This is a so-called amphiphatic molecule, very typical of lipids, all of them are amphiphatic. And amphiphatic, if you remember when we talked about hydrophobicity, that means that we have one part of the molecule that's fat-loved, like oil. And then we have one part here that is water-loving or fairly soluble, the head group. There are many names here. These molecules are actually synthesized in your body from a glycerol. And then we have two fatty acid chains here that bind. So occasionally we talk about these, the fatty acid chains, the glycerol, and the head group. There are even more fun parts here. Do you see that there is a blue atom up there? So this is an NH3 group, same type of group as we have on the lysine side chain. So we actually have a full plus one unit charged on this lipid here. Do you see that there is a yellow atom there? There you probably see it. That's a phosphate group. You've seen phosphates before in say ADP and ATP. And the phosphate, well, just as a phosphate ion, all the oxygen surrounding this means that we have a net minus one charge here. So you have a plus one charge here and a minus one charge in the head group. Where have we seen this before? That's right, in the amino acids. So this entire head group here, it's zwitterionic, very common for lipids. There are lipids that have positively charged head groups. There are also some lipids that have negatively charged head groups. In fact, the negatively charged ones are slightly more common on the surface of our cells. But I would say that the most common lipids are zwitterionic. So they're exceptionally polar. They will love, they have to be sold in water.  And then we have this transition group, the linker here, the glycerol, that then binds to these long purely uncharged hydrophobic tails.   The only reason why it's behaving like this is that I'm hiding all its neighbors around it. So this is again from a molecular simulation of a lipid bilayer. Of course, people couldn't do that in the 1950s. So I bet that you've all seen these idealized movies of what a lipid bilayer looks like. I'm going to show you one of them in a few seconds. But in the meantime, I will show you what else we can do with molecular simulations today. So when I was a PhD student, some 20 years ago, slightly more even, computers were finally getting fast enough that we could simulate lipid bilayers. And in fact, I wrote the large parts of my thesis on them. And that made us ask the question that couldn't we really simulate the process? What happens if you start to throw these in water? And do we, in fact, get bilayers, which we did together with Sivir Jan Marenk?  And this is again a bit of rehash of the molecular simulation lecture. So do you see that the light blue lines here, that's a periodic box. But just to stress that this is a continuum, I drawn periodic copies on all sides of the box so that effectively we have an infinite path of lipids with the tails in purple. You have the charged head groups or the sweater ionic head groups in this case, in orange or yellow. And then we are drawing the waters in light blue as very thin lines, otherwise you wouldn't see the lipids. And then we start the clock. And already within like a nanosecond or so, it goes exceptionally fast. You get a hydrophobic collapse of the tail parts. So you see here that the tails are then forming some sort of blobs. And then you have a periodic image and that's why it looks like you're having multiple blobs. But it's almost just one blob in this cell. You're going to lose sight of me for a second because I'm going to need to put another image here. Another few nanoseconds later, you almost formed a periodic structure here. Well, it is a periodic structure, but it's still fully mixed up with water and everything. So there's water holes going straight through this nascent bilayer, as we call it. And the head groups are pointing everywhere. There are some head groups on the inside of the bilayer. There are some lipid chains exposed on the outside and everything. What then happens after say, 20 pickers and nanoseconds or so, I think it's this. Now, all the head groups are now facing the outside because it was so expensive to put the head groups inside lipid bilayer.  And they are in fact in contact with each other since it's periodic. There is still some sort of hole through this bilayer, roughly here, you see. And you might not see it ideally here, but there are even some head groups pointing to the inside of that hole. That actually makes sense because if we had a hole with water through it, that water would be exposed to the hydrocarbon interior, the hydrophobic parts. And that would be very expensive. So the lipids that would normally face the water, well, they would look like this. In this case, some of them are still facing the inside of this pore. So on one side, they look like that. These are my hydrophilic parts. And then they're facing the pore and then on the outside. And that's a somewhat stable part because to break this, we now need to break that water pore. And this turns out to be stable for maybe 15 nanoseconds or so. And then eventually, we're getting to a transition state where this water pore is collapsing. And a little bit after that, we have a beautiful continuous bilayer formed. This was just an example. And I'm not sure whether we got the energetics and timescales absolutely correct. But the whole idea is that we it's very obvious that these bilayers will form rapidly. There will be some sort of free energy during the formation of this process. And again, the reason for this is to rehash what you've learned. So initially, we start out at the relatively high free energy, right? And then we're getting a drop in free energy due to the hydrophobic collapse. We want that. And then it keeps going down. But to actually, and then we're in a fairly stable situation here where we have this water, we might even go down a little bit more. We have this water pore formed and the lipids are not really exposing anything to anything hydrophobic to the water. But we still have the water pore and eventually there's going to be some sort of free energy barrier. We have to get over what we closed that water pore and then eventually you get down to a really stable state where we formed the bilayer. Again, this is drawn purely qualitatively. But just from looking at a process like that, you should be able to draw a curve like this. You should also be able to guess what happens here that the reason for this free energy barrier is mostly entropy, right? That we need to break that water pore that's going to lead to exposed hydrophobic compounds, hydrophobic compounds exposed to the water, hydrogen bond reformation and everything. It's going to be some searching. It will take a while to get over it. But eventually this is going to be a more advantageous state. Let's look at what that lifted bilayer looks like in the interior.


