The next one is, most men don't want flowers. This keeps coming up in our community where women are like, hey, I wanna send this guy flowers. And this goes back to what we were talking about earlier, where I was talking about projection of things, right?  Thank you so much. But it's not like, I don't know what women experience when they receive flowers. And I was mentioning this in one of the other live streams. I was walking down the street the other day and I was listening to these two guys that were next to me. And this one guy, he was like, he's like, yeah, women, they love flowers. So you gotta buy them flowers. And the other guy was like, well, well, why do they like flowers? And he's like, I don't know. Women like flowers though, so we buy flowers for them, right? And it was like a perfect demonstration of this, right? I mean, yeah, it feels good to get gifts. It feels good to have somebody to know that somebody likes you and all that kind of stuff. And at the same time, the flower gift, whatever it means to women, I can assure you, it does not mean that to most men. For most men, they don't understand the flower thing. And it's not like they, they don't particularly want flowers. My suggestion is that instead of kind of projecting that idea of men want flowers and then buying a guy flowers, that you, if you're gonna buy a guy a gift, that you find out what it is that he actually likes, like actually talk to him, actually find out what are the things that he likes and find something in alignment with that and preferably make it something that is consumable or dies, right? Like that's one of the good things about flowers. If you buy flowers and she doesn't really like them, they die in a couple of days or whatever. And you know, for most gifts, this is what I found is that you buy consumable gifts, like things like something to drink or something to eat or something that isn't used in a little bit, that way they're not trying to find a place to put things that they don't like. And then you get all mad that he didn't like it. And he hasn't put it up on his refrigerator, whatever the situation is. And the other one is go read the Love Languages book. There's a book called The Five Love Languages and my suggestion is that you read that book because it's got a lot of really good information in there and it's a really good story. I've read it before, it's great. And the other one is watch what he does with you and this is going back to what we were talking about before where I was saying that people do to other people what they want done to them, right? And so like if he's like, you know, touching you in certain ways that's probably how he wants to be touched if he acts a certain way around you, right? Which is one of the reasons why I think you should go read the Love Languages book because it teaches you about how people express love and what kind of love they're interested in. And that's the best way to go about it in my personal opinion.


Thanks for checking out this movie review video. So this is for the 1983 film Mausoleum and at the moment when I'm recording this it is available for streaming on the shutter streaming service now I will say there will be spoilers in this since it's an older film But a lot of you may not have seen it. So if you haven't this is a definite recommendation for me It's one of those movies though. Just so you know, that's so bad It's good and I love finding those types of gems and this is a gem The 80s seems like it's that time period that just keeps on giving with these so bad It's good films because they were green lighting pretty much anything especially when it came to horror movies And I'm so thankful for that. I know a lot of other people out there are as well. So Let's get down to it Mausoleum 1983 this was directed by Michael Dugan who did other films such as Super Seal and Raging Hormones. I don't know It was written by Robert Barrick and Robert Madero who did Wrote white hot all tied up Camp Utopia and battered. That's Robert Madero not Robert Barrick He didn't write any other stuff and Catherine Rosenwink was also involved in the writing of this one I don't know why they needed so many people to write on this script because It's not like it's good. I mean, it's definitely like a terrible script There's a good story idea there, but it's not executed well at all the dialogue is terrible There's a lot of plot holes. It's just kind of like meanders, but there's a there's a good core concept It's just they decided not to flush that out properly and do like a good film They just decided to do a crappy film, but I'm not complaining. I'm all for it This film was one of the ones that actually fell victim to the whole video nasties thing in the UK So even though it came out in 83 it only actually got a release in 1998 in the UK, so that sucks for them But during that time it actually won a special jury prize at the Paris film festival of sci-fi and fantasy When it originally came out that is not in 1998 So yeah, but yeah Sorry, I was thinking about something else The opening credits of this getting right into it the opening credits are terrible They they take so long and it's just showing that graveyard in the background with the credits Just gradually like coming from the background and up and just continually like this like awful I have not seen credits like that Look that bad and honestly a lot of the film feels and looks like it's from the 70s and not the 80s I know the 83 is not super far into the 80s But there are other movies from 83 and 82 and 81 that look like they're from the 80s This one looks like it's from the 70s and this intro credit thing does not help at all with that situation The smoke in the graveyard looks unbelievably terrible on this and it looks even worse than your typical 80s effects Where it's showing like the mausoleum with like that kind of like cut out smoke effect just on the building Oh my gosh It's so terrible, but it makes me laugh and to be honest There were many times during this film that I laughed because the things were so laughable Obviously, they weren't intentionally that way, but I'm glad they were that way I actually dug the color usage of this when they go inside the mausoleum that itself looked really good They designed it well and the coloration was really cool. They had like some nice purple in there They had some nice green. I think they had some blue at one point So the color usage was really cool. It's not