they don't need to understand wiki at all there's plenty of wiki people who will migrate their content into the wiki platform and universities and research institutes already understand this concept of openness if you just tell them open source software open access licenses open copyright do not make something private unless there's a reason to be private I'm not saying release personal information but if something ought to be public anyway then just give it an open license and the wiki people will take care of the rest I'm gonna do something I did earlier and answer a different question that wasn't actually asked which is kind of the but I think it's the mirror image to this so this is about you know contributing curating maintaining wiki data the other aspect is also getting it easier to pull information back out of wiki data and there have been some interesting early experiments again to be kind of a techno optimist in this with around AI and the ability to bypass the need to know sparkle the querying language in order to ask questions of wiki data so the example I mentioned earlier from this kind of multidisciplinary point of view about you know which which evolutionary groups of organisms produce peptides that might be that interact with receptors that are related to pain to be able to actually ask that question of wiki data is actually still quite complicated you need to be able to to write spark or code and even though we do have tools to help out with that it's still not trivial there's a significant barrier to entry and so you know you talked about pairing up people with subject domain knowledge and people with wiki knowledge I think that they will increasingly be a third member of that marriage which will be you know the machine tools to be able to facilitate that partnership so that we can for example ask that question just in plain language have the sparkle career written behind the scenes by an AI and maybe it has to be checked over by someone with with more wiki data knowledge but at least it's a first approximation to be able to being able to ask that question without having to have quite such a level of technical knowledge we have five minutes anybody has any question please raise your hands yeah I can why else some people take actually the time to reflect off questions I can make a brief clarification about what Thomas said actually the medicine tool that we showed earlier aims to bypass the sparkle thing actually you just need to choose using the elastic search using the search part that of a school year tool the same search bar we just get it and you search for the items the medical concepts and your reason about that you say you search for drug interaction diagnosis association complications and you click and the tool does that for you it writes the sparkle query and it generates the answer and that's all what it does yeah any question yeah thank you very much it was very interesting to listen to yeah how far we are going with wiki data and and I think it's there's a lot you're talking about this from a medical perspective but if we kind of try to expand this it's really huge what can be done there what I am particularly interested about is if you could tell me about your research journey like you have research questions you start with those questions right then you probably say I need to prepare the data to look if it's healthy if it's enough if it's probably I need to upload some data and some cues and piece probably to define some if they are missing assume you are having that you have also good references and you have probably common image which are linked to the items and how does it go after that like are you your models or your research is focused on the text or on the relationships of the data that you have or you are more and more using probably image classification or AI based tools to do kind of more out of the data that is there so I am not sure if the question is clear but I am interested to see how deep do you go on the data and in particular the model selection you use to come out with your research because I did not see the research yet but probably you could give a brief answer about that thank you yeah I can answer that actually well you are right actually actually when you are collecting data about a given disease actually you should formulate a research question you say that I know I want to know the semantic relations related to that thing to a disease to a drug etc and so what we would do is that you formulate the query at the bibliographic database which is we permit in our situation and so using kind of a prisma method but it is not totally prisma you can you can actually search for the the articles with higher level of evidence that are not retracted they are quite recent etc and then from that after you do that preprocessing actually you get the mesh keywords and in that part a second part actually begins in fact the mesh keywords have have qualifiers and the qualifiers actually informs you about the aspect of of the keyword that exists in the paper for example if you see a hepatitis c drug therapy it means that the paper is about drug therapy of hepatitis c so these qualifiers are predefined so we know them there are around 75 ones and so using kind of matrix of correspondence between the qualifiers of couples actually you can train machine learning model to recognize the relation type based on wiki data so that that's it is as simple as that then you will have the human validation step to actually reveal if this is correct or not yeah just very little extension to that do you use classical AI or you are focusing more on the deep learning models yeah because if I think about the amount of data probably it could be huge not that huge actually the relations between between mesh keywords in wiki data are are around 100 000 that's not that huge actually so and we are using concerning the models we are using actually three models one is svm support vector machine one is the cnn convolution neural networks and one is the dense model so quite state-of-the-art models okay we have