And they did the smart thing. You do it with all politicians. You put them out in the sunlight with no shade. And it's amazing how much shorter the speech has become. Make you follow the five B's of public speaking. Be brief, brother. Be brief. So I will certainly adhere to those rules. It's a, it's wonderful to be here today on Colonial Drive. Many of you may know that our first home as a couple, DeAndre and I, we lived just four blocks down the road. It's where we started our family here in this great city that, quite frankly, has given me an opportunity to do all the things I've wanted to do in life. Bless me. God bless me. With coming to Columbia over 30 years ago, a fantastic education and a family and a community that's loved me and invested in me in so many different ways. It led me to the St. John Baptist Church just up the road. And I mentioned that because of course, Reverend Roscoe C. Wilson Sr. He baptized me. He married me. And baptized my wife as well. And the ties to that church led me to this community, led me to our assistant pastor, President Wilson, who along with his brother, Roscoe got us here today to recognize Mr. Shives. I'm a big believer that we are all products of the men and women who come before us. Those who work to build this wonderful experiment that we live in, this great nation, the, quite frankly, I believe the greatest nation in the history of the world, built by men and women who sacrifice, who contribute, who give of their time, their talents and their treasures for us to have the opportunity to do that much better than our parents and even more importantly create a world where our children and our grandchildren do that much better than us. That doesn't just happen. It requires men and women of commitment, of sacrifice. All cities across this country, not unique to Columbia, 30, 40, 50 years ago, saw an exodus of businesses, people leaving to go to the suburbs and then the suburbs beyond the suburbs and then the suburbs beyond those suburbs and very few businesses in this community and all around Columbia chose to stay right here in the communities that given to them and they realized that they were going to continue to pay it forward and Shives General Holman and Mr. Bill Shives is one of them. He's right here on this immaculately kept corner for many moons, meeting the needs of families in their most challenging times, doing it with compassion, love, bringing the grace and mercy of Jesus Christ to families when they need it the most and it is an example, I believe, of the very best of us, the very best of us. So it's my pleasure on behalf of the people, Columbia, my friend and the city councilmen for 22 years, 23 years now, Sam Davis. Sam, Samstead does not let me come to North Columbia without having a passport. I have to ask to come out here. But on behalf of Sam, on behalf of our fantastic neighborhood leaders who work every single day to make this neighborhood strong and safe, as you mentioned, Gilly and some others and folks at St. John. Mr. Shives, we're just here and I want to thank John and Sarah. John and I first discussed this and John and I did not call each other and coordinate our outfits this morning either by the way, y'all. Potter called me and told me what his dad was wearing and I decided to suit up properly. But John and Sarah, I thank you for your long time friendship and I know how important it was for us just to come here and I'm a big believer, I get around this country and I mean if you know in five plus months I will be cycling out as mayor of this great city and I've had the wonderful pleasure of getting around the country and getting around the world telling people about what makes this place special. How you have the University of South Carolina and Benedict and Alan, how we're the home of Fort Jackson and we train the greatest fighting force the world has ever seen, we're a state capital which in some days is good and some days bad, that's a whole other story. But I tell people that when you're trying to figure out what makes this place special, you leave posts, you leave campus, you leave the state capitals and you find what really makes this special of the people. You still find men who open doors for women, you find folks who still pull over from funerals, those who are on reticent about thanking God for his many blessings in our life and tell them you can still find sweet tea in restaurants, Mr. Shives, and I tell them you still find people who know the two most important words in the English language and those are simply thank you. Thank you. This is a wonderful way on behalf of the people of Columbia and the thousands of families that you've touched, Mr. Shives, to simply today say thank you and know that your labors, that your contributions, that your commitment to this community have not been in vain and will never be forgotten. Thank you. Stayed to join my friends. Ladies and gentlemen, Bill Shives. Thank you so much, Mr. Mayor. I'm very grateful. There's so many, many people that I have to thank for this day and first of all, my wife Barbara and the children, Gail and John and Jane and of course, Sarah and the children, both Potter and Allie. I'll be very, very grateful. And my nephew Randolph Shives, who could not be here with us today, was not feeling well. But I'm certainly very grateful to all who have taken part in giving us the opportunity to serve so many, so many, many nice families over the years. City Council, back through the years, when I, this of course at one time was a separate city from the city of Columbia. It was the town of Eau Claire that was later merged into the city of Columbia. And of course went under, went in under the zoning regulations of being grandfathered in. When we had the vision of making this facility what it is today, of course we went to the city for the permits and to the council and there was just, you just wouldn't think there would be any way that they would be able to allow us to do it. But somehow, some way, the city of Columbia got behind us and helped us do everything that we needed to do to better this facility to be able to serve not only the community but the Midlands of South Carolina. And I am most, most grateful to all who have helped through the years. I had no idea they'd be a group like this. Here I do better on the other side of the speaker stand than I do on this side. But thank you all so, so much to all for being with us and what you all have done to help us through the years. Thank you so much.


Hello friends, welcome to the session I am Malka. We are going to discuss matrices. We have to solve the equation for x, y, z and t if 2 into matrix 2, z, y, t plus 3 into matrix 1 minus 1, 0, 2 equal to 3 into matrix 3, 5, 4, 6. Now we'll solve LHS in RHS individually and this gives us 2x, 2z, 2y, 2t matrix plus 3 minus 3, 0 and 6 as our second matrix. Now we'll add these 2 matrices, this gives us 2x plus 3, 2z minus 3, 2y plus 0 and 2t plus 6. Now we'll solve RHS equal to 3 into matrix 3, 5, 4, 6. This is equal to 9, 15, 12, 18. Now we'll equate RHS and LHS. 2x plus 3 equal to 9, this is our first equation, 2z minus 3 equal to 15 is our second equation and 2y equal to 12 is our third equation and 2t plus 6 equal to 18 is our fourth equation. From equation first we have 2x plus 3 equal to 9, this gives us 2x equal to 6, this implies x equal to 3. Now from equation second we get 2z equal to 15 plus 3, this implies z equal to 18 by 2 that is z equal to 9. Now from equation third we have, this implies y equal to 12 by 2 that is y equal to 6 and from equation fourth we have 2t equal to 18 minus 6, this implies 2t equal to 12, this implies t equal to 12 by 2 equal to 6. Therefore x equal to 3, y equal to 6, z equal to 9 and t equal to 0 is the required solution. Hope you understood it and enjoyed the session. Goodbye and take care.