quite Argento Level color usage, but there were things that actually look good in this film and to that There was actually good camera work in this film There were some very inspired looking camera shots and I was surprised by that So it's not that it's a total piece of trash. There are some technical components to it that are pulled off very very well It's just you know the story of the dialogue the acting for that matter also just not so hot Why so why was there a random dude in the beginning down in the mausoleum? I don't understand that because I guess it didn't really matter though because his head ended up exploding Which I'm glad he was down there because the head explosion early on is a cool fun scene So I'm all for the fact that this dude was randomly down in that mausoleum But once again, you know, there are plot holes in this a lot of things that don't make sense And this is one of those clear things that does not make sense I guess maybe he was like a groundskeeper gardener there. I don't know but his head exploding was it looked good I put down the no med family in this one if nobody saw Immediately in this film that no med is demon spelled backwards Then you haven't seen troll too. So No, I'm joking about that, but I picked up on that immediately I'm sure a lot of people do when they watch this film It's such a overused thing where the name is something spelled backwards and No one's named no med so it makes you look at it backwards So they I think they thought they were being clever, but they're clearly not being very clever The dialogue in acting is so bad So bad, but it makes for some really fun and funny moments in this especially The guy who plays Ben the gardener for Susan and Oliver. Oh my gosh His acting so terrible so weird and creepy at the same time He might be my favorite character for that reason. Oh or Elise I think her name was Elise the the maid that they had she was really funny too Actually, I think of a lot of the acting she was one of the better actresses on the in the movie But that's not saying a whole lot because you know, there wasn't much good acting in this I Like how the reaction to the guy in the burning car in this is to just stare at the fire I mean when the car caught on fire because Susan with her green glowing eyes Which by the way the green glowing eyes look cool when she lights it up And I like I understand the guy's drunk at that point But him just like turning around and just like looking at the fire in the backseat of the car Or I think is on the trunk and then spread to the backseat of the car Which is it didn't make sense like no one would do that No one even if you're drunk you wouldn't be like oh fire There is no way Susan is so dense that she can't see Ben is a super creeper now There are moments where like Susan is Susan and then there are moments where Susan is possessed by the demon now There are plenty of moments where she's herself And she's not picking up on the fact that Ben the gardener is being a super creeper and wants to get with her And I refuse to believe that she is that dense of a person that she's not picking up on those things But then things obviously get fun when the demon aspect takes over and that demons like oh this guy's into this chick Let's lure him in and kill him and that makes for a good time But that gets to another thing which is Our demons always so horny like this demon is super horny in this and I know that's kind of like a way to like lure People but you can just kill them, you know like outright I mean the car situation shows that that could just be done I guess maybe the demons just been cooped up so long just wants to have a good time I guess that's my assumption someone put a comment down there and let me know your thoughts on it This movie has some excessively long shots and that kind of makes me feel like they need to stretch it to a certain run time So I could really do out without some of that stuff For some people maybe that adds a little bit to the charm of how bad this film is But I really would have liked if someone make a kind of a better cut of this cutting some of those longer scenes down Because it's not necessary at all like it will still be a amazingly bad film when you cut that down I love how needless the montage of Ben working is that's so funny he's very good at incessantly whacking at a stump I wrote down because He's just swinging this axe at this stump not getting barely anywhere He does it for a long time then goes off and does other things like reading and sleeping and Doing a little bit of other work, but then he goes back to the stump And he's just whacking at it again, and it's like what is he trying to accomplish? You get the idea that this gardener is just there to hang out like he's just Stretching the workout and just when they cut when Oliver and Susan come home It's like oh you didn't get that much done, and he's like oh well It just ended up taking a lot longer than I than I expected. That's just what it seems like to me The music they play when Elsie that's the maids name The music they play when Elsie freaks out is so weird and so Against trying to convey horror in a horrific moment when she goes up and sees like the green smoke Coming out of the bedroom that music it's like almost like Benny Hill type music like it doesn't match At all and it's like what were they thinking when they put this music to those scenes like it's it's baffling And it only happens at that point of the film, and I'm just like I don't get this But that goes with part of the charm of how bad this is to be honest The hypnosis freak out is a lot of fun and it reminded me a little bit of like a Nicholas Cage type freak out Not quite as good, but it you know was getting there when Susan's being hypnotized by the doctor Dr. Andrews I believe and she starts flipping out That was fun and funny, and I dig that moment. Maybe one of my favorite moments probably Ken Dr. Andrews open his eyes all the way was one of my questions The moment where he was talking to dr. Roney on the phone after he you know gleaned that Susan's a problem He's talking to her and the whole time. He's like this Like if you watch that scene and you like really pay attention like he doesn't open his eyes very far at all He's like squinting the entire time. I don't know if he was trying to read like Cards behind the camera that someone was holding up with his lines. I don't know It was weird Oliver doesn't seem concerned enough