One of the biggest challenges of circular economy of textiles is the growing amounts of used textiles that end up as a waste, either on landfills or incinerators. And this is the case also with the Baltic region. So this project was born to advance the field with documented data on the post-consumer textile waste flows and to better understand what are the current practices and challenges of textile reuse and recycling in the Baltic region. The project also brought together stakeholders in Estonia, Latvia and Lithuania on the topic and kick-started a dialogue across the sector within the region and with Nordic countries. Since the Baltic region is a big importer of Nordic used textiles, it was very logical to develop this project together with Nordic expertise. The collection system of used clothes and textiles in Estonia is relatively well organized comparing to other Baltic countries. In fact, our collection numbers are more close to the rates in the Nordic countries. But still, around half of collected items are treated as wastes. And therefore it is crucial that we start investing and developing new recycling technologies. And we should do it together with other Baltic states and also make use of the knowledge and experience from the Nordic countries. So what we learned during the research process is that Latvia has the least separate collection of textiles out of the three Baltic states. Obviously that's a problem, but there's also a big potential by remaking and redesigning clothes, by using the second hand clothes as material. As a next step, there are plans to have this system for separate collection of textiles in place in Latvia as soon as 2022, which is sooner than the EU requirement. And that is thanks to one local waste management company that has done a pilot project on this and is now starting to move forward to put the system in place. What makes Lithuania stand out from the Baltic countries is the fact that really large amounts of second hand textiles are imported and sorted on this spot. And today Lithuania is country number one in Europe, regarding imports of used textile per capita. Today, our municipalities, regional waste management centers, public and private companies are actively starting the development of used textile collection and various reuse schemes, at the same time facing really big challenges of rapidly growing amounts of textile waste. Having strong need to have more flexibility in legal environment for the reuse sector, and also looking for recycling solutions. For these reasons, having in mind a great potential of possible cooperation with other Baltic countries, Lithuania's role for the circular economy in that European level could reasonably be to build a textile recycling plant. We are in the beginning of the journey to transition towards circular economy of textiles and a lot of work is ahead of us, which requires strong political interests, new business models and technologies, consumer engagement and interest and of course collaboration within the sector across the region and with the neighboring countries and regions. There are great opportunities, strategic Nordic Baltic collaboration in building bridge with Nordic technology advancements and innovations within textile circularity and the Baltic region's capacity in sorting, production capacity and the strong culture reuse and repair. We hope that this research started a process and provides inspiration and knowledge for further developments in the textile sector. And we are very grateful the process and the project called funding from Nordic Council of Ministers has been funding similar studies and projects previously in the Nordic countries.


Hello everyone. My name is Miha Macevsky and today I have the great pleasure to present to you my token titled when models query models Let me start with expressing my gratitude to organisers and allowing me to participate in remodeling to Europe. I wish I could join you, but some Personal issues block me from that And this is where carried out at ETA Zurich together with my Supervisor Yasmin Smayich, Bernhard Aufmann and Douglas Martins from Palscher Institute and Giorgio Vallone from Lawrence Berkeley National Laboratory. I will start by Mentioning actually nice coincidence because today is almost 10th anniversary of the exposed discovery at CERN It was possible by a great effort of engineers and scientists who Built an operated large rock ladder along with four detectors here. We can see Image of collision of beams of particles taking place in one of the detectors and by reconstructing that collision and matching to Physical models scientists could identify as this blip here exposed on Being created and that proved a theory created 50 years ago. So that's quite incredible And that's a big step for for particle physics, but also our understanding of matter and Universe as a whole Now, how does it work? Let me start with just a very brief accelerator principle And to me it's like a swing on the kids playground. So we have A charged particle which is kept in circular trajectory by a dipole magnet. So just to North and south poles put on top of each other that for a positively charged particle traveling perpendicular to that field would Experience a force that would bend it so we can see as Particle goes out of the screen to stir it into the middle of the circuit Circle and then turning at some point. There is Radio frequency cavity that eats electric kick That accelerates particle and goes round and round in the circle And there is just this one equation Lawrence Ford that you may remember from high school physics that is governing the movement of particles with a good approximation And what's really interesting here is that these magnets are actually super powerful So they operate at a 3 tesla just to compare an MRI magnet would run at 1.5 tesla And they need to be cooled down to very low temperatures like 1.9 Kelvin, which is even less than the outer space. That's quite impressive And yeah, we need quite big circle 27 kilometers in conference because the larger in the circle circle And the field then we have the more powerful collisions and the more powerful collisions that were more we can learn about behavior of particles and with superconducting magnets which is the objective of My project design of those magnets We can reach a compact design by fields that Allow for building better accelerators And it's actually not only Larger or not wider that's one to rule them all but actually there is an entire complex of accelerators Which provides particles and pre accelerated before going to the next stage and add different experiments at CERN But what's really striking here? That's for instance, protosynchrotron was built in 1959 and is operated until today So this shows that the design is really important part and have to be done right and to maintain knowledge about the systems and Information that is relevant to keep it operating for a long time after it was put into operation So the motivation for my project, which is the design of superconducting magnets Protractor accelerator comes from the fact that these are multi-stage static processes that involve various disciplines and they feature changing terms of experts and software tools That are on their own subject to have this in recruitment placement And may last as you can see from years to several decades. So we are aiming at consistent sustainable and reproducible organization of numerical models to cons together with construction valuation data And tools using the process and as you can see here circle of large amount collider The future circular collider would be about four times bigger than LHC today, so and that's the design and engineering effort taking place right now and i'm contributing to that And uh inspiration for this project Which is called pi nbsc so pi to the implementation of certain nbsc concepts where nbsc stands for model-based system engineering formalize application of modeling to supports and requirements design analysis verification and validation activities that start in the conceptual design phase and continue throughout the long and later life cycle phases And one of the concepts brought by nbsc is Design system matrix. So we try to decompose a bigger system into subsystems like we decompose our software solutions into Modules and interfaces between them. Here is some pretty similar Where this matrix shows the connection and coupling between systems And also the definition of interfaces so what data goes towards system as they are put together And if we look into one box, which is the super productive magnets We can see that this is composed on it owned by several sub models that also have certain dependencies And exchange information between them and when we design the magnet we want to put together these models, but we don't want to Deflicate information, of course, it's not a good practice involving software in modeling So instead we want to have specialized models that are good on its own And instead we want to provide query mechanisms such that these models can access data between each other and that's what nbsc framework is all about And it's especially important that we have many many models that are on different scales So it would be a certain composed of many magnets it can be a magnet itself or a cable that is Used to create that magnet or even a strand of that cable. So that happens at different scales and we do somehow Have first of all dependency tree of these models and the query mechanism to put them together and what we do is Reliance model with system engineering and that's actually a concept that is First of all introducing a quite generic concept of a model which is a simplified version of some It can be a graphical mathematical machine learning deep learning or even physical representation like measurements That's abstract in reality to eliminate some complexity such that we can focus on one particular aspect of system and its design and with nbsc we shift system engineering From documents to interconnected models So that models are query they generate news and are traceable and repeatable and if you look at typical project management pipeline we have initialization then study that finishes With conceptual design reports or report telling what are the suitable solutions if you want to realize that project Then you move to design of particular solutions which ends with technical design report And then we build it some documentation commission and finalize the project and there is always procedures and report and actually what's quite common in This community, but I would say when science in general is that when we write in the report We have some models some measurements some excellent spreadsheets some analysis scripts and That all is put together in the report but typically This link is only Available for the creator of the document and once the document is created country Trains back where this data comes from. So if we have to reanalyze some of this information might be missing and we need to bring it back and recreate which sometimes isn't even impossible when People leave software changes and we can already find the particular setup that was used to create that information So instead to this Static documents we proposed to introduce models And with these models be able to always retrieve information trace it back and and then put it together and that's exactly the Python mbsc primer well about and I will talk about its microservice architecture and here I'd like to really um Note the similarity between system and software architecture. So as you could see a system architecture is represented as subsystems along interfaces between them and Actually was pretty obvious of software a software architecture in our case. It's microservices and interfaces between them So there is this similarity and in five we tried to leverage practices from software development and use them in system engineering to improve the design processes So the framework itself is composed of several components So from user perspective, there is configuration that tells what models are involved in a particular design This forms a model dependency graph