ct employee, you're getting into, you're opening up a can of worms if you wanna try to get rid of that person. Let's say for example, they have two years left. Are we gonna have to pay that person out the last two years? Is it a part of an agreement to get rid of that person and then hire another person? That's the only problem I have with this being a contract position is that if it's at-will and believe me, if that person is an at-will employee, they know their feet is to the fire. They have to perform because if they don't, they're gone. You got somebody with a contract and I'm not just referring to Director Amodio on this, I'm talking to anybody with a contract. After that six month probation, basically you're on Easy Street for the next four and a half years and to get rid of somebody once they're off probation is very, very difficult. It's a whole different standard in my opinion than an at-will employee. Let's see, we've got Alderman Samson. I'd like to yield that over to Alderman Van Akron. Thank you. Apparently my work is not working either, Mr. Chairman. I guess just reiterating, I think the only way to make this cost effective is to do it the way it's proposed. I think we need to consider the long-term effects. It's about getting this position on our table of organization. If I'm understanding correctly, at the end of this four years, it would be an at-will position at that point. As Alderman Carlson brought up, if he's not meeting the requirements of this job description, we could remove him for due cause at that point. But either way, at this point, Director Imodio, which I agree is doing a good job, is here for the next four years in some capacity. And I guess I'd refer to City Attorney McLean just to confirm that. We have a contract with him for the next four years if we would delete his position or I guess that's really the only way I foresee it going, we would then owe him the rest of the money for the rest of his contract, is that correct? Yeah, it doesn't have a contract. He's got a term, he's got a five-year term and there's four years left on the term. And just to say, as far as removal for cause, for, it's basically what you're doing with the mayor. I mean, that would require a quasi-industrial hearing, all that. It's different than at-will employee. The council could just vote by a majority vote to remove the individual without a lot of due process stuff. So there is a difference there. Correct, and I understand, and I'm not trying to say that this is the best case scenario, but this is the scenario we're in. We either make it cost-effective and we go ahead with adding this position, or in my view, I can't support going ahead with this position and I think there's others that have indicated that same problem. It's either cost-effective and we add this position and we deal with the situation we're in, or I guess in my view we don't go ahead with the position. I, for one, would rather see us go ahead with the long-term plan of adding this position under the current circumstances to make it cost-effective if in four years, whether it be for cause or if at the end of four years, we decide not to renew a term and put Director Amodio in as an at-will employee or he decides he doesn't want it or for whatever reason, we just want to do a nationwide church and he can reapply. I think that's the best way to go. To get this position activated, to get this on our table of organization, to reorganize, to redo how we do government here and to get this started, again, I think this is the situation we have to deal with and we need to move ahead with it. Thanks, Alderman Van Ackren. Alderman Hammond, you're flashing. I don't know what this thing's been doing. Now it's green again. I've got the Van Ackren, but you're gonna have to hit it again Alderman Born. Go ahead. Let's go. Again, there's only a broken record here to reiterate Alderman Van Ackren's comments again. I think we're throwing the baby out with the bathwater here. We're gonna create this long-term position. I don't want to split hairs about a four-year term. When we hired Amod, and this body was the one that did it because we had to approve it, as a finance director, I think very few people can argue, at least I've worked with Amod on a regular basis, that he hasn't done a fantastic job and if you look at his job description relative to what the city administrator's position is, a lot of those things he's already doing in an unofficial capacity inside City Hall already. Department heads are already going to him as the go-to guy. So again, I don't want us to get so short-sighted on this individual that we, as Alderman Van Ackren indicated, missed the big picture on this one. Putting the city administrator in is the goal here. We have the opportunity to do it on a cost-effective basis. Fortunately or unfortunately, depending on your perspective, you might have to slide somebody else into this position in a temporary basis, who by the way, can do it and do it very well, in my opinion. So again, I would ask that you step back a little bit and again, to coin a phrase, don't throw the baby out with the bathwater here. No solution is ever gonna be perfect and I think this is a pretty good one, so. Thank you. Thank you, Alderman Hammond. Alderman Carlson is next. I've got, it's been said by, thank you Chairman, it's been said by, Alderman Hammond here and Van Ackren, so thank you. Thank you, Alderman Carlson, Alderman Bursi is next. I call a question. Yes. Second. Actually, do we ever get a motion on this? Yeah, we did have a, we originally had a motion by Alderman Bursi, do you have a motion? No, we didn't have a motion. I made a motion to bring those three documents together and then you made a motion to change. Oh, that's right. We never made a motion. Let's go back three hours ago. We had a motion by Alderman Bursi and a second by Alderman Belt. That was to amend it. We never had an original motion on the document, though. The motion by Hans Bursi and Belt Hammond to clarify. You stood up to clarify. Right, but we never had an emotion on the original document. We had a motion on the amendment that he wanted to make. We move forward after we vote on the amendment. I mean, we can still do the amendment and then go forward with whatever document we have, whether it's amended or not, is that correct? Well, if I may real quick with that, you explained everything down below, but it didn't report two. That still didn't get resolved. We were gonna change it to consult with the input from. Input there. He won it all, sorry. We're only on 1163. Yeah, we're only on 1163. Right, but we don't have a motion on that on the floor yet. We have his amendment, but we don't have a motion. And the term of the claim, do we need a motion before we're gonna have an amendment? Correct? A motion? Yeah, it was my understanding the way it was working was Alderman Hammond wanted to act on all three at once. Chair suggested just starting with the first one. And I don't know if there was a formal motion to put that on for passage or not, but then there was an amendment. It's true that you really can't amend something that hasn't been put on the floor to begin with. I just wanted to handle all of these individually because I think there's gonna be discussion on all three of them. I can remember that. I'd be perfectly happy for you to make a motion that you put this 1163 upon its passage and then under discussion we can do the amendment. So moved. Second. We have a motion and a second to put 1163 upon its passage by Alderman Hammond who seconded? Alderman Rasler. And now we've already have a first and a second on the amendment and I believe the amendment was to take the reports to any reference to the mayor starting reports to take the mayor out and change that, if I'm remembering your motion correctly, Alderman Bursi, reports to Strategic Fiscal Planning Committee and the Common Council. And then down below any part of the document that references the mayor, change that to Strategic Fiscal Planning and the Common Council. Am I getting that right? You did, but I think I can I don't know if I can retract that amendment from all the below. And we did discuss the reports too which was the biggest sticking point for me because going forward with the mayor he does need some input on these. So I'm okay with now the full explanation on this and where it's going, just the top portion on the reporting too. However, that's gonna be reworded. Okay, so you wanna make your motion then just the reports to that the Chief Administrative Officer