about the large amount of blood splatter on the phone That was another funny thing to me when the guy showed up to to deliver some plants for gardening And she's like oh you have the wrong place, but you should come in and call your supervisor and tell him It's the wrong place Then she kills him with her her demon green eyes, and then the blood splatters all over the phone Well when Oliver comes in he finds it and he's just like oh honey, are you okay? That was a lot of blood splatter He should have been Panicking when he saw that had been like was there a home invasion. Did she cut herself terribly is she dead? Like he's just so nonchalant. He's just like oh honey. Are you okay? Yeah, I see all this blood here crazy Showing Susan just walking around the mall Unnecessary the part where they're kind they're talking about her I understand like showing her but like they showed her a lot They kept cutting to her because it's like when Oliver and dr. Andrews are talking I think that's who yeah, it's them and they just keep showing her just walking around the mall like I like the mall scene Ultimately, and I'll talk about that in a second But just showing her continually just walking around the mall.  That doesn't make any sense they got but the guy playing that gallery dude was really funny the way he did his acting Especially when he was yelling after Susan after she stole the painting But then his death his falling death was great Loved it especially when they showed the aftermath of it with that piece of artwork through his stomach and out his back pretty awesome and That's the thing about this the practical effects are pretty solid. It's just it's just not a good movie But like I said, I love that I like how Oliver points to Susan getting the painting as a clear indicator There's something wrong with her like he uses the fact that look at the painting You got like and he thinks you bought it at that point But like he uses that as an indicator of like her taste in a painting that like there's something mentally wrong with her Like this is what I'm talking about about the writing like the writing is bad You should be pointing to something else definitely and there's a lot of just like doesn't seem believable at all Like I know it's a possession story and that's not necessarily believable in the first place But you have to create a realistic feeling within the world You're creating and a lot of what the characters do how they act what they say it does not convey that at all How are there so many bodies on the spider are so many thick spider webs on the bodies that are in that weird room in The in the nomad house that's what I understand the people she literally just killed I assume it's that same week or day even like They're totally covered in thick spider webs. That makes no sense. That's just another one of these things of like Major plot hole, but you know just charming The portion of Susan changing at the end is Unbelievably excessive That's another one of those scenes that really just needs to be cut down because it's not even like funny enjoyable at that point It's just annoying and kind of hard to look at because it's like two image over two images Overlaid like one image on top of another image and can't even fully see what's going on It kind of was really messing with my eyes and there's this really annoying noise that's being done the whole time Funny thing just side note when I see all the rats in the mausoleum I don't really think that like oh my god rats. It's so dirty or it's scary I think those things are really cute like I legitimately think rats are cute I think all rodents are cute to be honest I had mice in my house at one point and I was just like oh, they're so cute when I caught them and released them elsewhere, but That's just me but the other thing is like the rats are never doing anything menacing in this They're just hanging out and eating and just being there. So You know, they're not conveying what they wanted them to convey at least not for me And then the very end of this I wrote how the hell is been the gardener in the graveyard I guess we're to assume that he's now some sort of graveyard Attendant keeper. I don't know But that's another one of his plot whole things like how is that possible? He was just a normal dude and then he got killed There's no indicator that he's like now possessed by a demon or whatever But maybe they threw that in there to be like well, maybe he could be possessed Maybe there could be something else to this guy. We could leave that there at the end to be like a potential sequel lead-in Which to be honest, I would love to see a sequel Let's do this. Let's do this now This is actually a type of possession film I can get behind typically I don't like possession movies like at all But there are ones here and there that I'm good with and one of the one done like this Where it's so weird and it's so bad that that it's funny I could definitely get behind that type of possession film. So I'm all for it I love it. And like I said like even the the base concept of this is actually a solid concept with the idea of a Demon being passed down in the family to the firstborn female of each generation like That's cool. Like that's a good concept. It's just You know, it's a crappy movie. It's like they didn't use the concept to make a good film But I'm thankful that that's what happened So there's a main idea in this as well that's kind of been used a lot in horror and that's kind of the idea of Do you truly know the inner person that you're in a relationship with and the fears of what happens if the person you think You know, isn't that person and that's been done in horror so many so many times and it's done here And it's done super on the nose in this which you know, you expect for a film like this Yeah, I mean just wanted to point that out real quick But in the end this is one of those films that you watch it and even while you're watching it You you're texting your friends just being like look if you have shutter you have got to watch this movie This is one of those ones that kind of goes like socially viral Where you're just kind of like you just spread it to another person and then they spread it to someone else And it just keeps going and going and going and it gets like a cult status So I think we should get this going. Let's definitely get it going with mausoleum While I was watching it I texted my buddy rich and I because I know he has shutter and