 as well as a copy of the balance, there's a book about it for a peer judging. One second, I'm going to double check and I put it in the right place. Okay, I think I'm ready, let me get my pending form. Yeah, yeah, that's all mine. Yeah, that's a separate. Apparently, she's taken it and she's done it. I see, okay, very good. Okay, so we have that. And in the paper. So it will advance, but then? Yeah, it should advance, yeah. We can double check. And providing some in line. It didn't work this fine before. Yeah. And we'll check that. Yeah. Yeah, microphone on. Okay, actually we need this. This is the one we're going to use. It's a little less awkward for me. Okay. I pulled my thumb. That's okay. Testing, we'll use it. Just a second. I know. Okay, so everyone should have a copy of the listing of the presenters for both the snapshots and the posters. As well as a copy of the poster judging ballot. Okay, so let me remind you and just go through the rules which will be the ones that we follow for all the sessions. This is the first session. So we start with this session which is the snapshots. They will be presented one after another. They're all in a list and basically each person in turn in order will come up. Notice that on this sheet the poster, list of poster presenters, there is a number. Okay, that's the number you would use when you're judging the poster, you're ranking them. They're all indicated by this number. When you go out to the posters after the snapshots, there's the posters which are posted in on this floor but toward the back. Each poster will have that same number on it. So that's how you keep track of the snapshot, connect that with the person connected to the poster. So we start with the poster, the snapshots, two minutes and then after that we'll all proceed out to that session, the poster session, walk around. Presenters, please stand by your posters to be ready to answer questions there. Okay, now let's talk again about the judging, the three criteria, scientific content, the actual poster layout display and presentation which is both the snapshot oral presentation here as well as the presenter's ability to respond to questions at their poster station. Let's talk a little bit about judging. Again, the faculty hands-on judges will comprise one panel and y'all who are the peers of the presenters will be the other set of judges. Let's focus on that. This is the ballot that you have as peer judges. Using that number, a numbering system according to this, you rank in order with first place, second place, third place, fourth place, fifth place. In order to mention, there's a poster judging, peer judging drawing. Once we collect all the ballots, we'll take one of those ballots, draw one of those for a 20 euro prize. That drawing is not going to happen today. It happens at the start of the next poster session, snapshot session. Next Tuesday, at this time, when we do the second session, to kick things off, we'll take the poster ballots of everyone who's voted and put their name down. We have to know who you are to give you your money if you happen to be drawn. We'll take and draw for that 20 euro prize. When you're judging, you're judging both 1, 2, 3, 4, 5, the top 5. The presentation here, snapshot, as well as the poster session. You don't mark it in here and then turn it in. You need to both listen to the presentations here as well as view the poster. When you've marked your, when you've completed your ranking, then Megan, who is our official UN election monitor, will take this official UN sanctioned election ballot box and walk around and you can ask your poster ballots in this box. So Megan's in the back, raise your hand. Megan will look for her, but that will happen later. Now, there was a question about how, there's three separate sessions. So what we do is we do select for every session, the top five in this session. But in the overall ranking, everybody, all sessions compete with each other. So there will be a selection for your ballots, the top five. Next Tuesday, you'll select five more. Next Thursday, five more. But all of those compete altogether for the sequence, the set of prizes. Is that into your question? Yes. Other questions about that? Mark. It should say, yeah, must be present to win. Okay. Yes. Yes. Thank you for pointing that out. If you're not here at the start of the next poster session and you judged and voted for this session, and we draw your name, you don't get the 20 euros. We keep drawing until the person, until we have a judge who's written their name, they cast a ballot, their name gets drawn and they have their ear. Okay. So that's an important point. Other questions? Yes. Are there some, sorry? Waits. We will let you decide, each judge will decide how they want to wait those. Okay. So you decide and try to be consistent, right? Use the same criteria today as Tuesday as Thursday. Okay. As long as you're consistent, then it will all work out. Other questions? Okay. Now, let's talk about the specifics. Yeah. Sorry. Okay. If you win the drawing today, are you still going to win the other two drawings? So first of all, you won't know if you won the drawing today because we're not drawing today. We're drawing next Tuesday. Okay. So if you keep voting as a judge, you keep