reports to the Strategic Fiscal Planning Committee and the Common Council. Yes. Would you be all right with that, Alderman Bursi? Yes, sir. With input? Is there any further discussion on that amendment? Alderman Hammond. Thank you, Mr. Mayor. Our service. Please. It's gonna be a long night. That was probably the wrong taboo, wasn't it? Sorry, Alderman Born. I guess the only comment I would have about having the reports to the Strategic Fiscal Planning and the council, you know, I think I would just leave it the council, this body with input from the mayor if I could make that friendly amendment. I think we've got points down further in the document that, you know, talk about the hiring, the firing, all of those kinds of processes that, you know, again bring that back within the council. Again, looking long term, keeping the current situation out of it. As I reiterated before my challenge when I thought about the Strategic Fiscal versus the Executive Committee of the council was that Strategic Fiscal is still appointed by the mayor by the committee heads that they appoint. So again, you could make that a somewhat political kind of position where the president and vice president committee the whole are all elected by this body to be our leadership. So I would think that would be a more accurate representation of this body. So I would just ask for a friendly amendment to change that to common council with input from the mayor. Well I'm just looking, I'm just looking by me at number five under there where essential duties and responsibilities where if we leave consults with the mayor on emergent matters requiring policy decisions, there again, I don't know if I'm comfortable with that. Baldwin-Hammond? Again, I would reiterate this individual still has to work with the mayor and consults does that mean take direction from? It just means get input from. It's impossible and I think very short-sighted to think that we're gonna be able to cut the mayor out of this process entirely. Still an elected official of the city of Sheboygan and should have some input in what goes on in the day-to-day basis. So again, the consults or input from gives the mayor the ability to still function in city government. And I don't think there's anything wrong with a city administrator who again represents this body also consulting with the mayor on policy matters that affect the city overall. I would agree with you if it said American direct but consulting does not in any way, shape or form provide a direct line of authority. Thank you. Gene, what is the, I just wanna ask one more question of the council is the council comfortable with going ahead with appointing director and modio to this position for years or do we want to make him or the other alternative that I suggested before is why not keep the finance director and just make him acting chief administrative officer reporting to us all the diversity suggested the council. I think the only issue I would have with that is the finance director's current job description is that it reports to the mayor. So now you've got him doing a position that reports to the mayor and a position that reports to the council. And again, to me, it just doesn't make any sense. He's gonna fill out the rest of his appointment and we can continue to move forward from there. I think that creates even a bigger mess because again, he's now a master of two puppets and that just isn't efficient at all. Can't we have the finance director report to the chief administrator officer only? He's gonna report to himself? And the council, well, yeah, okay, I got you. Who's, I got a flashing light here. I got Alderman Van Ackron again. I guess I would just like to once again call the question on the amendment and the passage. First, I believe first, we'd have to vote on the amendment that would make the chief administrative officer report to the common council. With input from the mayor. Input from the mayor. Second. Second. We've already got a second over here. Second. Any further discussion? Please call the roll. Belt. Aye. Oren. Aye. Carlson. Aye. Decker. Aye. Common. Aye. Hammond. Aye. Koff. Aye. Kittleson. Says aye. Grin. Reisler. Aye. Samson. Aye. Van Ackron. Aye. Vanderweel. Aye. Anniversary. Aye. It's Corby here. We have 13. I am. 13 ayes. Motion carries. Motion carries. Now we have to vote on the document. We're just voting on the amendment, so now we're gonna be voting on 1163. We have a motion and a second to pass as amended. Please call the roll. Belt. Aye. Oren. Aye. Carlson. Aye. Decker. Aye. Hammond. Aye. Koff. No. Kittleson. Says aye. Reisler. Aye. Samson. Aye. Van Ackron. Aye. Vanderweel. Bursi. Aye. 12 ayes. Motion passes or document passes. Next we move on to document numbers, our item number 16, council document number 1162. An ordinance creating division five of article three of chapter two of the missile code relating to the position of chief administrative officer. Alderman Hammond. Thank you, Mr. Chair. I move the ordinance to be put upon its passage. Second. We have a motion and a second to put the general ordinance upon its passage. Is there any discussion? Hearing none, please call the roll. Belt. Aye. Oren. Aye. Carlson. Aye. Decker. Aye. Hammond. Aye. Kath. No. Kittleson says aye. Racler. Aye. Samson. Aye. Van Ackron. Aye. Vanderweel. Aye. Bursi. Aye. And again, we have 12 ayes, one no. General ordinance passes. Next we have item number 17, and that is council document number 1158, which passed the council on 9-6-11, a resolution establishing the position of chief administrative officer for the city of Sheboygan. And I just put a note on here because I knew we were gonna have a lot of discussion on this tonight, and that was a discussion on the comfort level of the older persons regarding the effective date of 12, I'm sorry, 10-111 after our discussions this evening. So the reason I put that on there before I open it up for discussion is I figured we were gonna have a lot of discussion on this, and what were we gonna do, and did we feel comfortable on moving ahead on 10-1? I guess my opinion anyway, before we open it up for discussion, these passed pretty convincingly, and we've had a discussion, so I guess my comfort level would be to move ahead with it December 1st, but that's my opinion. I've only got one vote. Is there any other discussion? Fix my light. Alderman Hammond. You meant October 1st, right? October 1st. Yeah, October 1st, it's getting late. Yes it is. Thank you, Mr. Chair. And again, the reason for the October 1st, again, because we already had the position in-house, or the person in-house, it allows us to get to that position much more quickly and get that individual operating in that position a lot more quickly. As we're going through budget time, again, the fewer distractions, the better. So again, that was the reason for the 10-1 starting date. There won't be any salary change for this position for the rest of the year. So we're just sliding him into that position. So it's for this year. Make a motion. It's already passed. It's a resolution. It's a resolution. Oh, it's a discussion too. I'm just clarifying. Okay.  Thank you, Alderman Hammond. Yes, I just put it out. I know I mentioned that it did pass at the last council meeting, but I wanted to revisit it. It's to revisit it because of the further discussion we were having tonight. So there's no action on that. It's already passed. It's just for discussion. So where are we on the agenda here? We're number 20 to set the next meeting date and that's already posted for tonight, tomorrow night. Thursday, September 15th at 7.30 or immediately following the Festival Foods Open House. There are any other city committee meeting, city of Sheboygan committee meeting. There's a separate, Alderman, I mean, attorney, what's your name? I have a motion there, almost. Just clarify, during the recess, I checked the statutes on what vote it would require or what the number of electors it would require for a referendum and 7% of the votes cast at the last gubernatorial election. I think for the recall, it's 25% of the votes cast, so it's a lot smaller number. I also double-checked you can adopt a charter ordinance and have that before it takes effect, submit it to a referendum of the electorate and if the electorate approves it, then it becomes effective, so that that might be what you want it to consider doing. Thank you. Thank you. I'll entertain a motion to adjourn. So moved. Thank you. I have a motion and a second to adjourn. Thank you, everybody. Thank you. Let's get them around to it.