This graph has to be a directed cyclic graph So that there are no loops and we can always execute it from start to end and as we execute these models they are Typically living in some notebooks or scripts. So When we run for instance magnetic analysis, this would perform a model query Find its dependent models execute them and get that information back And when the model is executed to be in a notebook or a script, this is calling an electromagnetic solver to solve for particular physical quantity that we're interested in And as you can imagine, we might have some redundant calls if two models depend on one And if the input information the same we can reuse that immediately by accessing a cache database. So all the execution of models is cache. We take certain snapshots such that we can reuse that information and also after a study of some analytics like what's the fastest model was the most which gave us the biggest margins this is still available And we Choose notebooks because after execution of each of the nodule we can create an html report and then build a book from that html report such that we form and document a bigger report So what are the three pillars based on this? Initial overview of the project. So first of all containers for numerical models And in general for reproducible environments. So whatever we use we put it into our container and expose and generate interface Once we have that so that is how to use particular solvers We have a model query mechanism that has two components one is dependency tree, which indicates What is dependency between different models and How a change would propagate across this model tree and the cache database so that when a cache is available We just return that information. Otherwise, we just Need to run the model again and the third pin are our model views. So auto-generated documents where We can profit from notebooks and build on-demand And representation of our design Such that it's also available for decision makers for managers in a convenient form. They don't run any code They have a view and it's actually a quite cheap way of generating the view And with that we also keep track of some information for reproducibility like versions of the particular Packages that we used version of the container we use version of software in general so that we can always redo that analysis later so Starting with containers for numerical solvers. So we have a solver which Is solving a particular physical problem magnetic mechanical thermal We then encapsulate into the container so that we have its all dependencies and running environment And then we provide a generic REST API to interface with that solver That has four methods Initialize upload files around these files and download results And we already created some co-edit containers Some are available provided by other companies Once we have that Numerical solver API we can enable model query. So how to get Information between different models and for that we have this pym bsc class which is building an execution query Based on the config source model target model some inputs and we can either get reports or some figures of merit Or artifacts if these are larger files And as I mentioned already in case a query is executed again with the same inputs And the underlying model will change and it's not only the model but also dependencies. We return output from the cache database The cache database is a document store a dictionary A document store Which is implemented in mobile db. So we have here a schema with name of a model its path Execution time last modification timestamp Hush of its content and contents of all dependent models input parameters and output figures of merit or artifacts that we may want to immediately return once We executed the model So, um, we chose model db because we may we have freedom for the dictionary fields that we don't know a priori and could have a different structure and that was quite convenient convenient choice and We have index that is based on model hush, which brings a high cardinality And that's actually the only table that we that we need to store in our cache So we don't need to really a relational database here And one important thing to note Once we have our model dependency tree We realize that for instance a mechanical model depends on geometry, but also depends on magnetic Which also depends on geometry so if We want to then find the shortest path of execution of dependency we need to perform three linearization And which actually is inspired by the method resolution order of python So Here once we have a model that we want to execute We need to check its state if it changed we respect what's in cache but also whether any of the dependencies changed and This we do by just going through the shortest Path of this tree and we don't need to waste time And again, if we have a cache hit we return what we had but if One of the dependencies or the model itself changed we need to rerun it such that We have Current result But with that Tree a realization. We only rerun those models that changed. So that's a big gain also in computation And one important step is changing propagation. So what this? Dependency three and three rely Linearization allow or is that in for instance one will change? Let's say electric thermal model And you want to rerun particle accelerator again. You would check if it's Content and input fines and parameters changed And if not we change check all the dependencies And Here we see that only Something in the magnet change we go into the magnet we check dependencies of the magnet That model change would only rerun this one while the others return The cached results are that we can then put back together The entire model and run particle accelerator Study only on change of one particular Model and update only those that that change And one thing that also brings to the third pillar, which is model use once we reform a model re-execution Document a report is auto generated and we can see it here. I'd like to Open now the Link so if we click here we have A CDR example so conceptual design report Of magnet design, so we have some introduction and geometry with code so that we can see what was Used with versions of API and time of execution a table of parameters And we've thought we can still have interactive view of model results So that's that's pretty convenient. We can zoom we can look at what we got And the same is also for some model results where We have Information about geometry again Some input files that we can print out. So it's all available And again some physical results in this case magnetic field Which we can Still read and check that information. So that's quite convenient for Everyone on the team, but also people from other groups from other Systems that they could quickly check was for instance the big field or stored energy And that could inform their design and this information Is cross-reprehensible and people can quickly access okay So just to summarize this part so We have this pi mbsc microservice architecture First step is that we have containers for numerical solvers And we also allow for command line interface or or for rest api jrpc calls But for those tools that we provide We package them Docker We presented this numerical solver calls with more Endpoints in rest api And then there is this pi mbsc query calls that allows models to exchange information and get data from each other And this all goes to a pi mbsc cache that stores information on model execution so that we can on one hand Retrieve it quickly if we run the model again with the same parameters But also we can do some analytics afterwards and then check our models see how they change and And track that information Then we support two execution modes. So One is local execution when designers play with notebooks and do some analysis make plots and then get data in the right shape that is biogenbitter server and python with some virtual environment and On local machine it relies on Docker and MongoDB instance It produces a notebook output Which then we can put together into a book and report that people can communicate outside But that's one way. The other is distributed execution. Of course, we can imagine that Once we have certain design and we want to change parameter. We don't do it manually We can do on-demand compute And here we just in a way abuse github ci but By making it running with its rest up on-demand of certain parameters and For that we use paid-per-meal to execute notebook programmatically And for that we rely either on github runner or open-ship instances to run these Docker containers and allow for The computation to be done on on the cloud Yeah, some implementation details. So as I mentioned, MongoDB for cache database Docker is rock-wrapped locally open-ship for distributed execution fast API for REST API development. That's really fast development Petri for the virtual environment and dependencies pay-per-meal and scrapbook for notebook execution And we create these books with jupyter book and eventually github for versioning ncsd pipelines Which actually is quite neat with poet-resokir sample pipeline that we that we use for our packages And now I like to come to one application to show how we use that tool in practice. So here is one example of optimization where the objective is to obtain certain fit quality so that particles are really focused and traveling in the desired trajectory this accelerator Of course, we need certain safety margin. We don't want to degrade the material too much as well as its installation And this is the taking place by optimizing a cross-section of that magnet where we put certain cables here around And the xy plane and we adjust the positioning angle inclination in the number of conductors And for this optimization, we have four models geometry electromagnetic mechanical thermal that run in the loop Until we find with a genetic optimizer a set of parameters that minimize all the objectives And the optimization execution is actually quite simple So we execute models of that by nbsc app So we need one line per model to retrieve figures of merit Then they are returned as dictionaries. So put them together Collect also some artifacts that we may use for further processing And we calculate scores one value that represents the design And we then take the figures of merits scores and artifacts and return it as as a result Once we have it We can run and the run is Very similar to what we see so far. So we have Different solvers for different models. They have this model api calls The optimization node will be performing by nbsc query poles to each of the models Combine them into one Computes score and that's for is then stored in the cache And database so that after an optimization run we can retrieve it from Simulation of a cockpit of Of the optimizer which is Alexei notebook and that's that's the cockpit where we can see the progress of optimization If we click any dot we can see a cross section of the magnet that was Used for this optimization and was the best individual in this Genetic optimizer we can see some parameters for that Model and we can also see how the design variables compared to the best in Individual so far And this is the last two information. First of all, if we are hitting the limits and we maybe we should expand the design space In that variable or we are somewhere in between and and we are still exploring the interspace So putting it all together with pimea and bse we could provide query mechanism for models so the physical connections physical interfaces that exist in a particular system are represented in the design phase When we use computer aided design with queries And that is a very clear interface between these tools so different components of accelerator and query each other with that tool and also within one system different models can query one another and We know that that particular accelerator is a system of systems implemented as multiple project remote queries for data exchange and one system Like a sprockets among the system of components that are implemented in a single project with local queries for data exchange And one important part in a design