getting entered into the ballot, into the raffle, into the, so if you get drawn more than once, but here's the way we'll do it. Okay. So we typically have the past winners are the next drawers. So it'll look funny if you draw your name. It has happened, something such, such thing has happened where the person drew their name a few years ago, but it's, you'll be able to see the drawing happening here. We mix it up, person reaches in, follows, pulls out a name. Yep. So you keep getting, you continue to be eligible. Other questions? Okay. Now, let's talk about the specifics of how we're going to run, run this. Okay. So this is, so the snapshots, we're going to go ahead and start. So in turn, each person will come forward. You have your listing. You know your number. So Bruce is going to present the, yes, why don't you pull those up? Okay. So this will look something. So every snapshot will start with this, right? Your number, the number. So judges have that in mind. The number comes before the presentation. So you know in which order. So that also is a clue to you who are the presenters that yes, you need to come up and according to this schedule in this order. Okay. I will put on a microphone. So we need to have a microphone so it can be heard. So I'll hand you a clip this on and hand you this. We have also a laser pointer that you can use. So the top button is a laser pointer. You can also choose to advance the slide. So I'm just going to do this once. And so there's a advanced button here. But if that's, you're too nervous to do that. Just focus on the laser pointer and Bruce will advance it for you. Okay. So you decide how you want to do this. Okay. Note everybody who put a thank you slide, that does not exist. No. Don't click for your thank. Oh my slide says thank you. Those are all gone. And we'll, we'll hold the applause to the end because we have eight or 17 of these we're going to run through. So we'll have the applause at the end. Okay. After I clip on the microphone, hand you your laser pointer. I will announce introduce you. So wait for that. Okay. Don't launch into it. Okay. I'll introduce you and then you can deliver your snapshot. Now one final thing. We are going to time. Here's the timer. Pull the timer up here. So we can see it. Computer. Yes. Fighting. Yes. There's the timer. Very clear. It went down. It went down. Okay. We'll bring it out. No. What do you mean? No. It disappeared. Oh. Yeah. It's there. Okay. Good. So there's the timer. So you can see your presentation. You can see how much time you have. There will be an audible signal when your time is out. That's it. We'll see what that audible signal is. Okay. All right. Any questions? You will see that it won't be possible to do that. Don't worry. Yes. We have two minutes for everybody. Two minutes. So it keeps it there for everyone. Don't follow the example of a number of our session leaders who ran over. And I devote missionary days. We're keeping to a very strict two-minute time with it. Okay. That one's incredible. Any other questions? Let's go ahead and get started. Nirmal. Check. Can you hear me? The presenter is Nirmal Narajan. Not Narajan. Not Narajan. Thank you. Institute of Technology in India. And he'll tell us about his work, which is entitled Popological Characterization of Time Series Data Using Network Grass. So it's fantastic to see you all for my talk. And I'll jump into the talk straight away. We all love Fourier transforms and FFT to analyze our time series data. The reason is if you have a nice signal, you can pick out your signal from the nice. And you know this is the signal if it is periodic. But you are in a trap if you have a chaotic or an intermittent solution. And we could use a method which will map time series into networks and a method which I'm going to use is called the visibility algorithm. What it does is that you can represent the time series as a stack plot or a candlestick plot, connect the peaks if it has a line of sight. If this and this is not in the line of sight, there is no connection. But this and this is having a connection, so you connect it. And you can display it in any grid you like. So further, I can ask what I can learn by constructing it into a network. Now, you can see that connections can be of two or three types. One is you have a three-node network, a subnetwork connected to a two-node subnetwork which has a common vertex. And this is a lower topological level compared to this which has a common link which is at a higher topological level. And it so happens that for periodic orbits, I have more number of lower topological level connections than that of the chaotic and intermittent stuff. Just the opposite happens for chaotic and intermittent time series data which has more number of such data. And this offers better way to analyze things rather than the common network analyzers. So visit question number one. Thank you. Our second poster presenter is Samuel Hidalgo, who is from the Benning Marita University of Mexico, and he will tell us about his work on determining the stable life-frost state of liquids in chronic ovals. Hello, everybody. Today I will tell you about the layman-frost phenomenon in conical plates. So I will start by a little explanation of this well-known effect, which