I think there's so much value in this that actually is not even environmental. Back in graduate school and in my doctoral studies, I got involved in a group of social psychologists looking at the value belief norm theory of environmentalism. And there's this kind of social psychological system that we explored and provided empirical support for on how you connect basic human values to environmental behaviors. And the key connective piece between values like egoism but also altruism and openness to change and traditional values to recycling vegetarianism supporting environmental policy is you both have to facilitate awareness of consequences, i.e. we need better information. But that's not enough, that's that kind of information deficit model we have. You also need attribution of responsibility and it's that combination that becomes the kernel of a new norm that helps people connect their basic human values to environmental behaviors. So we really started focusing on that, that is how does service learning serving a community who faces a problem potentially improve the attribution of responsibility and we think the mechanism is basic efficacy that is you not only have to believe an object you care about is under threat you have to believe that you can do something about it. So what serve things like service learning do and the applied research that I do with my students is it allows them to actually do the research themselves and begin to see that they can make a difference and then that in some cases will also lead to a norm that they have responsibility for applying their skills to a problem. So the value of this kind of work for the community and the students because both of them are now involved in the research that we do. So we have high school students out there taking samples and looking at air and noise pollution data and my students are out there doing it and it's that space where you combine the awareness of the condition or the consequences of these disparities along with the attribution responsibility is in that kind of alchemy if you will that will lead to more engagement hopefully you know support for changes and policies and also you know a desire to be a leader in a community fighting for those changes. You know as a professor one of the big rewards is to see my students succeeding and learning and in a way modeling what happened with me with my professors going all the way back to an undergraduate I had a group of professors and mentors who supported and mentored me but also challenged me to go out and take on the big environmental puzzles of the time and so at the time environmental justice was one of those today it's climate change but being able to help my students get into positions where they're taking on the environmental challenges that have to be taken on even as an undergraduate is a reward for me as a teacher and a mentor and we are social beings and we get more value out of helping others as well as helping ourselves and so that's a you know part of that reward kind of social psychology I think that is you know a big reason I do what I do I do what I do because there are voices that are not being represented in the conversation in the policy decisions in the political processes and so I'm committed in my research program and environmental justice to continue to do that.


As it is said that, camera doesn't matter as long as you have vision and skills. To an extent, it can be supported, but one needs a tool or a good camera to put the imagination in front of the people in the best way possible. Just like any other field, the photography field also believes in the more proficient you became at, the more specialized tools you need. So today in this video, we will introduce the basic equipment required to be a wildlife photographer. Welcome back to CreativeHut channel, an exclusive platform to know more about photography. For anyone who is passionate about wildlife and decided to do wildlife photography, the first question comes to the mind is, from where to start and which all gears should be there before starting the quest. Gears play a vital role in wildlife photography, but our gears can help in getting the best results. Usually, wildlife photographers need to invest additionally for the accessories, although the expense is more, but the outcome of the wildlife photographer manages it all. So here are some practical suggestions for you to select the appropriate gears. First is a comfortable camera, either half frame or full frame. Second is telephoto lens. To capture the animals and birds photography, the most recommended and flexible telephoto lens are 300mm and 600mm, while some of the affordable tele lens for wildlife photography are like that of Canon 100-400mm, Nikon 200-500mm and Sony 200-600mm. Third is macro lens, mostly used for macro photography like that of small insects, most recommended is Sony 90mm, Canon 100mm and Nikon 105mm. Fourth is wide angle lens. To compose the animal in a wide view in its natural habitat, wide angle lenses would help to get best results, such as 10-20mm, 14mm, 14-24mm and so on. And fifth is teleconverter, aka extender, which is placed in between the camera body and lens to increase the apparent focal length of the lens like that of 1.4x and 2x. And along with that one needs a tripod, binoculars, beanbag for stability, protection material for USL as well as for your gears, memory cards and battery grids, simple clothing that are camouflaged to nature, waterproof shoes and most importantly a sturdy bag which is suitable for all climatic conditions in order to protect your gears. So whether you are a wildlife photographer or a passionate upcoming photographer in this field, we need to realize that it is one of the toughest, craziest, creative, responsible and challenging and struggling fields. So take up the task with dedication and enthusiasm without harming other living species. As we need to rely on the same nature for our survival, so let your lenses see them, camera frame them and at last your heart and hand nourish them. Now you let us know what kind of difficulties you face when you shot for the wildlife photographer in the comment section. Till then stay tuned with us, subscribe our channel, click on the bell button for the notification of our latest videos. For photography courses, different specializations in photography, visit our website www.creativeheart.org and for more photography articles, tips, tricks, portfolio and much more, visit our official blog www.creativeheart.com. Feel free to like and share and to be with next time. Stay safe and healthy, bye bye.