is its versioning so Here we rely on idlam, which is a standard way of keeping track of information Where we can have reference of our main branch of the design but also certain sub branches for particular versions of a design which still can be updated And we can keep track of that or put some ties to keep information about main main changes main Main versions of our our design And for each of these dots we can run a continuous integration pipeline and at the end produce this report so that every change We can keep track of what was done and maintain also that focus and artifact in githlabs so that Anyone can access it rather quickly Okay, so to conclude the pine bsc and bsc framework, which is a python implementation of model-based system engineering concepts Um It's quite generic. It's not only force for protecting magnets, but can be used in other engineering fields It is a set of containers with numerical models a model for a mechanism of a cache database And a model view based on jupyter notebooks and jupyter book for documentation And on top of that we added a set of optimization algorithms interactive cockpit for multi objective multimodal optimization And one important thing is that we rely on standard open source software technology stack And really pay attention to testing and documenting So that this solution would last For years as as as needed. So thank you very much for your attention. It was a great pleasure to provide delivered stock If you have any questions, I would be very happy to answer Um We have a few minutes for questions Would be to ask you if you could expand a little bit on the motivation for this project I'm curious, you know, how expensive these model api calls were to to justify this caching caching approach and secondly why developer choose pi mbse and Was there no other package available for example? uh-huh And so on the first point. Yes. So some models may take a few hours to run um for most advanced if you look at the party or on the big accelerator study this can be a few days and Sometimes the system did not change. So in this case we would just rerun something that you know the output for So, um, here is a big game and as for Having already Package library for that. We of course did a search and tried to see what's out there and we did not find A tool that would exactly match our our requirements. There is a tool and developing java but that would require us to then go via pi for j and and A bit complicated our our stack Plus did not support natively notebooks and then that was our our one of our requirements to rely on notebooks Okay, thanks. We have a one more question in the room Uh, thank you for your talk. It's really nice to see how this works in action So the examples we've seen have um a very strict order in which the models are run Are there more exotic examples where you iterate over two models that feed into each other and you try to get them to converge Or you have multiple versions of a model side by side Uh-huh. Yeah Thank you that was a good question So When two models require one This is called post-imulation so We indeed run one and and the other and to resolve that We would have a model which is post-imulation calling to internally So that way we we can run the To and to respond when we resolve So you encapsulate them in another model Exactly, right Yeah, and run until conversion Thank you Yeah Okay, so it looks like we have no more questions. So once again, thank you michael for your very interesting talk


Welcome to this soft pastel painting tutorial. I'm calling this painting Tangled in Pink. And in this lesson I'll be sharing my three-value underpainting method that works great and it's really easy. I'll be creating an alcohol wash on some sanded pastel paper. I think you're gonna learn a lot and have a lot of fun. And in case you didn't know, this is Monet Café and I'm artist Susan Jenkins. And I would really appreciate it if you would go ahead and like this video. Also leave me a comment. I love to hear from you. And subscribe to my channel and hit that little bell icon to be notified of future tutorials. I would also love it if you would consider becoming a patron of mine on my Patreon page. This is a place where you can get extra content for many of my lessons plus you support this channel to keep the free lessons coming. And a shout out to one of my patrons right now on my Patreon page Cindy Sanford. She shares such lovely photographs in our group and she's becoming quite the outstanding artist herself. Thank you so much Cindy for this photo. Now let's talk about the products. I think you'll be happy to know I'm once again using the Paul Rubens set of soft pastels. I love these pastels because they are affordable but a great quality as well. I would say they're very similar to Sennelier pastels and the vibrancy, the softness, the color application. And I often do something I call a color test when I'm checking pastels to see how much color to binder ratio there is. And if you get a lot of color on your finger when you do this, you know you've got a really good quality soft pastel. So I'm using also that was the 36 set. I'm also using some of the colors in the 40 set. Each of these sets is under $50. You can get them on Amazon. I'll have the link to both of these sets in the description of this video along with all of the other products. I love this 40 set. It has so many nice earthy warm tones in it. So you can really get started as a beginner for relatively inexpensively by using these two sets. The surface I'll be using is a sanded professional sanded pastel paper. And yes, I do mean sanded. It feels like sandpaper. That's what gives you a lot of layering ability. I love this Luxe archival paper. It takes water and other liquid mediums so well it stays nice and flat. And it is a little bit more expensive. If you're getting started, I do have many alternatives, even making your own do it yourself pastel papers. I have a video on eight ways to do that.   You could also use water. Alcohol just dries faster. Now I'm going to show you three values that I'm choosing. My main color is going to be a teal color and I'm picking three different degrees of lightness to darkness, a light, a medium and a dark. And I'm going to use these three values to create my under painting for a nice cool beginning. And I'm using a piece of vine charcoal just to get in my sketch. The great thing is the sketch is very simple. I'm really just getting in the horizon line, some of the tree shapes and that's just about it. And now I'm going to get started with my three values. I'm using my lightest value in the sky. And notice I'm turning my pastel on the side using broad strokes. Now I do add a little bit of a lavender color. I mean, you could totally just do this with just the three values. But I thought I'd go ahead and pop in a little bit of this lavender color to kind of neutralize that sky a little bit. My next value is going to be my dark value. This is a nice dark teal that's in the Paul Rubens 40 set. Now I'm sanding it off a bit. Sometimes certain pastels will have a little edge to them where you can't get an even application. So I sanded it off a bit. And now I'm just blocking in these tree shapes. Once again, laying the pastel on its side and just giving some kind of direction to how the trees would be growing. And you don't have to press really hard with this just enough to get enough of the color down. And now I'm getting my middle value, which I'm using to actually scumble on top of some of the trees that were darker because some of the tops of them were a little bit lighter. You could totally just put the dark down first if you wanted and then go back later and layer the lighter values. So now I'm using the middle value again to get in the field. And a really simple way to think about it is that the three values are going to be the lightest value is the sky. The middle value is the flat parts of the earth or the field. And the darkest value is going to be vertical elements such as trees. Darker values are also things that are in the foreground. You'll see me at that dark again. But right now I'm getting in directional strokes with the middle value. And I know I'm going to be wetting this, but I still like to get my my coverage in a directional way. I'm adding more of that dark to see in the reference image how there's some dark, darks down in those deep grasses and just kind of scumbling that in with some of the middle value. So there's my three values again with a little bit of lavender in the sky. And I am adding alcohol with a brush. You can use whatever brush you have. I like to use a brush that's a little bit wider or bigger than you would think. It helps to create those nice broad strokes. And even though the under painting does get layered over, I feel the gestural marks do influence the final painting. So I'm just emulating the feel of this landscape. I felt like even the trees were reaching. I love it when the flowers are reaching to the heavens like they're in praise and worship. It really does feel like nature glorifies our Creator. And I love to make that feeling in my paintings. So I'm picking out a few colors. Now it is dry. I think I got a blow-dry and dried it very quickly, but it dries pretty quickly because it's alcohol. So I got these nice warm lavenders for the sky. One's a little more pink. One's leans a little more blue. And then I got a neutral color that's it's not really a white. It's almost a beige. And I wanted to keep some of the colors a bit more neutral and muted in this. And I just loved making the sky a little bit of that lavender with the blue that I had already put down. It just made such a soft pretty color for the sky. Now what I'm doing now is also called, oh let me stop here, I like also to put in a lighter color. This is the color I had, the lighter of the three, in an area of focal interest and also usually just above the horizon line, the sky does get a little lighter. Now I've gone back to, I think this might actually be a black. I think it is. I don't often use black, but I love to limit myself with a pastel selection like this pastel sets. You can literally buy a pastel set and create a painting. This one happens to be a great one. I have another video where I used only the Paul Rubens 36 set to create one painting. And in this case I'm using the two sets. But the black worked fine. I typically love to use a dark purple, a Terry Ludwig eggplant color it's called. But this proves that you can use black and layer other colors and you don't keep that harsh black color as we layer. And again this Luxe Archival paper is going to take a lot of layering, fortunately. Now I'm adding a little bit of kind of a pink color to the sky to give it a little bit of a glow. Oh and all I did with that dark was again I just reinforced the darks of the trees and some of those grasses. Again with reaching up gestural strokes, keep it nice and free. And now I love this really pretty neutral kind of a beigy color. It's not normally a color I would use for grasses. But these grasses are far into the distance and also like I said I want to give some gentle color. Now I've got this it's like a gray, gray blue teal. It's I mean I can hint a little bit of colors even when something looks gray. I can see how it leans and it leaned a little bit of greenish teal to that pretty gray. And I did have a month I think it was two months ago. I focused totally on neutrals for the whole month and the power of neutrals in your paintings. This is another beautiful neutral. I believe this one is in the 40 set. It's a neutral green and I think it's just so pretty. It's like a mossy green. So notice how I just layered those over the darks of the trees. And now I got this neutral. It's almost like a neutral purple. This dull purple. And it was just really fun using some of these colors. I know we would typically just go for greens. Let's get some foresty greens, some earthy greens, some tree greens, grass greens. But we really can pull colors that aren't maybe what you would normally choose but they are the right value. If you get the value, that means the lightness or the darkness right, you can get rather