I picked for example when we are cooking and we drop a little amount of liquid over a preheated substrate. Normally we see that the liquid boils fast, but what happens if we increase the temperature of the substrate? Well, what we'll see is that the liquid doesn't boil any more, but levitates on its own vapor avoiding the direct contact with the substrate. So it's evaporating slowly, and this is pretty amazing because we are heating more than before. So the main problem is that this phenomenon has been studied a lot only on flat surfaces, but for a large number of applications, such as storing liquid that were preheated before, we can find conical shapes. So in order to explain this phenomenon on conical shapes, we have made the analysis of the equilibrium between surface tension forces against gravity. We arrived to a system of nonlinear differential equations. We solved it numerically. By the way, we can find different regimes. For example, on the top of this picture, we have the one with bubbles. Then the second is the oscillating patterns that appear. And finally, the quasi-stable regime. From the experiments, we have plotted a phase diagram. And finally, we studied the quasi-stable regime. To do that, we consider the heat transfer from the plate, by conduction. And the quasi-stable vapor flow below the drop. We arrived to these equations, and we solved it numerically also. The results are pretty close from the reality. Anyway, we obtained many other interesting results. That is why I invite you to see my poster today. Thank you very much. Okay. I'm neuroscientist. We study brain, the most complex system in the world. Today, we are able to measure the connectivity between neurons. And here the question is that, is there any geometric structure behind these measurements? Can we embed neurons in a Euclidean space or not? Putting this measurements in a matrix, that colors represent the value of the connections, we can assign a set of graphs to this matrix. Just by doing this, taking the biggest element here and connecting the row and columns there in the graph and adding the next biggest element. And here we can have a set of graphs that just depend on the order of the elements of the matrix. We have a phenomenon in social sciences, that is a friend of my friend should be my friend, and enemy of my enemy also should be my friend. By this idea, we can have a graph that has these four kind of triangles that these two are okay with the row, and these two are not okay. Here we can define a global energy for whole graph, that is the count of number of this minus the number of all these. Combining these two, we can measure the energy for each graph in that set, and here we have these two curves that randoms are distinguished from the structural matrix and we can distinguish them. Here we also can have some idea about the dimensionality of the origin of the space that we can put in neurons. And also this method is general. We can apply it whenever we have a coupling matrix and we want to do geometry of that. Better than my test. Two more seconds because the technical difficulties have finished. Go ahead. One more second. Oh, that's okay. You're good. If you don't, if you click in it doesn't advance weight before you click in it. Don't keep pinching your head. Some of your PDFs are big. I don't know how to put in your pocket. Oh, I'm so nervous. Are you okay? I'm a laser pointer in advance. Yeah, okay. Testimentano. Testimentano. Okay, last but not least. Fourth poster presenter is Viorica Tonu from the Nikolai Testimentano. Testimentano. State University of Medicine and Pharmacy in Moldova. And she'll tell us about her work on nonlinear effects of electron lattice interactions in superconductivity. And we need to be set to class. That was really good. Fast, no. Yeah. Hello everybody. Superconductors, materials that have no resistance to the electrical flow, they do great frontiers to end the discovery of the science. Some example of the superconductors are levitation, magnetic resonance, imaging, or even the large Hadron collider. In contents, the matter of physics, Cooper pair is a pair of electrons that are bound together at low temperatures and they are described by Barton Cooper Schieffer's theory. A pair of electrons have a lower energy than the Fermi energy and that makes them to be bound together. In semiconductors, these electrons interact with each other by photons, so this is an electron-photon interaction. And my work or my paperwork aims to research the big quantum interaction between electrons and to be compared with the single quantum interaction in the traditional Barton Cooper Schieffer theory. As a result, we achieved a maximum value of the water parameter in dependency of the temperature and at low temperature, the water parameter increase achieves a maximum and then slowly decrease to a critical temperature and actually this slow decrease gives us a maximum value of the critical temperature bearing with the original superconductivity theory by Barton Cooper Schieffer. And for those who are interested in my area of research, please be welcome to join my poster. Thank you so much. Ebola is a disease with dead infectives which offer insights into disease control. Ebola virus disease is a very deadly