Hey, my name is Michael Bennett, and I'm here to talk to you about the GPU accelerated machine learning with the OpenShift container platform I have Diane Fedorna here who's a principal software engineer at Red Hat who will be presenting the performance results from our ML Perf benchmark on this platform So we'll start with the talk about the introduction to the potential of AI and ML and then how GPUs can accelerate that We'll discuss OpenShift as an enterprise Kubernetes platform for AI workloads and how the Dell EMC ready stack provides a validated flexible solution to deploy OpenShift in your data center environment, and then we'll go over the results of ML Perf running on this environment So to start out talking about AI and machine learning artificial intelligence is a Big subject that encompasses many things of which machine learning is only a subset of what enables artificial intelligence artificial intelligence is also, you know driven with automation and being able to act on the predictions or the classifications that are made by these machine learning algorithms and Inside of machine learning. There's actually deep learning and neural networks, which are just the most state-of-the-art implementation of artificial intelligence today and so and and these neural networks just happen to be very fast to train and Inference on GPUs, so we'll talk about how the OpenShift platform enables some of that with Kubernetes Focusing a little bit more on the impact of AI though It's been said that if you don't have an AI strategy that you know, your business is going to fail that AI ops AI Marketing and AI risk compliance are all the types of things that are going to be able to be Automated and done with this artificial intelligence that can be faster than a human and more accurate for certain types of use cases and so the OpenShift platform is with GPUs acceleration is designed to speed up your adoption of the next three technologies to have the Infrastructure you need to power your AI applications and enable all your business to realize all of these benefits It's important to note that when we talk about building out artificial intelligence one of the reasons that Kubernetes is a great platform is because the actual code that is done to Train a neural network or perform inferences only a small part of the total number of components that are needed to have a machine learning and AI infrastructure You also need configuration management tools ways to collect the data and verify it as well as a serving infrastructure once your model has been trained and then ways to monitor that model for drift so that You can ensure that your inference results are accurate over time and so what we like to do in order to break down the process into a Journey that can have smaller steps is to first discover the problem that we're trying to solve with artificial intelligence And usually that's a business problem that we want to solve not an infrastructure Problem the infrastructure will just be used to run the solution And so after we have discovered our problem We will begin to explore what data we have that will help us to train a neural network to assist in Automating or supporting decisions for that business requirement and will analyze the ROI Then at that stage once we have all the data that we know will be useful for the model we can start running the model doing AB tests and Trying different neural network architectures until we land on something that is accurate and performant Which we evaluate in our findings and then finally we will operationalize the model by deploying it on serving infrastructure and promoting user adoption of the artificial intelligence backed service and so Bringing all this back to kubernetes. We enable it with this stack of what we call it NGC containers Which run on this red hat open-shift? Environment and then on finally underlying deli and see data-setter infrastructure And so that delivers you your containers your GPU acceleration as well as red hat Open-shift for enterprise kubernetes and then the NGC software stack from NVIDIA that is optimized for AI model development and training and includes all of the Latest SDKs like TensorFlow PyTorch and cafe inside of those different NGC software registry Now to talk a little bit about GPUs accelerating AI So with this slide what we're hoping to reference or what I'm we're getting across here is that again if Referring to that earlier presentation where ML code is only a small part of the problem even inside of the AI application You know a small amount of the code that is the convolutional the convolutions in your convolutional neural network and Things like that are Benefit from being able to be highly paralyzed and they often actually just represent a very small amount of the code But by moving them to the GPU you can see 10 15 times speed-ups Versus running the same part of the application code on the CPU So this is why it's useful to have this GPU accelerated open-shift environment a little more on how the NGC software optimizes your usage of NVIDIA GPUs on side of inside of kubernetes again, they have those NGC containers that contain the optimized SDKs and deep learning frameworks as well as helm charts to deploy Some solutions like how Clara healthcare? AI and other like tensorRT inference server different toolkits and then OEMC offers a wide range of NGC ready systems that are validated to Run these NGC containers in the most performant manner And then NVIDIA goes through the effort of making sure that these stay updated that they're designed to scale to multi GPU workloads out of the box and That they achieve state-of-the-art efficiency or accuracy or better for the models that they host inside of the NGC containers So this is an example of all the different software that goes inside of the NGC layer of the container architecture that we showed earlier You can see here that they have NVIDIA optimized versions of a Lot of the different popular deep learning frameworks that they package inside those containers for you and so we've talked about artificial intelligence and why GPUs and containers are a good choice for developing and hosting your artificial intelligence application and now I'm going to touch on the specific benefits of Red Hat OpenShift for your enterprise Kubernetes environment that's going to be running AI workloads So if we look at again that process of identifying the problem gathering data We want an entire platform to be able to do this on again the ML code only represents a small portion of this Stack which is the develop ML model. We still have to gather data deploy implement in apps But of course in order to do the ML model development and deployment will need The ML frameworks like TensorFlow as well as DevOps tooling like Selden to enable us to deploy those models into an environment where they can be reached at as an API endpoint We'll also need to tie in data sources that the model trains on or will be running inference operations against so we have to plum in those data sources and Then ideally, you know, we would want a platform that is self-service so that our developers can request new containers or pods on demand and Move things between development environments and production with minimal need to interact with operations teams Of course since artificial intelligence workloads benefit from GPU acceleration we would will want to make sure that our Platform has support for GPUs and that our data science teams can get access to them and Finally, you know the infrastructure that everything runs on which in our case is a Dell EMC ready stack for OpenShift with GPUs inside the servers And so, you know OpenShift provides all of these Through a couple different things. We'll talk about here one is Open Data Hub Which is an operator for deploying things like Kubeflow, Selden, Jupyter Notebooks and TensorFlow T There's the NVIDIA GPU operator which is responsible for going out and finding the GPU resources and in the systems and then There's also the different data sources that you'll need to plum in which in the OpenShift operator hub there's Deployment for many of these and then being a