creative with your color choices. And these are still greens. This is another nice neutral green that I think that one is also in the 40 set. It was just a little lighter. And just so you know, we layer typically in pastel and with acrylic and oil from dark to light. The darkest value is usually first, layering the lysis on top. It's like we're building the tree from the inside out. And it works that way with many elements. Even these grasses. I get the darks in. Eventually you'll see me add the flowers in. I didn't worry about drawing any flowers or sketching any flowers to begin with. Because most of these flowers are small and I'm going to add them in after the fact. Not totally after the fact. I'm going to layer some over them too. But I first wanted to get in the base for some of these grasses. Again, I'm using some of these neutral colors. Some of the same colors I just used in the trees. It's going to connect the painting together and let it feel harmonious and congruent. This is a really pretty neutral kind of a brownish color. And what's interesting, I think the reason I decided on this is the flowers are so punchy. I made them even brighter pink than they are in the photo. And I even warmed them up a bit. I made mine kind of a cool red and pink. And that was because the set that I used, I wanted to try to use only these two sets. I throw in a couple other colors later. I'll talk to you about. But I loved those bright pinks that were in that set. And I thought if I have everything in this painting so vivid and bright, the flowers aren't going to get the attention. So that's why I decided on some of the neutrals. Now you saw I added in a little bit of a vibrant, more pretty purple in some of the grasses that gave nice shadows. And so now I'm adding another pretty neutral kind of purple color in the sky. It looks a little dark now. But what I'm doing now is adding a little bit of soft lavender. Now that I believe lavender was from another, from my workshop set of pastels. I have a whole lot of pastels in my workshop set that I don't necessarily know exactly which type it is, especially if they're a little like that one. Again, I'm using brown craft paper this time to test some of my flower colors. Often it's a good idea to do that before you commit to something. That way you already know. That's that red I was telling you. It's a cool red. But I thought let me just play with that and see if it makes some really punchy pretty colors. Now I don't know, which is pretty standard for me, the names of these flowers. But they were, you guys always tell me, I'm learning a lot from you guys, or y'all I should say. I'm a southern. I can't help but throw the y'all in there sometimes. But you guys help me so much with identifying flowers for me. They look almost like little pom poms. They have little spiky things sticking out of them. But again, just like with the trees and the grasses, I go with my darker colors first. Darker values I should say. And then I gradually layer lighter values on the tops. Again, building from the inside out. And here I go, laying a little bit of a lighter pink. And also I'm horizontally glazing some pink. Why would I be doing that? Well, a lot of times your flowers, if you see them in a field like this, they're not just right where you are. Often they cascade way off into the distance. And you won't necessarily see the individual flowers. You'll see more of a blanket of color in the distance. And when things are far away, they're usually a little lighter in value and a little more pale or neutral in color. So that's why I use that lighter pink to glaze over those distant fields. Just a hint. Now I'm just sprinkling in flowers in a way that I feel will be a beautiful composition, pulling the viewer in. The beautiful photo from Cindy was already doing that. You can see how the flowers, they're just grouped in very compositionally beautiful way already. That is that cooler red. See how it's a little warmer than some of those pinks? And it looks kind of segregated now, separated from the pink flowers. But I'll connect it a little like right now. I'm layering some of the pink over that warmer red to kind of make it feel like it is the same flower. And the reason I did that, I wanted to play with that pretty cool red. I don't think I had used it very much. And also, things are typically a little warmer in the foreground with color temperature and it gets cooler and lighter as things recede into the distance. So I thought it made those foreground pink flowers pop a little bit more using some of those reds. Sprinkling a little bit of that in now again. Also trying to make a visually appealing composition with groupings of flowers. And what we want to try to do is not create patterns where things are lined up like soldiers or in these look like mathematically equally divided areas. Nature doesn't do things that way. Often you'll have a little grouping of flowers here and then they cascade a little bit. And then another little grouping of flowers. And I often compare painting to music. There's a lot of similarities. One is that basically you don't want a pattern kind of like with music. If you had a song that had the same division of notes bump bump bump bump bump. Maybe a little skip every so often it would be a very boring song. So creating a painterly and more natural looking composition is much the same way. Now here I'm gradually adding like I said we're building the flower from the inside out and I'm adding some of those little linear strokes that seem to be almost exploding out of the flower. I apologize that I didn't zoom in more for some of the detail but I was trying for a layout of my camera view for you to see the pastels I'm actually choosing. And I know I couldn't get both sets in so sometimes you can't see what I'm choosing from the upper set. But if you have these sets you can probably figure it out. And I did just speed this up slightly just to make the video not so long. And now I'm adding some of the stems and grasses. I love to pop things up over the horizon line. I feel that just makes the flowers feel even more so like they're reaching to praise our creator and just to celebrate life. With stems grasses and leaves I don't often try to create everything exactly where it is in the photo. I usually don't actually. But I try to look at the general design of the leaf the general shape and then just give those suggestions throughout in areas again that compositionally look nice. Now here's that pretty neutral again rather than going with a really green green. I went with those gorgeous neutrals. I think it worked so well with the teal underpainting and the pink flowers. I really was having fun with color with this one. Now I want to pop some of the pink flowers up over where the trees are because that's going to create some contrast. And so those are like really far away so there's super little teeny pink flowers back there. And again just still adding in some pink flowers now that will be ones that will get more buried. If I just finish the painting here the flowers look much like they're on top of the field and that's not how things work. They get buried deeper with other grasses layering them. So you'll see me do that too. Now I did go for one of these pretty greens. I don't know if I'd even used this green yet and etc. But I added some of that to some of the trees. There was some light even though the sky looks a little cloudy. There was a little bit of light coming into the field and onto the trees. And light typically warms things up. So that's why I went for a little bit of a warmer green. And I wanted to punch up the color a little bit. I had a lot of neutrals going on. Playing still with just sprinkling in more flowers here and there. Trying to keep them in groupings that are visually pleasing. Now I'm going to grab a lighter value in just a minute. And I wanted to put some lighter flowers in this. Little sprinkles of I'm saying sprinkles a lot in this video aren't I? Of some lighter flowers in the background. But oh first what I'm doing here is I'm blending the sky a little bit. Once you get a few pastel layers down first they look kind of chunky. But I wanted the sky to look really soft. So I used another pastel. I didn't use my finger or a blending tool. But I let the pastel blend the colors. And I think it keeps things looking more fresh than if you use your finger. It gets all muddied. This is where I'm using a little bit of a lighter value. I thought maybe it's too light. So I was trying to this one's a little more neutral again. Which I was again loving these neutrals in this painting. I was just kind of putting in some where I thought it might give the hint of lighter values of flowers in the distance. Now I liked this little minty green. Isn't that pretty? And I decided oh I think these make the better choice for light flowers. I'm just continuing to work on some grasses. Getting in some areas that are a little bit darker. Where perhaps many of the flower stems and roots are tangled together. And that's why I called this painting tangled in pink. They seem like a tangle of flowers. And later you're going to see me actually do a little technique where I actually grate some pastels. Yes with a grater like a cheese crater. Grater just to get little sprinkles of value. Looking like little teeny flowers. And I often find that when you drop things or grate them they fall more spontaneously than if you tried to put them in yourself. We tend to put things very much mathematically and in order and in a pattern. So you'll see that great great method in a minute. But I'm using now what is called a prismacolor new pastels. Built in you pastel. They're harder pastel. Almost like in little rectangular sticks. And I'm using this to scumble in some grasses. I don't want my grasses all just reaching up again very orderly like soldiers. They're tangled. And they're going to have gesture and motion. And I don't want to be totally haphazard with it. There is a bit of rhyme and reason to it. But it does create a more natural looking painting. I'm even putting some of this color. It was kind of a nice soft green. A little lighter in value that made for some lighter highlights on some of these trees. And now it looks kind of like there's four trees there. And the ones in the middle look like they were more shadowed. So that's why I used this cooler color of a green to highlight some of those trees that were in the middle. And I'm using it also to scumble in. Give some suggestions of shapes of some of the leaves and the grasses. And here comes the cheese grater method. Again for getting in just little teeny flowers that might be growing. Like maybe a suggestion of baby's breath or something. I'm using kind of a neutral gray. Again used a lot of neutrals in this painting. And I do grab some more of the pink. What else? Yes some more pink. And I'm sprinkling some of those in. Like they might be really far away. And just giving some interest compositionally. And now I'm going to take a piece of tracing paper. I layer it over my painting. And I tape it down. I don't want it moving around. If it shifts you're going to make your little sprinkles of pastel kind of get muted and dull. Now I just grabbed a wine bottle. An empty wine bottle. I keep this empty wine bottle just for rolling. I don't have a good rolling pin. I need one. I don't bake a lot. And now when I lift up the tracing paper I've gotten some of those little sprinkles still left. And what that did is it set them into the sanded paper. And other than a few grasses I'm pretty much done here. And what I loved about this painting was the play of color with the neutrals. And I really think it came out lively and fun and energetic. So I hope you enjoyed this and learned something from this tutorial. And if you recreate from this tutorial I would love it if you would find me on my social media links and tag me. I love to see your recreations. Also consider becoming a patron for five dollars a month. I would really appreciate that. It helps this channel keep videos coming and you can find this original painting and more in my Etsy shop. All right everyone. God bless and happy painting.