virus. Actually, Ebola is the name of a river in Africa, the Democratic Republic of Congo, but I wonder if people will go there to have a swim now. That would be very unlikely. Ebola was a regional disease. The first outbreak was in 1976 and it affected mostly sub-Saharan African countries. But in 2014, this deadly virus changed, the dynamics of the disease changed totally because it now moves away from Africa, it was exported to the USA, the UK and even Italy. So it became a global problem at 2014 which was the most recent outbreak. What I did is to look at the total population at a given time and the total population is divided into six at a time. The first compartment there shows the population of the susceptible people to Ebola. Virtually everybody in the population will be susceptible initially. Then the second compartment is the population of the latently infected. The third compartment is the population of the infected that are free to move in the community. Then the IH which is the fourth one is the population of those who are hospitalized and ID the population of the dead that are not yet buried. And actually the dead people, those that died because of Ebola can actually still infect people and harm the population of the infected. If you look at my graph here, I have a forward verification the proportion of the infected people as against the production number. The production number is actually the average number of people one infected person can infect in his lifetime of infectiousness. When I come to my poster, I will tell you what bavocation means in epidemiology and some other wonderful results I have derived from this model. Thank you. In the name of God, hello everyone. Now I want to speak about a method to analyze cross-correlation of fluctuation. First, I speak a little about fractals. Fractals has only one scaling exponent. If you focus here, you can see similar shape. But multifractals have infinite number of scaling exponents. What is important in multifractality here is that if time series are multifractal you can extract all statistical information properties of them from this method like for a spectrum and the other. Here is some part of multifractal data and this is the result. The main part is to find a best polynomial can fit to your data that will not kill the fluctuation but kill the trend because this is a method to detrend your data and then analyze the fluctuation. We want to study the mutal information of two time series and with this method we put them in a universality class. Are they correlated or uncorrelated or anti-correlated maybe? It means that our fluctuation affects each other or not and it's not dependent on what kind of data do you study. Maybe it's sunspots and river flow maybe it's oil price and stock market and it's not dependent on dimension or more things else. Thanks for your attention. This poster is delivered by Sara Faradi from the Feshmahan University of Technology in Iran and she'll tell us about her work on limited resources established inter-agent cooperation on networks. Hello everybody. I try to describe here a model which happens to be very close to what we see in nature and that's about cooperation. You see cooperation is very abundant in nature and we see that every day but natural selection challenges it. It says that if an individual is strong enough it can survive in the environment and now the question is if you're strong enough to survive why should you cooperate to others and why should you help others but if cooperation exists our models should describe it. Now this model, limited resource model happens to be very close to cooperation. You see you can assign a resource to every individual and you can consider it as the money that you all have in your pocket. You can spend your money and you can share it with the others and probably without money you'll die. That's exactly happens here. You see in a series of interactions resources can be changed to be the matrix something like this and the result will be a stable state in which cooperation can happily live together. But this has done on a homogeneous population which is not very realistic because mere populations do have structures. I try to challenge this model by adding a structure to it and I try to study about the aspects that can be changed by adding this structure. If you're interested I can describe the model in details and the results and with this brief summary I'll end here. Thank you for listening. Okay. Looking around you can see a lot of devices that work in bilateral frequency transmission. Did you ask yourself if this energy is dangerous for us? We will divide these opinions into groups. Someone will tell that it's dangerous, someone will tell that it's not dangerous for a living mother. Our question was what is the maximal value of electric field in a normal city from Europe? We have city Baku from Romania. Here you can see the streets and we measurement the electric field in 1600 points using the portable dosimeter. So green colors you can see the lower intensity of electric field, yellow colors that means higher and red one it's much higher intensity of electric field. What we found out is that maximal value of electric field is 2.2 volt per meter if we compare it with legal norm