Kubernetes infrastructure you can deploy data sources via Helm charts also So talking about the Open Data Hub it is a Operator That Red Hat has for data science tools and deploying them on top of the OpenShift environment And so it if you're familiar with Kubeflow, you know, it it does services like that for data science workbench functionality, but it also enables Spark and TensorFlow deployments and then logging data to Prometheus and Grafana So it allows us to Deploy all those different components we saw in the earlier slide where the ML code was only a small part of it Open Data Hub ensures that we can not only run the ML code, but that we can have all the supporting services around it and So OpenShift is it's a trusted enterprise Kubernetes Red Hat puts a lot of effort into both upstream Kubernetes release, but then also taking the Kubernetes releases and hardening them and then making them production ready for OpenShift and Dell EMC works with Red Hat to Validate these OpenShift releases on Dell EMC hardware to ensure their customers have the best experience when they're running OpenShift on Dell and Red Hat's been the leading contributor to Kubernetes since day one Some of the benefits of using OpenShift for your Kubernetes platform are that it makes an it has an automated full stack installation they provide Ansible scripts as well as installer tooling for to enable deployment on HCI infrastructure like vSphere or public cloud instances and then they support auto scaling of the Resources like worker nodes inside of your Kubernetes environments And it's very easy to do updates with one click on the home page of your Kubernetes cluster manager Red Hat also has certified operators which are built with the operator framework and then certified through the OpenShift Operator certification at that point then they can go into the operator hub that is integrated into OpenShift 4 which you can see on the right is a portal right inside of the cluster manager to make it easy to Deploy these operators and they all have different levels of automation that when you drill into them They show you if it supports for example Automated lifecycle management or just automated deployment and scaling things like that So it's really cool. I enjoy knowing my operators are sort of finding going to work when I install them and then another benefit of Red Hat OpenShift for Kubernetes is Red Hat CoreOS that which is an immutable operating system with CoreOS all of the operating system images are managed by the machine operator and so The systems are an operating system configurations get handled with APIs and Configuration definitions and so you don't have to worry about mismatched settings inside of the hypervisor OS That are running your containers and things like that All right, and then right before we get into the ML perf benchmark results just a little bit about our Dell EMC ready stack for OpenShift So as I mentioned before we work very closely with Red Hat to validate the releases of OpenShift on Dell EMC hardware and we also Do scale testing with several racks of equipment to ensure that our reference architecture Will scale to any size deployment that customers desire The design is pre-validated in in the lab, but we create a lot of collateral that enables our systems engineers to customize and write size that ready stack for customer usage and you can find on info hub.delltechnologies.com a lot of Information of like for example the reference architecture design and deployment guides Some solution briefs and some videos and blogs talking about the benefits of OpenShift This kind of gives you a high-level overview of all of the pieces that have come together for to make this GPU Accelerated enterprise grade Kubernetes environment for artificial intelligence In the center, we have the Dell EMC ready stack hardware where we used three Powerajar 640s as manager nodes as well as Different GPU accelerated server options that we have With the DSS 8440 being a 10 GPU server for dense configurations and the C4140 Supporting four servers with NVLink Or for GPUs with NVLink, I'm sorry and then to manage the Identification of the appropriate workers with GPU resources and install the NVIDIA drivers Stack we have the NVIDIA GPU operator Inside of OpenShift and then finally on the right we have those NGC containers I mentioned as well as the OpenShift open data hub for deploying the different tooling required to build Artificial intelligence applications All right, and now I'm gonna hand it over to Diane to go over the ML perf benchmark results that we got when running on this cluster Michael gave us an introduction to the benefits of running AI ML models in OpenShift Using the Dell ready stack now We'll talk about the benchmarks we ran in the Dell AI innovation lab and how we monitored them We chose the ML perf benchmarks to validate our remits architecture because they are all open source They're created and supported by more than 40 industry and university research organizations And they're designed to help people choose the right ML infrastructure for their applications The models in ML perf are neural networks that train on publicly available data sets You can go to ML perf.org and download the benchmarks yourself and try them out Now we'll take a look at the lab set up. We had in the Dell technologies AI innovation Lab in Austin on the left you see the cluster system admin host which serves as a single entry point into the OpenShift cluster The OpenShift nodes on the right are in their own private subnet for security reasons You use the cluster system admin host to gain SSH access into the OpenShift nodes and to administer the cluster Next we have the bootstrap node which is Which is doing the setup of the cluster and after cluster setup is completed it can be added as an additional worker node Then we have three Dell R640 manager nodes, which are the control plane for the OpenShift cluster And we have on the right two worker nodes with GPU acceleration The C4140 with 4V100 GPUs was trained Was used for our training benchmarks and below that the Dell R740 with 1T4 was used for the inference benchmarks And now we'll talk a bit about Monitoring so this is how we monitor our monitored our benchmarks that we were running in the lab You can see the Dell cluster on the upper left running OpenShift Next you see the NVIDIA DCGM exporter that is installed by the NVIDIA GPU operator and exports the metrics from the worker nodes that have GPUs The DCGM exporter is continuously exporting metrics from the GPU worker nodes then the Prometheus time series database scrapes those metrics and puts them into a time series database and You can roll back and look at those Metrics later if you have a reason to because they are stored in a database And then we are continuously displaying those metrics on Grafana dashboards that we created so in this case I created this dashboard and Created the queries that we see But you can also download from Grafana.org you can download pre-created Dashboards that people like Grafana have created This is another dashboard that shows PCI sends and receives and the temperature of the GPUs So you can view that metrics like this and you can also see things that don't relate to the GPUs such as Iowax and The CPU usage Basically, these are some of the great things that are built into OpenShift that customers love because they can use these graphical interfaces to see What all their how all their resources across the cluster being used they can look at individual pods you can basically tailor this to report whatever you like and you can also Report metrics from your own applications and export them and have them scraped in the same manner Now we'll look at the system details For the cluster that we for the the worker node that we ran the training benchmarks on and So you see on the left column. We have the Dell C4 140 and This is the hardware and software stack that we had for that worker node on the right We have the NVIDIA DGX one comparator system that we Used to publish results to you know measure how well we were doing on on our OpenShift cluster, so both of these systems have a V100 