the last minute any last question thank you very much for the presentation it was very informative for someone coming from a non medical background I just have a very simple question the tools are excellent we can see their their use and their added value to the field but how can you avoid having like avoid any tiny risk of having vandalism on wiki data because the information is very sensitive so if one thing is changed or misleading maybe it can goes that are some very harmful consequences thank you the best answer that I can give you is that there's 20 years of criticism of wikipedia and how vandalism works there's hundreds of papers written about this everyone in every country in the world has come up with this like every three months for the past 20 years so you read that and then you get a feel for the quality in wikipedia and at this very conference there's multiple talks of people developing artificial intelligence bots that are doing mass surveillance on every aspect of wikipedia to try to detect vandalism I will not tell you that the quality of wikipedia is good I'm not going to argue that I do think it's good but I'm not gonna not gonna try to impress that on you what I what I will tell you is that nobody in the world has identified an accessible source of information that is better than wikipedia I'm absolutely sure of that I guess one small thing to add is also just the number of eyes on on information is important because I actually think the the greater risk is missing information right if I'm standing here with you know an injection ready to give someone and I'm relying on some tool that tells me you know oh you know what are the contra indications when should I not give this injection and there's some information missing and I go fab time to give the injection like that's I would say a more common problem than someone going into wikidata and changing a piece of existing information it's it's actually going to be the the mistaken lack of information rather than a deliberate piece of vandalism yes for example for example that is a study in nature comparing the accuracy of wikipedia comparing to to encyclopedia britannica it founds that wikipedia is one and a half more accurate than encyclopedia britannica although encyclopedia britannica all know it's written by experts so we still have a trust in wikipedia we have we can argue academics in that but it is it's a long journey I think with time with time this problem will be solved and you know there doesn't need to be more checks and balances with respect to wikidata and you know my hope is that those will continue to be developed you know one of the key aspects is you know if if a change occurs in wikidata and that property is used in a wikipedia then then that change should appear in someone's watchlist so that then you have a greater number of human beings reviewing changes that occur to wikidata currently that doesn't work very well I know that is on wikidata's efforts but they have a backlog of things they want to do so it continues to be a work in progress one other aspect is also something that is incredibly baked into wikipedia's culture and wikidata is still catching up on references citation citations citations there's still a disturbing number of wikidata statements that are unreferenced and that's I think also a huge problem because that that also raises the barrier to vandalism and make can make vandalism easier to detect in the long run that if the it makes it easier to spot hey this statement either doesn't have a supporting reference or I can go to that reference and very quickly check to to verify it and so the the way that wikidata has so far evolved has led to a lack of references for some of this information that's changing pretty quickly because there's been a concerted push in that direction but I think that's still a current significant limitation thank you very much actually this is my contact so if you can if you have any further questions and you need to reach out to me these are my contacts you can reach out the phone is actually available on whatsapp and telegram you can reach out to me and there are also on the back there are my business cards as well as the business card of the head of research for my institution so you can grab it and actually contact me thank you


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This research paper proposes a new method of using acoustic tweezers to manipulate living cells. The authors use genetic engineering to create bacteria with gas vesicles that could be manipulated by ultrasonic waves. These bacteria were then used to trap cells in clusters and move them around in a controlled manner. This technique was tested in both in vitro and in vivo settings, demonstrating its potential utility in medical applications such as cancer treatment. This article was authored by Yi Yang, Yao Zhong Yang, Ding Yuan Liu, and others.


Welcome to JSA TV and JSA Podcast, the newsroom for telecom and data center professionals. I'm Laura Noland here in beautiful Honolulu, Hawaii at PTC20. Joining me now is Donny Chung, the product director of NexusGuard. Welcome Donny. Hi, hi Laura. For our viewers, tell us who NexusGuard is and what you do. NexusGuard was founded in year 2008, and for the past more than 10 years, our sole mission has to protect our customers from DDoS protection. And we do it on three layers. We protect them on the application front, we protect them on the network, all the origin front, and last but not least on the DNS front. NexusGuard's infrastructure and our technology is proprietary and fully self-built and continues to evolve according to the requirements of the market. And today, NexusGuard not only delivers the best solution in class for protecting customers on DDoS attacks, we are also the only company that has a unique service offering that is delivered and catered for CSPs. What are some of the challenges, the DDoS mitigation challenges that carriers and service providers are facing today that you're noticing? I think one of the challenges that most CSPs are facing in this