It's time for us to talk ball presented by Duncan with General Manager John Robinson. Hope you get to spend some time with your family on Thanksgiving Day, a little downtime at least. Yeah, it was good to break a little bread with them, have a little family fellowship. Desmond Patrick is a pretty interesting story. After you drafted him in April, he doesn't make the ball club initially. For 75 days, he's on the practice squad and now he's part of the team. Talk to me about his improvement and what he adds. Yeah, I mean, he's really worked hard and probably improved as about as much as any player on the football team. Every receiver is different and they've got to kind of find their niche and, you know, Des is improving on doing that. He made some contested catches for us in the Houston game and we're going to lean on him here as we move forward. All right, let's talk about this weekend's opponent, the Patriots. They've won five in a row, they're seven and four and it seems like the improvement has largely been keyed by a defense that is just stopping everybody. What's got their defense going now? Yeah, they're playing really sound defense, Mike.  You know, high tower and Bentley in the middle. You know, those are two big, fast linebackers that really lead the charge. They've got Van Hoy and Judon on the edge, really disruptive edge guys. I think overall team defense, they're playing really sound football right now. What has impressed you about their rookie quarterback, Mack Jones? I think it's his poise. You know, he has been really poised. You can tell that he's played at a high level, at a big time program like Alabama. He's taken command. You can see him being vocal in the game, on the sidelines. He's been decisive with his throws, he's making good decisions. State certainly hasn't proved too big for him. But no surprise, big challenge this weekend for the Titans. Yeah, we're going to have to play good football this weekend, Mike. Talking about good football right now, let's talk about some of the top players in the state of Tennessee earlier this week. The announcement made the finalists for the Tennessee Titans, Mr. Football Awards, which will be presented on December 7th. John Robinson is going to be there, excited to have that all go down. Why is it so important for this organization to support high school football in the state of Tennessee? Well, I mean, I think that's where the foundation is laid, you know, from a football standpoint. You know, that's where these guys learn, you know, the importance of hard work and teamwork and dedication and sacrifice and accountability. Being a part of that, supporting that, putting our arm around high school football here in our great state is something that's extremely important to us.


From the CUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. Hello everyone, welcome to this special CUBE Conversation here in the CUBE's Palo Alto Studios. I'm John Furrier, your host with a great story here to tell and a great story with Bob Russell, the CEO of the CTA Group, also known as the Community Technology Alliance. Great story, very relevant in this time and it has to involve data and technologies for good. So, Bob, thanks for spending the time to join me today. Thanks for remote dialing in or internetting in, thank you. Oh, my pleasure, great to be with you. You guys have a really great mission with the Community Technology Alliance, also known as the CTA Group, which is you guys go by. Tell, take a minute to explain the firm and what you guys do, because I think this is a high impact story for this community, just in general, but now more than ever, it's a great story. Can you take a minute to explain? Thank you. We're a San Jose based nonprofit and we were founded in 1991 to provide the technology needed to support the work to end homelessness in a number of California communities and counties, primarily by providing data collection and reporting tools for agencies that were receiving federal funding to house the homeless. Several years ago, as we were looking at the data, we realized that we needed to expand our focus to not only include the homeless, but to include what's called homeless prevention. And homeless prevention is providing services to those who are not homeless, but who are at risk of becoming homeless, or those that are living in poverty and do not have enough money to pay the mortgage or pay their rent. And so they too are at risk of becoming homeless. Because what the data was showing is that once you become homeless, it can be difficult, it can be time consuming and it can take a long time for you to secure new housing. So if you can help people who are on the cusp of becoming homeless, that's a wonderful thing. Keeping people from becoming homeless in the first place is one of the most effective tools in fighting homelessness in the Bay Area and throughout the United States. That expanded focus meant we needed to rethink how best to leverage technology in order to help agencies' communities both in homelessness and homeless prevention. And so we focused on three different components or three tools. The first one was creating data integration pool. So that agencies that are using multiple systems and integrate their data into a single source of truth, they can quickly communicate and exchange data with one another in order to identify how best to help people in need in their communities. The second thing that we did was we created a mobile app so that you could collect data out of your closed or your proprietary system, upload that data later to your system or to a central data warehouse. And then also you could use this data that once we pulled your data in from multiple data systems and created a single source of truth, you could actually view that unified data. And the third tool we developed was a reporting and analytics tool so that you could quickly visualize your data, look at overall trends and determine what measures are most effective in helping people to remain housed or to help people who are homeless to secure housing as quickly as possible. So that's our story in a nutshell, John. Yeah, you know, one of the famous Q-alumnis, Jehan Rebecca founder of Cloudera once said in theCUBE, this is 10 years ago, and he only came from Facebook and then he said our brightest minds in the industry are working on data science so people click on an ad. And that really kind of became a rallying point in the computer science industry because this is really a data-driven strategy you guys are taking that's proactive. It's not reactive, which it's still got its own challenges. So using data for good is some reality there. It's like collective intelligence or predictive analytics or a recommendation engine for services to be delivered. So love it, love this story. I think it's super important. It's not going to go away. It's only going to get stronger and better. But I got to ask you with that, what are some of the challenges with the current environment for social services? Because you mentioned legacy, legacy systems. Well, there's legacy in process too. I can only imagine the challenges. What are some of those challenges in the current environment? Yes, yeah, there are many challenges, but I'd like to focus in on two. The first is agencies aren't networked. Their systems are not networked. And so agency A cannot exchange and communicate with agency B. And so what happens in most communities is that if someone is in need, whether it's an individual or a family, odds are they're going to multiple agencies to secure all the different services that they need. And because agencies are not networked, it can be very difficult to secure services. If you're in need, you can end up spending a lot of time going from agency to agency, asking what's available and seeing if you're eligible for services. So one of the challenges that we were asked to overcome by talking to various agencies and communities is can you allow us to continue to use our current systems? But can you figure out a way for our systems to communicate and exchange critical data with one another? And the second reason or challenge is tied to the first. Most agencies have multiple funding sources in order to provide the services that they provide. And many of those funding sources will say to an agency, in exchange for us giving you funding, you must use this system to collect data and to report out. And so what happens is a single agency can have multiple data systems that either that just simply cannot communicate with one another. And so this creates inefficiencies and this means that resources that would be going to a client, a family and an individual has to be redirected to doing multiple data entry and administering multiple systems. And so before we built any of our tools, we spent a good chunk of time talking to these various stakeholders in the homeless and poverty arena going, what are your primary pain points? These were the two that stood out for us in how we could use technology to help these agencies get a more unified view of what's going on in their community and what works. How has any of the systematic changes affected you? Because the networking piece is huge. When we see this play out in data-driven businesses, obvious ones are cybersecurity, the more data the better, because you know machine learning is a lot of things there. The other problem I want to get your thoughts on is this idea of not just not being networked but the data silos. So the data silos are out there and sometimes they're not talking to each other, even if they are connected. So if you're homeless or at risk of becoming homeless, odds are you're going to need multiple services to help you. It's very rare that an agency has all the services that you need so that you end up being helped by multiple services.  