GPUs the C4 140 has four V100s whereas the the DGX one has eight V100s So we'll explain how that's obviously going to affect our results and we will we will account for that then you notice that for the software stack the Dell system has an extra software layer that our comparator system did not have it is running OpenShift and Gives you all these added benefits and what we'll see in our results is that even that you've got this extra layer of software There's virtually no performance penalty That we paid because of that We ran a slightly different operating system. We ran Red Hat Core OS 4.3 on the Dell in the Dell lab and our comparator system was running Ubuntu in both cases. We used the PyTorch Version that is optimized for Nvidia GPUs and on down the line you see there's a slightly Different level of CUDA and CUDA driver that were used in the two systems and everything else was the same The exception of the fact that we have additional software running the entire time that we were benchmarking so that we could monitor Our performance so that we could go back and then tune those applications So now we'll talk about the ML perfect training benchmark itself And in terms of the types of applications that they focus on in this benchmark There are computer vision and natural language processing models in this benchmark So we train four models to or object detection models and two were natural language processing models Mask RCNN and SSD are object detection and GNMT and transformer are natural language processing Models So the public data sets are listed here as well That we use to train the models. So Cocoa is the common objects in context Dataset created by Microsoft and Cornell and it contains 300,000 more than 300,000 images that are that have objects in them that are labeled and For the translation benchmark the public data set we used was WMT Which is over 8 million sentence pairs in German and English that you use to train the model and These sentences were taken from newscasts and parliamentary proceedings. So These these public data sets are the way that you train the neural network and All of these benchmarks were donated by companies like Facebook and Google and they are used to solve real-world problems such as Google translate and applications like that. So along the bottom we have the timings that we received and we're gonna That we had in the lab Adele and we're gonna compare these timings to the published NVIDIA DGX1 results so These are our results and You can see that Okay, again, we need to remember that On the left we have the Dell system, which had half as many GPUs as the DGX1 that we're comparing to so you would expect The training time to take a little bit longer. So Lower is better for training times for neural networks because you want to train as quickly as we can so that your data scientists can get faster turnaround time and try different model settings and So We did really well on mask our CNN as you can see here on the far left the object detection benchmark and We also did extremely well on SSD We took us about twice as long and we had half as many GPUs So then going on to the translation benchmarks. They were slightly they are highly variable benchmarks We didn't do quite as well on these There's a random seed that's used to get these benchmarks started and that affects the number of epochs that The model takes to train So if we had run this benchmark more times, we feel that we could have gotten it down to about half as much or twice as much training time as the DGX1 So now we'll look at these we look at these Same numbers are only normalized per GPU and Again, you see like we did better for the mask our CNN did you know Equally well in the SSD and not quite as well in the GMT and the transfer from benchmarks When you look at it on a per GPU basis so now moving on the next set of benchmarks are the inference benchmarks and This is when you put your trained model to work you give it queries and it gives you results and You have a quality metric that you're aiming for you your benchmark fails if you don't meet that quality metric and All the benchmarks we ran of course did meet the quality metric and were successful so the MLPURP inference benchmarks have four possible scenarios Offline single stream server and multi stream We ran offline and and server because those are intended For Data center benchmarking the Single stream benchmark is intended for smartphones and the multi stream benchmark is intended for embedded systems So what happens here is you have something called low gen which generates an artificial load to run the benchmarks it sends queries to the model and in the case of the offline scenario it sells it sends all the queries in one big batch and then you get the answers all in one batch and in the case of the service scenario it uses a PIZON distribution to simulate the birthiness of queries coming in that are more Realistic to real-life situations So the MLPURP inference results that we are comparing to are from the MLPURP.org Website you see them off on the right here and all the published results for these benchmarks had ECC turned off error correction turned off So Turning ECC off does give you a performance improvement of 13.14 to 14.29 percent depending on the models in this group but the cons of turning off ECC are that single-bit memory errors would not be detected or corrected and Double-bit errors would not be reported so We decided to leave ECC on so that is going to slow Slow our results down a little bit, but any of our customers in the financial industry or the scientific computing community and any situation where safety is involved you would want this extra Level of security for your data and basically it's just cheap insurance that you you want to keep So we decided to leave ECC on but you want to keep that in mind when you're looking at the performance results that we Present because we're comparing it to a system where they turned ECC off So these are our results you can see that that these are the server results and In this case higher is better So we're doing inferencing we want to answer as many queries as we can as quickly as we can and We are comparing one T4 on the left with four T4s on the right The other difference between the left and the right is that on the left. We're running OpenShift and on the right the comparator numbers that we got from the mlpurp.org website They were not running They were not running OpenShift or any other container orchestration platform So we had an additional layer of software that they did not have So you can see that You know, it should take about They should be able to do about four times as many queries as we can and and that's about right So if you normalize The server benchmark per GPU, that's what you see here You see that it is about the same but we are off by a little bit and that can be accounted for By the fact that we turned ECC on we turned our error error correction on just for a little more data safety so That was the server results Now if you look at the offline results that we had Again Higher is better here And we're comparing one T4 to 4 T4s and you see something similar You get about four times as many inference answers when you have four T4s Just compared to our one T4 with OpenShift then if you normalize Per GPU You see that We we did about the same just the slight difference between you know three to 14% difference can be accounted for because of the difference in our memory correction setting so we got excellent results and Now back to Michael to wrap up. Thanks, Anne For that So just wrapping up. We have a couple of links here GPU accelerated machine learning with Red Hat OpenShift white paper that goes into more detail about these ML per benchmark and the ready stack that we use to run the solution We also have our design and deployment guides for the ready stack and Then a link to the AIML and OpenShift page by Red Hat as well as the NGC Program run by NVIDIA with those GPU optimized containers that we talked about Thanks everybody for taking the time to listen to our presentation today on GPU accelerated machine learning using Red Hat OpenShift