industry is revenue growth and sometimes in certain cases defending their own revenue. With downward pressures of pricing and competitors and trying to differentiate their service and products, they have to look for new revenue streams either by expanding their customer base or looking at new targets or maybe increasing their product portfolio. And one of the ways to do that is usually to look at their core services and to build services around that. And most of them are not. DDoS protection or other security services becomes one of the most strategic and organic road to take. But as a traditional layer one, two or three companies trying to build a service can sometimes be very challenging. From trying to find the best fit solution, implementation, go to market and delivering a service can be challenging. And that's where NexusGuard really comes in because we have a very unique offering to help CSPs overcome those challenges, get to market and get new revenue streams. Donnie, how do we address this challenge as an industry? So typically the DDoS problem for the industry, for CSPs in general, has been seen as an operation cost, as an operation problem. And this problem has always fallen to the shoulders of the network providers, engineers team, to uptake this as a noma. How they do it is to spend considerable amount of investment as a capital expenditure and then hire and maintain a team to keep the solution going as long as they can. The resultant in fact of that is while they protect their own infrastructure, they are able to pass on some of their value to the customers. So since these customers, while they demand such a service from the carrier, they receive it in a very ewe-defined manner and sometimes not clearly defined and therefore the solution sometimes doesn't work. So I think one of the challenge and how they can actually overcome this is to look at the way that they're dealing with this. And they can turn this capital expenditure into a revenue generating cost. And fully productise this service so that they can actually deliver at the same time protection to their own infrastructure, but create a solution that really works for their customers. And how can we take that a step further and actually transform DDoS mitigation for service for carrier service providers? So like I mentioned, so with this solution, if they actually change the way that they think and address this solution, looking at not from a cost perspective, but an opportunity because DDoS is going to not go away, it's going to be a constant problem for CSPs to deal with. But instead of looking at it as a challenge as a problem, they should look at it as how you can turn around and then capitalise on this opportunity, turn it into a service so that they can not only get new revenue, but deliver more value for their customers. Because as consumers, as you buy service from carrier service providers, it has become kind of like an inbuilt part of our request that the service that we're getting from CSPs has to be of certain quality. And most oftentimes, we expect that security is an inbuilt feature, if not an option for us to purchase. And current standing is CSPs are just not equipped to be able to deliver that. And Nexus Guard is here to help? Definitely. Like I said, we are the only company with this unique offering that is catered specifically for CSPs. Wonderful. So tell our viewers where we can learn more about Nexus Guard. Information is generally available on our website. We are on Facebook, social media, Twitter and stuff like that. And I think if anyone wants to reach out interested party, can always reach out to us, schedule an appointment. Our reps and partners from all over the world will be readily available to get in touch, to have a friendly discussion, in-depth technical discussion if they want to. Well, thank you very much for joining us, Donnie. We appreciate you having you here. Thank you, Leila. And thank you for joining us here on JSA TV and JSA Podcast. Happy networking.


In the last couple of weeks, I've really spent several hours each day focusing on cleaning up a lot of my personal projects over on my GitLab. You guys have seen me make videos about some of this recently regarding DM scripts and shell color scripts. Well, most of the last two weeks I've spent actually focusing on my website over at distro.2 because I wanted to completely rewrite the website, redesign it. I previously maintained a small website that I wrote in org mode and I used Emax org mode basically to publish a static HTML site. Well, I had something a little grander in mind. I still wanted to use org mode, but now what I wanted to do instead of maintaining a site that had, you know, 20, 30 pages, I wanted to see how org mode would handle a website that had around 22,000 pages. Now I know some of you guys are going to say, that's crazy. You would write such a large website, a static website using Emax and org mode, right? Well, that's the point of this is I wanted to see how viable of an option would it be. Could you actually maintain a rather large website using strictly org mode and Emax? So before I go into the details of how I created this site, let me actually show you the website in its current form. So this is distro.tube and what I did is most of the documentation here, most of the articles and things, they have been on my previous versions of the site. But what I wanted to do to really push the boundaries is now I have this section here called Linux man pages. What I did is I took all of the man pages that were currently installed on my Arco system because I have a rather bloated system because I have a ton of stuff installed on my main production workstation, mainly reviewing software and things like that. So I grabbed all 21,500 and something man pages that were installed on my system and I converted those man pages over to org and then I have to convert the org over to static HTML. And this seriously took a lot of time. When I say this took me a couple of weeks, it took me a couple of weeks to do this. Now it's one of those things that took a long