I was like dude You need to watch mausoleum this movie is terrible, but it's so much fun because it's so terrible I believe this is a vinegar syndrome film by the way, too It's I think it has a blue kind of recent blu-ray release on vinegar syndrome So if you want to purchase it, which I feel like it's going on my list for that I think it should be available on vinegar syndrome's website But anyway, I have to rate this twice basically because this is how I do it since it's so bad It's good. So as an actual like film film in the whole pantheon of films out of five stars. I'm gonna give it a One-star rating. It is not a good film at all even though it gets to the one because of you know the camera work actually being pretty good and the base concept but What do I give it as far as a so bad? It's good film out of five stars. I'm gonna give it a Solid three and a half stars for so bad. It's good. It's not quite a four or anything, but three and a half I definitely recommend this if you're into bad movies like this is a must in my opinion So anyway, thanks everyone for checking this out Put some comments down there about your thoughts about this will geek out about it But do me a quick favor hit that subscribe button if you like any videos I do this one or any other ones That's your best way to repay me and it's totally painless Literally takes you a second and it means a lot for my channel because I'm trying to grow And if you are gonna subscribe or you're already subscribed Make sure you hit the notification bell because that way you know when I have new videos going up or also when I'm live Streaming because we talk about some fun stuff when we live stream Always great time, but thank you everyone for checking this out and until next time keep it brutal


Right well thanks for having me today and I'm happy to demonstrate my experience with CSDMS modeling framework and and the BMI. A few years ago we got a small chunk of money to to do sort of a demonstration product of wrapping a USGS model around with the BMI and you know at the time when we started this the USGS has a lot of different models that are all basically built around some domain whether it's a watershed domain as in the example I'm going to show today or mod flow is ground water domain there's lots of surface water hydraulic models that are available but none of them had really been integrated and using a common framework and so part of the the interest in working on this project was to really just experiment with the CSDMS modeling framework and and the BMI so what we did is we started with PRMS which is a precipitation runoff modeling system it's a watershed scale model and we decided to break PRMS into four components surface component a soil component a groundwater and stream flow component basically wrapped around sort of each of these reservoirs the surface reservoir soil reservoir groundwater reservoir and stream flow with the intention of ultimately using the surface and soil components to integrate with the mod flow BMI in the future and that's been done so what I'm going to demonstrate today are our our PM PRMS components the other thing we did is we wrapped the BMI around gridbed so the main model inputs to PRMS other than constituent parameters like soil parameters and things like that the model is driven by climate weather and we use grid met which is a cone of scale set of climate forcings minimum and maximum temperature and precipitation these are delivered at four kilometer scale daily so every day this data set is updated through yesterday so we also wanted to look at driving model components with data components so I'll also give an example of that and hopefully this will follow on nicely from from Eric's whoops Eric's demo so what I'm going to show is a is a coupling of PRMS model we're going to look at sort of a small demonstration application we're going to look at a small watershed in the prairie pothole region of North Dakota PRMS is a little bit different it it isn't grid based it's based on hydrologic response units so we're going to look at this small footprint here and that small footprint is composed of 14 hydrologic response units around this main pipe stem creek here and I'm going to be showing some plots uh as a function of time of the values of each of these HRUs um in this spatial footprint so you you will see uh this footprint displayed in plots where each HRU has a different value for example the temperature in HRU 12 or the precipitation rate in HRU 12 and I'll also show some plots that show basically the the footprint of pipe stem creek and values of the stream flow on pipe stem creek um that'll become clearer later but just so when you see the plot you understand that we're looking at this watershed footprint and that watershed is delineated into 14 hydrologic response units and the pipe stem creek here I think has seven different stream segments and please don't hesitate to ask any questions along the way here I'll now increase the size of this hopefully everybody can see that well so I'm gonna I'm gonna run this interactive notebook um the first thing to note here is that we're importing these uh these modeling components from pi empty models we're gonna look at the surface soil groundwater and stream flow PRMS components um I have grid met here actually that shouldn't be here but it'll be okay um I'll explain that again later and because I want to plot our model results on these HRUs I'm gonna load a shape file of those HRUs so we can plot to them this is something outside of pi empty just so you know and then I'm gonna initialize our four components so um we've got a run directory and then for each component we have an input file and um you said I think you were asking about net cdf I mean just for example these input files do have net cdf files that they're reading um that's one thing and the other thing is the grid met data is actually delivered as a net cdf file and we're gonna extract that data from the net cdf file and feed it to the model later and I'll I'll show that more detail later so here we're gonna initialize our bmi's using the initialize method here I've just got some helper methods that that basically use those shape files and put them into a geopandas data frame so that we can use them for plotting and and that's all this is doing and also we're the model is using initially this day met data set for its climate data so I just read that net cdf file into another geodata frame