And so you do not get a complete picture of in your community of what are the various services that you are providing this client and which services are most rapidly helping that client move either into housing or into self-sufficiency. So agencies are very much aware that they have data silos out there, but they simply do not have the expertise or the time or the resources to manually take all of that data and try to come up with a single spreadsheet that tells them everything. On the role of data, obviously you mentioned the users, you mentioned an app. Can you just share some anecdotal examples of kind of where it's working and challenges and opportunities you guys are doubling down on? Because I mean, this is a really important point because if you look at our society at large today, the ability to deliver services, whether it's education, homeless, this poverty, it's all kind of interconnected. Help has the same almost systematic kind of functional role. You got to identify services, needs, match them to funding and or people and move as in real time or as contextually relevant as possible. If you do that right, you're on the front end, not the back end of reacting to it. Can you give some examples? Yeah, I'm thinking of a young woman. I mean, for me, this has been a powerful story for our organization in helping us to understand the human impact that data silos can have. So this is, in one of our communities, there was a young woman with them who was recently divorced with a young son who became sick. And so she went to the hospital to secure treatment for her child. The hospital, the clinic was able to help her. But when she asked about are there agencies out there, are there services out there that can help me with financial assistance and help me with getting food and finding stable housing? They told her, no, we can't help you, we're a clinic, but we can point you to a shelter. Well, by the time she got to that shelter, they were full for the night. And so she had no place for her and her son to stay. And so what happened is she ended up spending the night out on the street. And then she spent the next week looking for food banks. So she'd get food going to various agencies to find out, do you have any available housing? Do you have any financial assistance? And she was coming up against one obstacle over another. So if you're homeless and you don't have a car, and think about anyone in the Bay Area, how difficult it is to get around if you don't have a vehicle or someone who can provide you with a transportation? Her life changed. And yeah, her life changed when she ended up at a homeless encampment. And what's called an outreach worker went to that outreach, that encampment with our tools, with our mobile app. And this outreach worker met up with this young woman and said, how can I help you? And she, this woman explained, look, I need a place to stay for the night. I need food for my child. Can you help me? So what she did was she took her tablet, opened up our mobile app, and found, yes, there is a nearby shelter that has space available. Let me get you into that shelter as soon as possible. She also alerted the case managers at that shelter that this is what the woman needs. Can you provide that assistance to her as soon as we get her to the shelter? And so what happened was instead of wandering around the community trying to find help, because of this timely encounter between this young woman and this outreach worker, this outreach worker was able to get this woman and her child into a temporary shelter, an emergency shelter for the night. And then over time helped her secure her own apartment with financial assistance and also the other services that she needed. And for me, that is the essence of what we're trying to do here is simply remove the barriers for you to... In essence, what happened here was this woman was able to quickly determine through the help of an agency what's currently available and then connect her to those appropriate agencies to get the services that she needed. And so I have told this story many times. It still gets me that this is the beauty of technology. This is how you can leverage technology and help someone in need. For me, it's just amazing what you can do with the right, yes, with the right technology. It's such a powerful story because it also not only illustrates the personal needs that they were met, but it also illustrates the scale of how data and the contextually relevant need at that time, having the right thing happen at the right time when it needs to happen can scale. So it's not a one-off. This is how technology can work. So I think this is a great indicator of things to come. And I think this is going to be playing out more. And that is the role of data and people. This has been a fundamental dynamic. It's not just about machines anymore. It's the human and the data interaction. This is becoming a huge thing. Can you share your thoughts on the role of people because audiences want to get involved. You're seeing a much more mission-driven culture evolving quickly. People want to have an impact. Right. Oh yeah, data plays a fundamental role. The best way, what helps me to understand just how fundamental that role is, is that what data does is it creates a narrative on the past and current experiences of people in need. In other words, data tells a story. And whether that person is homeless or at risk of becoming homeless or living in poverty, that narrative becomes a powerful tool for agencies. And when you take that narrative, because you've been able to harness technology to create that narrative, what you can do with that narrative is you can coordinate available services to those in need. And as in the story of this young woman, you can also greatly reduce the wait times and the time that someone says, I have this need until you connect them with that available service. That narrative also helps you to improve your programs and services. You can look at what's working, what's not working and make the necessary changes so that you can end up helping more people. It improves access to programs and services. Instead of someone growing by bus or however, trying to go from one end of town to the other, imagine if you could go to a public library, for example. And as a person in need, you could log in and go, you could tell your story, enter some data and say, help me to find the services that I need. The other thing is that it reduces inefficiencies. Many agencies are spending an considerable amount of time in duplicate data entry in order to make sure that they're collecting the data and all the different systems that they need. And then I think another key thing that data plays a fundamental role is that you can take your data as an agency, as a community and you can tell your story to policy leaders and to funders and say, look, if you notice how you can support us in order to provide effective homeless and poverty alleviation solutions. So again, the idea- That's the key point right there. That's, I mean, the key point is, when you look at people process technology, which is like the, you know, overused cliche of digital transformation, very relevant, by the way. The process piece is kind of taking that same track as you saw the internet technologies change marketing and advertising performance based, show me the clicks. If you think about what you just said, that's really what's going on here. You can actually have performance based programs with specific deliverables to say, if I can do this, would you do more? And the answer is you can measure it with data. This is really the magic of this. It's a new way of doing things. And again, this is not going to go away. And I think stakeholders can hold people's feet to the fire for performance based results because the data is there. If you strive to do a good mission, if the systems are in place, you can measure it. Thanks for that question, John. Three possibilities come to mind. First, many organizations now financially match the donations made by their employees that they make to nonprofits. So I would say that check with your HR department to see if they have a matching program. And if they do, what happens then is that for every dollar that you give to that agency, your organization, the company that you work for will match that. And so your money will go farther. These same corporate social responsibility programs not only will match your donations, but the other thing that they will do is they will sometimes work out opportunities to volunteer at various nonprofits. And so you can also check with your organization to see if they do that. A second possibility is that you connect with groups such as the Full Circle Fund. There are other groups out there, but I'm most familiar with the Full Circle Fund. And it is a San Francisco-based nonprofit that leverages your time and your resources and intellectual capital to help out with nonprofits throughout the Bay Area. So whether it is that you're looking to volunteer coding or development skills or you're looking for some way to find out what's going on in the Bay community and how can I help? Full Circle Fund would be a great resource. And again, there are other nonprofits like them out there as well. The third thing is if you know of an agency in your area, a goodwill, a united way, a habitat for humanity, give them a call or check on their website to see what volunteer positions they have available or what they're looking for. And if it looks like a good match, give them a call and have that conversation. Those are three things that immediately came to mind for me, John, about if you wanted to help out, how could you? Well, certainly it's important, Mission. I really appreciate, Bob, what you're doing and your team. Bob Russell, the CEO of CTA Group, also known as the Community Technology Alliance, really putting technology into practice to help the services get to the folks that matter, that homelessness and the folks in poverty, on the edge of poverty, and it really is an example of how you can solve some of these systematic problems with performance-based, if you follow the data, follow the money, follow the services, it all can work in real time. And that's a good example. So thank you so much for what you do and great mission. Thank you for your time. Oh, thank you, and thank you for having me. Hey, I'm theCUBE. I'm John Furrier covering all the stories here while we're still programming here in theCUBE Studios with our quarantine crew. Bob Russell, the CEO of CTA Group with a great story. Check it out and get involved. I'm John Furrier of theCUBE. Thanks for watching.