time. There's a lot of upfront costs but maintaining this going forward I think will be rather simple. You see under the Linux man pages, I have it broken down by section. If you're not familiar with how man pages work, they're actually sections of man pages. For example, if I did a, I don't know a man on man, you see man and then out to the side you get a number one. That means that that particular man page, that program man is section one, meaning that's one of the executable programs or shell commands. So that is what that is. As you can see, there's about 10 or 12 different sections of man pages. And if I click on one, we'll do section one here. Section one and I believe section three are very large. There's many, many thousands of man pages in those sections. So instead of having a really lengthy list of man pages to view on one page, I broke it down alphabetically. For example, A and then here are all the section one man pages that begin with the letter A. For example, I could read the man page for audacity. Let me click on audacity and there is the man page for that. And you can see some of the styling and the CSS, which I didn't spend a ton of time on the colors and everything. I kept it kind of similar to the previous version of the side. I made it a little darker. Something I did want to add because I spent so much time with these org documents in Emacs. When I converted it over to HTML, I wanted to keep the bullet points kind of like you have hitting bullet points in Emacs org mode. Let me show you. So let me navigate to the GitLab repository where I have all of the source code for the site. And let's look at the index page here and you can see Emacs org mode. You see the bullet points that I zoom in here. I wanted to keep the same style bullet point, not just in the org documents, but also in the converted HTML. Now creating some of these man pages was really challenging. For example, this listing of all the man pages in section one that begin with the letter A. How do you do that? It's a challenge, you know, getting all the alphabetical stuff separated. And here is the main index page for the Linux man pages sub directory. And how did I accomplish this? Well, let me show you exactly how I accomplished this. Let's navigate to this sub directory here, man-org. And this is the directory for all the org man pages. Let's go to the index page. And I have this section here search alphabetically and then I created a table with A through Z. I also included numbers because some programs will start with a numeric digit rather than a character. But say I go to the A page here. So let me click on that. How I get this alphabetical listing in the rendered HTML is I actually create a source code block here in org mode. Let me zoom in. And it's a bash script, right? The source code block is a bash script. And when this bash script executes, it prints the results in the org document and it also prints it to the rendered HTML page when I run org publish. And just quickly, this bash code here, I create an array and I call the array starts with A, right? Everything that starts with the letter A. And this array is basically going to be populated with the find command. I search in the man directory for type file for any name that starts with the letter A or capital A. It's an insensitive name search. And then I take that list of all the files that begin with the letter A and I pipe that into the sort command because I want to get an alphabetical listing. But with the sort command, because I'm dealing with some subdirectories, and it will sort it based on the full path. And I want it to sort it based strictly on the file name. So with the sort command, I actually use the dash t flag. I'm going to specify a slash as a separator, as a field separator. And I want the third column. I want you to sort by the third column, because these file names with the find command are actually going to be period slash, name of directory slash file name. And I want you to sort on the third column with the slashes, which is the file name, right? That'll be the third column. So that's how we do the sort correctly. Otherwise, the sort will be all messed up. And now that we've got our array of all the files that start with A sorted correctly, we take that and we put them in a for loop. So this for loop here for the variable X in the starts with a array, run the following command. And this command, all it does is it cleans up the file name a little more, because each of the file names are going to have .org as an extension. So we get rid of the .org extension. That's what this echo into all can decide does. And then finally, we echo this here. This creates a link in org mode. A link in org mode is created with double brackets. And you can see the first part inside the double brackets is dollar sign X. That is just the file name, the file path. Actually, that is a link. And then dollar sign name is actually what shows up as the description of the link here. Now when you're dealing with hundreds or thousands of files running some of these source code blocks in an org mode document can take some time. It can take several seconds to several minutes. So these kinds of files here, these take a while to generate. But it's one of those things, I only have to run it once, right? Unless I'm adding more man pages down the road. This is not something that I'll have to execute very often, but I'll show you this on camera. I have my cursor here on the end source line here on the source block. So let me hit Enter. And in the echo area down here, you can see it's writing to slash temp. Doing a code block evaluation, it just said code block evaluation is complete. But Emacs is still tied up because now it has to take that code, write it into the org document here. And yeah, now it's done. So this here, we're not dealing with a huge file here. Let's see how many lines, 806, so pretty good bit of results. But that took several seconds.  