and we're just plotting tmax team in and presip for a given time period on those HRUs so again here's that footprint of the watershed and each of the HRUs has a different value that's delineated by different color so I want to run this model and look at the output and to find a period of time where that output might be interesting I simply just looked at the climate data and looked at precipitation and we're going to look at model results following each of these two periods of precipitation so that the output shows something interesting and again we're just using the plymt bmi methods showing this is this is now time is a prms variable so it's returning the time the start of the model 1980 January 1st it's also showing the end time this is in days so we're going to the model is going to run for a total of 731 days now there's a lot in here this is this is basically I set up a bunch of lists of variables for each component that we're going to use to transfer data from the surface component to the soil component to the groundwater component to the stream flow component and so I just set up these sort of transfer functions and really the thing to see here is that I'm using the set and get value functions to transfer information from one model component to another so for example in transferring surface values to soil here I'm using the get and set values for each of those so it's just going to loop through those lists and get all the values for each one of those parameters and transfer them to the other model so this is really in essence the coupling of each of those four components together and then what I did is I sort of made a master update so it's calling the update method on each one of the components and doing the transfer of information from one component to another in between the updates so I won't you won't see the update method as I'm running the model you'll just see this update coupled but you understand that we're using the update method of the BMI in the background there does that make sense to people yeah sorry real quick so when you update coupled is is it important or sensitive like which of those components you run and update in which order or could you theoretically just run them kind of in any order as long as you're consistent between time steps in this case it is important the order because we're we're sort of transferring information down through the system from the surface to the soil to the groundwater and ultimately to the stream flow so yeah it in this case it does make a difference okay I'm just gonna run it for 455 days to basically get it up to the point where we want to look at a specific precipitation event again this is running that update coupled so we're running the update methods in the background there and now I'm going to run it for seven days and we'll just plot the results and take a look and I've got some helper functions to do these plots in the background here and all the code for those is available in that repo again this PRMS is slightly different from your typical model it's not grid-based so we don't have the capability of using the the plotting routines that are available immediately available in PMT but it's not a big deal so again this is just we've just moved the model ahead seven days and time and I'm just plotting T max pre-sip soil moisture the amount of moisture available in the soil reservoir the surface runoff the subsurface reservoir flow groundwater reservoir flow and segment outflow so again this is this is looking at a footprint of the pipe stem creek and it's colored according to the discharge in each one of the stream segments of this creek so you can see as pre-sip falls on the surface you get runoff and that runoff goes to the stream and increases the flow in the stream it's basically what that's showing oops I didn't mean to run that again sorry now because I ran that again I may really mess up my my order here let's see what happens okay then I'm going to run it for another period of time except this time instead of using the input files which contain that day met data which is being used to drive the climate forcing in the model I'm going to use this grid met component that I wrote and what this component does is it fetches the net cdf climate data from a thread server that net cdf climate data is grid based in order to interpolate that onto the polygons of each hru we do an area weighted mapping so this function is going to go out and in real time here fetch the net cdf data from the thread server and map that data to the hru of this model and then feed that data to the values of precipitation t max and t min so it's kind of a cool way you know there's a lot of work that goes into going out and fetching model input data and formatting it into files and and here we're we're doing that in real time by using a data component to couple to our model and that's the first time that's failed okay I'm sorry I'm going to restart this yeah the reason why that failed is because I reran that one cell with the update method and so I think what happened is our dates got out of step here the dates I have in here for a specific period of time that were matched to where we were in the model runtime okay so again here I've used this grid met data component and I'm pulling preset t max and t min out of that data component using the set value to assign the value to the model at runtime and again it does a nice job so now in this next step what I'm going to do is yeah I'm just going to override the input of precipitation and I'm going to specify a constant value of three in this case inches of precipitation over a watershed over one of the hru's which is a lot of precipitation for a day in an hru and just look at the response and really one of the things we thought when we first started working with csdms and the bmi is at a minimum it's relatively low cost to wrap individual models with the bmi and it would be a great way to sort of investigate different potential model couplings and and also um something like this was never available when I first started modeling I mean it was really hard one to run a model one time step at a time but this is also a great way just to build to develop intuition about your model so here we're just kicking our model in the butt at one hru with a bunch of precipitation and looking at the response so again I I hit this hru with a giant amount of precipitation and we can look at its response with time you know all the