Hey guys, how you doing? This is your boy Rich from Rich TV Live and you too can join the club at richpicksdaily.com where you can learn how to win and trade. What are you doing? This is your boy Rich from Rich TV Live and richpicksdaily.com where you can go and learn how to trade stocks and cryptocurrencies. And now we are talking about NFTs. Take a look at the Boo team, the Boo team NFT platform and they're also going to be buying space in the metaverse and they're also giving you the ability to be a part of a DAO voting system where the community has a choice. The community has a voice. NFTs are like literally the hottest, fastest growing new market in the entire world and we have committed ourselves here in Rich TV Live to bring you new projects that are undervalued, under-appreciated, under-exposed. We love Bitcoin and cryptocurrencies. We've been investing and talking about Bitcoin and cryptocurrencies since 2017 and this is a new sector that is exploding so quickly, so fast, so people keep asking me, Rich, where do we find NFTs? Well, you found the right place right here, right now exclusively on Rich TV Live, another NFT project, brand new project, the Boo team NFT. Let's take a look a little deeper, shall we? All right, so this is a new project that we've never seen before. It's called Boo.team and what are the key points of this project? It will be an NFT crowdfunding to support and launch young projects. Each NFT is an entrance to the Dow with the right to vote and share of profit, more NFTs, more influencers and shares. So we've been talking about NFTs and it seems like everybody's getting into NFTs. Boo.team is the website, co-own, co-earn, co-learn. 10,000 unique NFT passes to Boo.Dow with its own businesses, incubator, learning platform and collective profit sharing. There are links to their Discord and Twitter right on their website. We'll go show you some of that a little bit later, but I wanna show you guys what it looks like. So this is NFTs or digital art, really, really simple. NFTs are digital art and art is a big industry. So the idea of art that has been a big industry now moving on to the blockchain and going digital is what Boo.team is all about. The increase in the cost of the project should occur due to the self-sufficiency of the NFT. Because the NFT is a growing concept, the team here believes that this project will grow and the NFTs will grow and the prices will grow as well. The more ideas and successful projects they launch, the faster the minimum price per card will grow. So you can see here the concept, Boo.team is an association of crypto enthusiasts working together on a dream to build on NFT accelerator with a fund of 4,000 Solana. Investment decisions will be made by Dow. The project itself is aimed at gathering interesting projects and talented people, promoting their development and growing a strong community of like-minded individuals. So the price of Solana is going up and down, but 4,000 Solana is at 100 bucks would be at around $400,000. So investment decisions will be made by Dow. The project itself is aimed at gathering interesting projects and talented people, promoting their development, growing a strong community of like-minded individuals. So are you one of those like-minded individuals? Are you looking for a cool project? There are countless brilliant ideas around us. We can make them work together with our resources combined. Boo.Dow will kickstart promising projects, boosting their capitalization and the profits of participants. We see ourselves as a community and a decentralized fund that has a real impact on the Solana NFT market. Wow. And Solana is one of my favorite coins and one of my favorite projects. So this is a project that I think everyone should put on their radar, everyone should put on their watch list. You can see the initial Dow capital of 4,000 Solana, 333 traits on the bottom right, one of the most varied collections on Solana and the Boo Boss NFT to be announced. You can see on the left-hand side. So love to know your feedback on this project. If you liked the video, please smash the like button, comment down below, share the video everywhere and subscribe. You can see their roadmap, 100 Boo Boss Drop, release of Pooboo's on rarity aggregators, collaborations with celebrities and influencers, 20% airdrop of special Boo Twitter banner NFT, airdrop of 200 Solana to Pooboo and Pooboss holders, 200 Solana for the charity donation of Dow Choice, 40%, 1,000 SOL Solana transferred to the Dow Wallet, release of social crowdfunding NFT platform and starting regular floor sweep. 60% acquisition of a land piece in the metaverse based on Dow vote. That's so exciting. Everybody's getting into the metaverse, so is the Boo team. So they're doing NFTs, they're getting in the metaverse. Event on our land with influencers and music artists, AMA with team like this is wild. Boo Dow launch with voting weights, according to the amount of Pooboo and Pooboss NFT in hold. Collaboration with our secret celeb friend, I wonder who that is, and 100%, 3,000 Solana transferred to the Dow Wallet, Dow will vote on investment strategies and share profits. This is a sneak peek of some of the NFTs and NFTs are just blowing up. I keep telling everybody this is literally the hottest fastest growing sector in the world and there's going to be so many projects getting involved. This is the team. You can see the all deadie, blockchain developer, Rogoz, lead illustrator, and you can see other names and other positions. So in addition to everything that these guys are doing, these guys only Dow members can submit projects. So young projects will also want to come in. This is a great investment for their marketing budget. Dow will also give everything that the young project lacks, the opportunity to find the missing roles in the team, get the support of a large community and their investors and get funding. Decisions will be made by the community itself. Full democracy immediately after the mint, they plan to delegate the adoption of key decisions to the Dow. So this is your opportunity. You can see the positions they're looking for, positions for Rust developer, blockchain developer, digital marketing manager, content manager, financial advisor. So there's positions available. You can see that there are links to their Twitter and their Discord and we'll show you guys. This is the link goes right to their Discord. I think it's really important that everybody goes to the Discord. If you want to get involved in this project, the pooboo NFT project and metaverse project, you need to go to their Discord on the website and you need to access the whitelist and get Solana. So you need to go to the Discord where you can access the whitelist and get Solana. So just want everyone to know that the best way to access the whitelist and get Solana is go to the Discord on pooboo. You can go through just through the website and get access to the Discord. So I am on their Discord and you can see pooboo is the first and biggest NFT accelerator. We will reinvest 4,000 Sol into the best projects chosen by community pooboo holders will get the profits. So this is their Discord. I'm on their Discord right now. If you guys just remember that RichTVLive is strictly for information and education purposes, please do your due diligence, do your research before you invest in any projects that we talk about or discuss here on RichTVLive. Discord is hot. It's one of the fastest growing platforms for communities to grow. This is a community that is growing on Discord. They are also growing on Twitter. This is their website. It's boo.team. And you can see some of their NFTs. We've given you a sneak peek and we've shown you guys their website. So you can co-earn, co-earn, co-earn, co-earn right here with boo.team. And they have already been supported by several Solana influencers. So love to know what you guys think about this project. This is Rich from RichTVLive. We bring you the winners and we bring them to you first. We love NFTs. And you can see here, this is, you know, a new project. 10,000 unique NFTs passes to the boo.dow and we're bringing it to you guys first. That is our modus operandi here in RichTVLive to bring you winners and to bring them to you first. What do you think about boo.team? If you like the video, smash the like button, comment them below, share the video everywhere, and subscribe. And I'd love for you to comment on the video and let me know what you think about this project. And I'll see you in the next video. Thanks for watching. I'm Rich from RichTVLive, and I'm going to continue to bring you guys the winners and winners, and the winners and winners. And I'd love for you to comment on this project. We want to be on top of all the newest best projects in the world. We really are bullish on NFTs and metaverse. This is another project that is going to be doing both the NFT market and the metaverse. So love to know your feedback. And we love to bring you these types of projects first. is a new sector. Obviously with that comes a lot of risk, but also enormous rewards. Love to know what you guys think about Buu.team. Comment on the video. This is Rich from Rich to be live. We bring you the winners and we bring them too first. Go to richpicksdaily.com, learn how to trade, join the club and earn rewards. And another crypto project, it will be an NFT crowdfunding to support and launch young projects. Each NFT is an entrance to the DAO with the right to vote and share of profit, more NFTs, more influencers and share. This is your boy, Rich from Rich to be live. And I'm out.