Don't be surprised if your computer is taken up or Emacs is taken up for a couple of minutes. And remember, Emacs is single threaded, it's not multi threaded. I can't do anything in Emacs while it's running a process like that. So all I can do is just sit there and wait for it to end if I want to actually use Emacs. So I have several pages on this side, quite a few pages that use the source code blocks to generate the output and what you guys actually see on the pages. So here's that page, we were just looking at the eight page. Now you're probably wondering how I got the individual man pages. For example, the man page for a 52 deck, whatever that program is, I'm not familiar. How did I get those man pages converted to org? Well, what I did is, let me open a terminal here, I'm gonna zoom in. Let me show you where your man pages are on your system. If you go into user share man, this is where all the man pages on the system are. Now there's a lot of language specific categories, but here are the real sections of man pages, right there. And that is what I put on the side here. If I go back to the sections, section zero P1, one P2, three, get back to the terminal, zero P1, one P2, three, et cetera. So let me CD into one of these sections. Let's CD into man one and I'll do an LS. And you'll see that these man pages are .gz, so they're compressed files. So before I can work with them, I had to uncompress them. And what I did, let me get back into Emacs, is in this project directory here, I created a directory called scripts. And I just created some simple shell scripts. For example, let me zoom in, decompress-gz.sh. This is a shell script, obviously. All it does is it creates an array using the find command once again. I created a folder called mandb for man page database. Find every file that ends in .gz and then the for loop pipes that into gzip, which decompresses that. So it's no longer a .gz file, it's in just a standard trough format, which is the man page format. So now I have about 21,000 uncompressed man pages that are still in trough format. How do I get them in org format? So for that, I used pandoc. So pandoc, for those of you not familiar with this program, pandoc allows you to do file conversions, file type conversions. For example, trough to org mode or from markdown to odt or PDF, HTML. It allows you to convert between a lot of different text formatting languages, LaTeX, for example. So the way pandoc works for the conversions I was doing is I would do pandoc-o for output and then name.org. So we're writing to a specific file name, name.org. And then dash f man, that's the format that the original document is in. And then we do dash t org, and that is what we're converting to. And then name.man or whatever the extension happens to be. That is the file that we're converting to name.org. Now obviously you don't want to run pandoc 21,000 times, right? So this is another thing that you'd probably just stick in a for loop. And let me show you some of the other scripts that I had in that scripts directory. So I had one for convert, the man pages here. So same deal here, we're creating an array using the find command and we're finding everything in the man page database slash man three. So this is everything in section three that has the name, any name. And then I've got this for loop here that basically formats the name in the correct way I want the pages to be named and then I run the pandoc command. Very similar to what I just showed you there in the terminal. Pretty simple stuff, I'm not going to go into detail. Some of the other scripts I have is I have specific scripts for each section is I didn't want to, when you're dealing with 21,000 files, I didn't want to run a script that had to convert 21,000 files. With pandoc, right? So what I did is I created a script for each section. That way I can just manage each section. So let me show you a little bit about org publish. I've talked about org publish on videos before, but let me find my config for do me max. So let me search for config doom config.org here. And then my do me max config. You can see I've got a section here labeled org publish. And I have this variable set here org dash publish dash project dash a list. So these are our org publish projects. So our org publish directories, essentially you can think of them as websites. Well, what I did is because this website was so massive, I actually split it up in the website without the man pages. So just my 50 or so pages that have nothing to do with the Linux man page section. Because that way I don't have to render 21,000 files if I just need to render stuff outside of that particular directory. And then I have each individual man section, man 0p, man 1, man 1p, etc. all the way to man 8 as their own projects. That way, again, if I'm not tying up my computer for hours at a time, I can actually split up the conversion into sections. So if I run the org publish command, which in do me max is space M capital P. And then you see I get suggestions for the next thing I can do. So I can do a for org publish all. I don't want to do that. It's going to take a long time or I can do F, which is a single file. So if I'm only making an edit to one single file in this 21,000 page project, right, that's the one I want to do. I want to go edit that one page. And then when I'm done, I'll do space M capital P, lowercase F. Now I love working with these websites written in org because they're essentially self-contained org sites, right? This whole site, I can just read as a org document as its own little org wiki because it just links to everything that's a org document, right? And then the conversion just magically translate your org wiki essentially into an HTML site, right? And it looks the same and it's really nice. It's really seamless. So the website and the org documents don't look that different.  So if I go to my GitLab page at gitlab.com slash dwt1 and I go to my repository for distro.tube right there and I scroll down, there is the index page, right? And it actually renders the tables and the links and everything. And if I clicked on one of these links, it would actually just go to that page here inside GitLab. So I just love creating websites in org mode. Like, I will never go back to being one of those WordPress users.  