way to surface runoff subsurface flow groundwater reserve flow all of those are contributing to the stream flow and you can see that in the increase in stream flow as a function of time from this one event and then the amount of soil moisture decays with time as there's no more input precipitation and you can see that the groundwater reservoir actually starts to get more and more flow as you as you progress in time so that's what that looks like and then we can also view that in a more simple way just by looking at an hru and looking at each one of those functions each one of the responses of of different parameters as a function of time so soil moisture you know just decays with time surface runoff you get a bunch in the first time step and then it turns off the subsurface reservoir decays groundwater reservoir gets more flow as a function of time and then here's the stream flow responding to that one event on then finally just to shut down the model we'll use the finalize method so that's that's what I have to show does anybody have any questions I just say you know I'm an old gray haired guy the other thing to note is this was an existing Fortran model that we wrapped with the BMI so it was an older model component and we wrapped it with the BMI which made it available as a python component and that is totally cool and I really have to say that that working on this project was one of the funnest things I've done in my my career and if you guys are model developers or model users especially if you're model developers I'd really consider using the BMI as a template which to build your model from the ground up I think it will help you in the long run to a great extent so


4 Common Opioid Myths 1. The recent increase in heroin use in the U.S. is a result of increased restriction on prescribing opioid painkillers. Myth. Research has found that the increased use of heroin in the U.S. had begun before the newer restrictions on prescribing opioid painkillers were instituted. 2. Because they are sedating, opioids are useful to manage sleep problems that are often associated with chronic pain. Myth. Although opioids are sedating, they can disrupt normal sleep architecture and exacerbate rather than alleviate sleep problems. 3. Because of its long half-life, methadone only needs to be administered once per day to achieve its optimal painkilling effect. Myth. Methadone only needs to be administered once per day when used for the treatment of opioid addiction. However, its painkilling effect only lasts from 6 to 8 hours. 4. Very few patients prescribed opioid painkillers for legitimate pain complaints end up misusing or becoming addicted to them. Myth. Between 21% and 29% of patients with chronic pain end up misusing the medications and between 8% and 12% become addicted to them. If you have any questions or would like to speak with our nurse, please contact the Professional Supplement Center and one of our knowledgeable staff members will be happy to assist you.


The study examined three forms of molybdenum disulfide, MOS2, 1T, 2H, and 1T-MOS2 for their ability to produce hydrogen from water under visible light irradiation. The 1T form of MOS2 was found to be more efficient than its counterparts, generating up to 75 millimoles of hydrogen per gram of material per hour with a turnover rate of 15-19 hours. This is attributed to the lower work function of 1T-MOS2 compared to other forms of MOS2, which makes it easier to transfer electrons from the material to generate hydrogen. This article was authored by Utham Gupta, B.S. Naidu, Ramamala Maitra, and others.


An observance of Donate Life Month, Piefill Medical Center, held a moment of silence at approximately 10.08 a.m. Monday, as eight is the number of individuals one organ donor could save. There are a lot of people who are eligible for donation, but unfortunately do not become donors because they are not registered. So that is why we encourage everyone to register and provide hope to those who are waiting and if and when that time occurs within a hospital setting then they can become an organ donor if it's applicable at the time. As with many individuals looking to become a donor, some believe that being a donor lessens their chance of receiving health care. Community and Partnership Services liaison Lauren Salyer says donors not receiving health care is false. So many times people feel that they will not be saved whenever they come into a hospital if they are a registered organ donor and that is the complete opposite. Doctors and nurses and medical professionals are here to help save your life. They are here to help preserve your life. That's what they took an oath for and that is key. If and only when your time of passing occurs is when you are able to save life, the organ and tissue donation. According to Salyer, organ donors can give families a second chance at life. donor recipient Barry E. Step receiving an organ was a difference between life and death. Just had some kind of a rarer liver disease that my liver just started shutting down on me and was causing a lot of issues, forest breathing, just overall completely had my whole health messed up and then when he come down to pinpointing the problem found out it was I had a real rare liver disease. So to survive I had to have a liver transplant. We are Pikeville Medical Center and we are an amazing place to work, health care heroes of all types work here, all who deserve great rewards. So while our heroes are working hard to take care of our patients and visitors, we are taking care of them with top tier benefits, higher pay rates and great sign on bonuses. So join our team today. So what are you waiting for? Apply today. Incredible opportunities await at PMCjobs.org. After receiving his liver diagnosis, E. Step was told that he only had 24 months to live. 23 months in, an organ donor saved his life. In return, he became a donor as well.  After receiving a new liver, E. Step and his wife Lisa expressed great gratitude towards the family of the donor. We wanted the family to know a little bit about Barry and our family, about him being a minor, a grandfather, how we love the Lord and we're brought here and we were very blessed that we knew that they were going through a terrible time but we would continue to pray for them but also to let them know that the life is moving on with us. To become a donor, you can visit your local DMV or visit donatelife.net. For Mountain Top News, I'm Joel Hodgell.