This is stock number 91140, a 2014 F-250 Supercab Long Box. This truck has a 6.7 liter power stroke diesel. From this HD video you'll be able to tell that this truck is extremely clean all the way around. Green gem metallic is the color. And yes we do shoot our videos in HD so if you don't have it on HD turn it on HD right now to see just how clean this truck is. It's like you're right here standing next to the truck. This truck has brand new Cooper Discover LT27565 R18 tires and they are on the factory painted and polished aluminum alloy rims. These tires are brand new. We put them on in our shop during our safety inspection. Frame and underbody is very clean on this truck. Didn't see any dents or dings on that front fender. As you take a look at the hood you can see just how clean it is, how reflective that paint is. No dents, no dings. You can see that metal flake and that green gem paint. Very good looking color. Passenger rim is in absolutely perfect condition as well. No scuffs or scrapes or corrosion and that tire is brand new too. As you go down this side of the truck you can see just how clean the body is, how reflective the paint is, how clean the body is, how glass like that paint is. We take these videos so if you are far away or even if you're close by and just cannot make the trip down you can still see the truck here, the truck and of confidence in the vehicle that you're looking at before you even get here. Cab is very clean as is the entire body down this side. We feel that videos give you a little bit better idea of the overall condition of the vehicle than just pictures. This back rim just a little bit of corrosion right there. But these back tires are brand new as well. Frame and underbody is very clean on this truck. And it's like that all the way underneath. As you can see it has all the factory exhausts remaining on it. So it hasn't been modified in any way. Factory chrome step bars. Rear bumper is in excellent condition. No dents or dings on that. It has backup sensors. Full towing package which includes the receiver hitch four pin and seven pin wiring. Locking tailgate has the backup camera right there. It has a rolling tonneau cover. This is a pace Edwards rolling tonneau cover. It basically goes like that. Then you use this strap to pull it back. You can see it has a drop in bed liner. Goose neck hitch. And then once you pull that back it locks. Down this side of the truck is just as clean as the passenger side. We want to make sure we get the most accurate representation of the vehicle as possible. So that when you get here there's absolutely no surprises. Saving you time and money. See just how glass like that paint is. Very good looking truck. Has the power scope mirrors. Driver side door code entry. Inside the Lariat package gives you the tan leather seats. There are no rips or tears on these seats. Both of these seats are heated and cooled. This is a memory driver seat. Factory all weather floor mats throughout. Carpentine is very clean underneath. Has the memory driver seat power scope mirrors so they power fold in. They also power telescope and power windows power locks. Auto headlamps and power pedals. And as you can see this truck has 45,228 miles. Multifunction steering wheel. This is your information center controls. On this side you have your audio controls. And your Bluetooth audio controls. You also have your cruise controls up here. My Ford touch radio. You got your heated and cooled seat buttons. This is also where the backup camera shows up. AM FM series satellite radio capabilities. Your CD player is right there. Does have dual climate control. Factory brake controller or tow command as Ford calls it. Turned out four wheel drives, traction control system. And then of course a six speed automatic transmission with the optional tap shift. You have a 110, 150 watt plug-in up here. You also have one in the back. And of course like I said it has a sync system so you can pair it to your Bluetooth phone. Up here we have the power sliding rear window to map lights. And the passenger seat is absolutely perfect as well. Factory all weather format on that side. You can see the carpeting is very clean. Take a quick look at the back seats and then we'll check under the hood. Back seats are very clean as well. Rips or tears. You can see it does have the power sliding rear window with the built in rear defrost. Under here we have, I believe this is the subwoofer for the vehicle. And the carpeting is very clean back here as well. And there is your 110, 150 watt plug-in. Very clean truck inside and out. Much of the same under the hood. 6.7 liter power stroke diesel. This truck has been fully safety and inspected by our service shop. Has a fresh oil and filter change. All the fluids have been checked and topped off. And this truck is 100% ready to go. If you're looking for a super cab long box, Lariat power stroke diesel. I can't figure one that's going to be any nicer than this one. Brand new tires all the way around. Fully inspected. Clean as a whistle. And 100% ready to go. And to see more pictures of this truck, or one of our other 400 new and used cars, trucks, SUVs. Minivans, Wranglers, half ton trucks, three quarter ton trucks, one ton trucks. You name it, we got it.  Videos of every single used vehicle that we have. All at SummitAuto.com. Thank you so much for checking out my video. If you want to make this super clean 2014 years, give us a call<PHONE_NUMBER>. Ask for one of our sales associates to help you out with stock number 91140. Tell them the video sent you. And we look forward to helping you with the super clean 2014 F-250. In a second you'll notice a link to subscribe to our YouTube channel on your left. A link to more heavy duty truck videos on your right. And if you're not on our website already, on the bottom link to this particular truck on our website. Click those, check them out. And we look forward to helping you with the super clean 2014 F-250 super cab long box power stroke diesel. Thanks again.


Over on the girls side, same teams playing right before. Cornorlan looking for an opening. Decides just go for three and she gets it.  Greyhounds with the lead in the second. Later, Josie Savage gets the takeaway and runs it back for the nice layup. Kelly, you're trying to stay in it. A bit of a defensive lapse on the other end. The Greyhounds would get a wide open layup. Jenna Manke was left wide open. The Greyhounds come away with the win 67 to 37. If you enjoyed this segment of Lakeland News, please consider making a tax deductible contribution to Lakeland PBS.


Today, this morning, I am going to talk to you about a new container runtime and something that we just announced, Cata containers. So when you look at the isolation spectrum, on the one hand, you have containers. On the other end, you have virtual machines. Containers are awesome. Containers are very, very fast, very simple, very easy to use. And they're just very, very easy to bring it up really quickly.  Virtual machines are amazing in that they're very, very secure. And they're secured by hardware. And they can run a full operating system and so on. The drawback to containers is that you have many, many containers typically running on one kernel. So if that one kernel is compromised, all of the containers that are running on that one kernel are basically compromised. Virtual machines, the drawback is that they're slow. And you can't run some of the modern applications and cloud and native applications that you would want to run with that amount at that kind of speed. So you basically end up with making a choice, speed versus security. And sure, some people would just run a container on top of a VM, but not sure how much that would get you. And what we really, really wanted was both speed and security. And when we started thinking about this, a few Intel engineers about a couple of years ago started a project that's called the Intel Clear Containers. And the objective of that project was how do you make containers more secure? And the one thing that we ended up looking at really, really closely is how do you use the technology that made virtualization so secure, the virtualization technologies whether it's an Intel VTX instructions and so on, to make in a container context without bringing in the drawbacks of being able of running a full virtual machines. So at the same time, this was a couple of years ago, at the same time, another company, Hyper, came up with a similar concept. And they implemented it in a very, very similar way. And that project was RunV, which effectively does the same thing. So yesterday, we announced a new project basically that merges both of these projects into one. And that is called the Cata Containers. So Cata Containers is basically a new container in time. It's a hardware accelerated containers that uses virtualization technology. And it basically runs at the speed of containers. So you get that advantage. At the same time, it uses, in its underlying implementation, it uses virtualization technology that makes it far, far more secure than containers. But it does look and behaves like a container. So boot time is sub 100 millisecond. And it's very, very lightweight and so on. And more importantly, it completely integrates with the container ecosystem. So it complies with the container runtime interfaces. It is managed and looks and behaves and integrates really well with all the container ecosystem, whether Kubernetes and all the orchestration and management software that is designed for containers. So it looks completely like a container. By the way, Cata, the word Cata, is from Greek. That means trust. The project itself is a completely independent open project with many supporters from the start, as you can see. But also, it is hosted by the OpenStack Foundation. And one of the unique things that we are doing with this project is a slightly modified version of a governance process that does not have any kind of a pay for play kind of governance or any kind of boards and business boards and any of those things. And instead, it's only a technical steering group that is completely based on contributions. And what we're doing with that is the initial technical steering, and that gets elected every six months, but the initial technical steering group, it's just a few of the key contributors and people working on the projects. I think it's in a few engineers from Intel, Google, Huawei, and Hyper. So also another thing about Cata Containers is that it does support the multiple hypervisors, multiple architectures, and integrates with multiple software stacks, multiple software stacks like Kubernetes, OpenStacks, and so on. So get involved. We ask you to get involved. The amount of work that it takes to do, I mean, Cata Containers is not a simple one technology. It touches a lot of things. Many optimizations in QMU, many optimizations in the kernel, in SystemD, and just to create a runtime that can behave like a container runtime. So finally, I'd like to thank the OpenStack Foundation for bringing all of this together. And I would like to also thank the CNCF and the Linux Foundation for all the help that they gave us in integrating this into a larger ecosystem. Thank you very much, and have a good conference.