If you have a need for a dynamic site, you know, something that needs like a dynamically driven database, that's fine. 99% of the web though, 99% of the websites out there could just be static websites. And if you're an Emacs user and you're using org mode, it makes sense because if you're like me, I write everything in org mode, which means literally everything I've ever written, all my notes, anything on my system that's in org, I can convert it to HTML just like that. And it could be a website. So this is the project I've been working on for a couple of weeks. I've had to do a lot with this. So such a massive project, 21,000 plus pages for that big of a site, does it make sense to use org publish for that? Well, I will say that the upfront costs are massive because it's gonna take hours and hours to convert all those pages from org to HTML. Also, if you're gonna run into mistakes, right? Nobody creates a website from scratch and there's not gonna be mistakes, right? I had to do a ton with grip, said, awk to correct things because after I run the conversion I got 21,000 org documents and now 21,000 HTML documents. And then I find, you know what? The link I did for my CSS page, I accidentally put HTTPSS colon, right? Like I misspelled it. So this is not gonna render right, right? When I throw this up on the web, it's not gonna look right. So I had 21,000 pages, actually 42,000 pages because I wanted to convert both the org documents and the HTML documents back to having the right links. You know, that's where I get into things like grip, said, awk. I also had to rename a lot of file names because a lot of the man pages include colons and I can't use those in org. Org does special things with colons, especially when you have two colons in a row and a lot of man pages actually have two colons in a row as part of their file names. And for org, they can't handle that, especially if you're linking to a file that has two colons in a row in it. That's not gonna work right. That link will be broken in org. So I had to do a lot of renaming. We talked about renaming on a video just a couple of days ago. And I talked about all the tools for renaming files. I had to use a lot of those because a lot of those man page file names had to be changed. So a lot of upfront costs, many hours, but now that I've got it to the point it's at now, it's still, there's errors on the side. There are things that are still not right. But for the most part, it's right enough to where I went ahead and put it up live on the web. But don't be surprised if some of the man pages, especially you go and look at, they don't look right, because I do know that there were out of those 21,000 man pages, there were at least 50 or 60 I know that are not going to look right because they included some special formatting in the trough format that Pandoc could not handle. Like Pandoc could not convert that over to org. And really this was just kind of a proof of concept. I wanted to see could I make such a large website using org publish and I can. And it was fun because there were so many challenges.  You know, I had to do so many conversions, file name conversions, also text conversions of one of the scripts I wrote. Let me show you, because I don't think I mentioned this particular script and it's actually kind of neat because I ran into this problem here because the man pages, once I converted the 21,000 man pages, I needed to add the header, you know, the org mode header to each of those files. And you know, that was kind of crazy because you know, how am I going to accomplish that? Well, the way we accomplish that is with this for loop here, and with said, we actually insert on the very first line, you know, this line of text here.  Now what it actually does is it inserts them as the first line. So this is actually line five. This will be four, this will be three, this will be two, this will be one, which is the correct order. And these variables here in the for loop for file name and extension, this is for me getting the correct file name without the extension so that the title of the page can be man pages dash, you know, name of program, for example. So many challenges to this site. So many things I had to overcome, but it was fun. I had a blast. And I hope you guys appreciate the new website over at distro.tube. Now before I go, I need to thank a few special people. I need to thank the producers of this episode. Devin Gabe James Matt, Michael Mitchell, Paul Scott, Wes Allen, Armored Dragon, Chuck Commander, Ingrid Diokai, Dylan George lead, Lennox Ninja Maxim, Mike Erion, Alexander Peace, Archon, Fedor, Polytech, Rib prophet, Steven and Willie. These guys, they're my highest tiered patrons over on Patreon without these guys. This new distro.tube website, it wouldn't have been possible. The show is also brought to you by each and every one of these ladies and gentlemen, all these names you're seeing on the screen right now. These are all my supporters over on Patreon because I don't have any corporate sponsors. It's just me and you guys, the community, right? You like my work, want to see more videos about Lennox, free and open source software, subscribe to distro.tube over on Patreon. All right guys, peace. Them users are jealous. Nano users are probably confused.


The Duke and Duchess of Sussex are set to visit the UK next month to attend charity events. Harry and Meghan will also visit Germany's part of their trip to support several charities close to their heads, the Spokesperson set. The couple will travel to Manchester for the One Young World Summit, an event that brings together young leaders from more than 190 countries. On September 5th, they will then head to Germany for the Invictus Games 2023, one year to go event before returning to the UK for the World Child Awards on September 8th. Their visit to the United Kingdom will be the first time they have been back in the country since the Platinum Jubilee celebrations in early June. So you get notified about fresh news updates.