Thank you for joining us here this afternoon. I am SVJ Lakshmi, standing here today to talk to you about a project that is comparison of behavioral patterns based on gender, education, age and location. As the saying goes, talent wins games but teamwork and intelligence wins championships. So let me introduce my team members. She is Tanusha, Reshma and Sumanj. Let's walk into the content overview. Okay, we'll see the objective. The famous philanthropist Warren Buffett has his great investment rule. That is, if he understands business, he'll invest on that. If he doesn't understand, he doesn't touch it. So one should understand when, where and how to modulate his business apart from starting or setting it up. So considering a massive application such as MOOC where millions of learners undertake a course, there isn't essentially a case that all the users or learners take the course in the same pace. So this is the reason why the MOOC instructors or the educational data mining technologies are interested to compare the behavioral patterns of different categories of participants. So our objective in our project is to enhance the insights of IIT Bombay X by analyzing the course activity based on gender, education, age and location. Moving on to the introduction to Open edX and IIT Bombay X. For time being as you've all heard of what Open edX and IIT Bombay X, we are skipping the slide. The technology is used, the demonstration of the project. Apache, Hadoop, Hive, MySQL, Lugi. So we are showing this demo in the development version. We couldn't completely deploy this in the production version because of some issues with the VM. We'll see the architecture of the IIT Bombay X, which is told by Somansh. Right now, we don't have the image up, but basically, IIT Bombay Analyze Architecture is composed of three main components. The first is LMS and then it's pipeline and then applications. So LMS stands for learning management system. So basically a platform where the learners can view courses. It can also be used by the course team members. So LMS is a learning management system and that's where the learners can view the course and the course team members can use student enrollment and they can look at maybe discussion forums. And basically, every time a learner interacts with LMS by let's say watching a video, enrolling for a course or attempting a quiz, each of these actions generate an event and this is stored in a log file. Now, this log file tracks events for every user every single day. So obviously the size is massive and you cannot store them in a normal file system. So you store them in something called a Hadoop distributed file system and normally it's stored on a cloud, but for our purpose we store in a local HDFS and all the data in this is now processed using Hadoop's map reduce program and the results of this map reduce program is stored in a relational database such as MySQL. Now that the data is in the database, we now have to get it to the dashboard and dashboard is the part is the UI part. So that's where the instructors can see all the insights. Now to get the data from the database to the dashboard, we use a data API which is based on Django REST framework and we'll explain each of these components later. So let's start with the pipeline. Let's have a demo first so then you'll understand what's happening and then look at each component. Coming to the IIT Bombay X analytics pipeline, let us first tell me about installation. Open edX has provided as a single script for installing analytics locally, but we do face some problems while installing. We have fixed the script and completed the installation accordingly. We have implemented four tasks as mentioned now and I'll be going into detail in the further slides. Let us see the architecture of IIT Bombay X analytics pipeline. The entire data generated by the IIT Bombay X platform is stored in these data stores, which is shown on the left side. This data present in the data stores is copied into the Hadoop cluster along with the tracking log files. These tracking log files contain the events that are generated by the learners when they interact with the LMS. So basically every click of the learner on the LMS is considered as an event. Now when once the data is available in the Hadoop cluster, we process the data by using MapReduce program and the resultant required data is stored into the hype. When once we get the data into the hype, then we import the data into the MySQL database, which will be further used by data API in order to send the data to the dashboard to display the results. Logic behind the tasks which we have written uses Luigi, which is a workflow management system that is used to run complex pipelines for batch processes. Now coming to the tasks we have implemented, initially IIT Bombay X has a course activity task which gives us a total number of learners for each category of activity for each week. Now what is this activity? Basically depending upon the events that the learner generates while interacting with the LMS, we have categorized the activity into five types. They are active, attempted problem, played videos, posted forum and resource usage. Now the course activity which is initially present gives us the total number of learners based on this category of activities. Now we have broken down this course activity into four different tasks. The first task is gender which gives us a total number of learners based on the gender and we have categorized gender into male, female, others and unknown. When once this task is run, we get a MySQL database as described. The next task is course activity education level which gives us the learner's count for each category of the activity for each week based on the education level. Now we have took some education levels such as masters, bachelors, doctorates, etc. in order to categorize the learners. Similarly, the third activity is birth year where we categorize the learners based on the birth year. When we run this task, the MySQL table as shown will be created. The fourth task is location where we get the total number of learners based on the location where they belong, the city. So in order to achieve this, we need to initially run the task which gains the country, country code and city by using a Python module known as PyGIP to which we give the IP address of the learners which we get from the tracking log files and once when we give the IP address, it gives us the corresponding country, country code and location. So when the data we get from the initial task into the HTFS, now we run this course activity location to get the final results. Now the further explanation will be done by so much. After these Luigi tasks are completed as you have described, it's all stored in the MySQL database and now from MySQL database to the dashboard, we do it to a data API which is based on Django REST framework. So somebody already mentioned, I'll skip that part. I'll show you the work that we have done. So these are six APIs that we have written. The four main ones are gender, education, age and country. We also have two helper APIs to list all the countries and all the locations for each country. So let me show an example. So this is an example API. This is our age API. Basically it gives a age of a user in four buckets, which is above 40, between 25 to 40 and less than 25. And in case we don't know the age, the classifier is unknown. Now by default, this API returns the usage for the last week, the most recent week, but we can provide specific parameters that start and end date if you want a custom API response. Now the result of this API is sent to a dashboard, which will be explained in the description. Dashboard. Open edX insights makes the information about the courses, what the dashboard consists of. The dashboard consists of enrollment, engagement and performance. Enrollment consists of activity, demographics and geography. Engagement consists of content and videos. Our task was to segregate the content into gender, age, education and location to view the behavioral patterns based on the activities like playing a video, being active, attempting a problem, participated in the discussion forums and resource usage. The changes we incorporated in the dashboard. Originally the engagement content had only the summary view of the activities and now the content is broken down into gender, age, education and location along with the summary. These are called the tertiary navigation items under the secondary navigation item content. For each of the tertiary navigation item, there are five quaternary navigation items are there.  Behind the scene. The whole idea behind the scene is to render the data into a template, the form which is visible to the user viewing the page. But where do we get the data from? As mentioned by the so much about the data API, a call to data API is made along with the required parameters. But the dashboard cannot directly extract the data from the data API. The data API client acts as the interface between the data API and the dashboard. The purpose of the data API client is to transfer the data from back end to front end and it supports calling APIs. The analytics client fetches the data from the data API and returns the data in the form of JSON. And this data is further processed for displaying the weekly student metrics which shows the required strengths in a graphical representation. This is the graphical representation and the second metric is the student activity metrics which shows the recent week information. And the third metric is the content engagement breakdown which shows the required strengths in a table of form. By these, the MOOC instructor and education data mining technologies can compare the behavioral patterns of different categories of participants future work in pipeline. The current geo location supports only country and location. We can obtain the state of the learner by using a IP address, by using a databases available on the internet. Then a new field is added to the course activity location table in the dashboard. The extension of the pipeline can be updated in the dashboard graph. Now we are using a graphical representation to view the behavioral patterns. Instead of that, a geographical heat map can be used. And also machine learning techniques also can be used to achieve more meaningful conclusions. Thank you. We'll quickly see the demo of a project by passing the authentication since this is the developer version. This is one of the courses available. Our task is to segregate the content. This is the education in which you can see the labels like the bachelor's, master's and all. For all of these activities like active students played video posted forum, the values are shown. As you can see the number is huge for masters. It is the same for age and gender. The location is a little bit different since we have to select three locations and the comparison between the three locations can be seen from the graph. Selecting three locations from a country Tanzania. You can see the number of active students in a particular location, the week wise trends, the recent week summary and the content engagement breakdown. The rest are the same. The spoilers for age and gender. Thank you. Okay, that is some actually good work but you are not you're not displaying what is important. So that's a problem. So there's some good work which is there but there is one question here. So your demo has got everything but your slides have nothing. That's what I'm trying to tell you. Basically, we thought of starting with the demo. So once you have an idea of what's happening then you can look at each component one by one. So why you have the same tertiary level nomenclature for each of those secondary level So talk about the labels, right? The activity. Yeah, labels. Yeah, so that's a form of filter. So you want to look at a particular activity. So if I'm getting in this, if I'm getting by just visiting education, the same thing, do I get the same thing? No, no, no. So suppose you visit education and then what is the tertiary level? Usage, resource usage. And then I visit gender and then I go to resource usage. Is it the same? Okay, so as an example, let's say 500 students played a video. So if you open gender, it may say 200 males, 150 females and unknown. But under education, the same 500 will now be segregated into maybe 10 categories according to education level. So that is true across. Yeah, so basically the same 500 total is the same.  So it gives you more insight of the type of students that you have. Yeah, but I think it is too complicated. So maybe you could have figured out displaying by some other method. Okay, we can take this off. So these these labels are same for each category, that is location, age, gender, whatever you're taking, that is the upper level category, then lower levels are you're segregating depending on what are the activities they're doing. So for like if you take video activity, then for different locations, how the video is accessed, that's what the graph is showing on the location, I can understand because you're filtering it out. Other things that are no filters.  As location is filtered, like that male is filtered. Education is also filtered. Yeah, everything is filtered. No, can I see you get the total amount, what do you say? Can I see your not there? Maybe on the laptop or something. Okay, thanks.