that is 27 volt per meter. But the maximal value of electric field in the city is for band GSM. That's what we developed. These results we will use in the lab to treat the plants but at the same time treating these plants with chemicals. And then we will see the result. Thank you. The ninth poster is to be delivered by Mohamed Amini Azawi from Mohamed's 5th University in Morocco. He will tell us about his work including the contour of presence shaped dunes using an active shaped model. Dear faculty members, dear fellow students, thank you for looking at my presentation here which is about these beautiful shaped sand dunes that specialists geomorphologists call barhand dunes. My work is about monitoring these dunes which are in the Sahara Desert and as you will see in other places and I use an icon of satellite to track their positions and their shapes along the time. Of course these dunes can also be found in other planetary landforms as in Mars. We will get back to this later. Actually these dunes can be a threat to human activity. They can cover roads, they can cover agricultural areas and they generally could be a hazard for any human activity or settlement. These are the fastest sand dunes and as you can see here we can characterize them by three main curves. In red it's called the foot, the green one is called the crest and the blue one is called the avalanche and in white arrows you have the wind direction. So it's important to know how they will progress along time and also to... they could be something which is important to monitor surface wind activity in other planetary landforms. In my recent work I have developed a model to get the surface wind activity in Mars using the shape of these bar hand dunes. My work will be about an active shape model which is a computer vision model that gets the control of these dunes and I invite you to be at my poster to know much more about the details. Thank you. So hello everyone. Excuse me. We'll be presented by a very eager Shumalia Kamrat from the Komsats Institute of Information Technology in Pakistan and she'll tell us about her work on efficient transfer and imaging of graphing grains on dielectric substrates. So hello everyone. As we know, single layer graphene has zero band gap so we cannot use it for switching devices, faster switching devices. So attention is diverted towards multi-layer graphene where you can tune the band gap and also it has multiplicative effect so it has applications in optoelectronics. So we grow multi-layer graphene in a chemical vapor deposition on metal catalyst, platinum. Sorry. And then we deposited PMMA on graphene deposited platinum and put it in electrolyte exclusion during electrolysis. This platinum coated graphene electrode was used as a cathode so hydrogen bubble moved towards this cathode and peeled off graphene layer. After peeling off this graphene layer, we scoop it out on the dielectric substrate and with the optical images we find out that potassium hydroxide and lithium hydroxide are more efficient in transfer and gave us very larger area coverage as compared to barium hydroxide and sodium hydroxide. So after transfer we also tried to find out what happened even when two graphene crystals are in the process of merging which was overlooked previously and it is not possible to find out only with the help of optical microscopy so we used Raman imaging Raman mapping to find out the stacking sequence inside the multi-layer of carbon and also the number of layers. It is very important from application point of view device point of view. So I am presenting poster number 10 and welcome to attend my poster. Thank you so much. Hello everyone. We are actually studying the polycrystalline material under applied shear. So first let me explain what actually mean by polycrystalline material. So for example you can take a real polycrystalline material from nature this is a piece of metal and if you want to know the actual internal structure it will be like that. It is a snapshot means it is a schematic snapshot of this material internal structure. Here you can see the different color portions these different color portions are representing different grains or different crystallites. What we have done? We have done the snapshot of this kind of polycrystalline material and we have applied shear. And now we are interested in measuring the size means the size of this grains. Because the grains is distribution of this kind of polycrystalline material you can relate this thing with the strength of the material. It is important because it is of some fundamental interest and it is some application in industry also. So it is a completely numerical study. So we have used phase fill crystal methodology to simulate the polycrystalline material. And we have used means we have actually designed a new methodology to count the grain size distribution more accurately than the available methods. And we have also studied the system for different applied strain rate. And for that as a result we have gotten different strain rate probability distribution when you have plotted it in reduced area and we have found a power law distribution which is completely different from the distribution in the equilibrium state means when there is no such kind of applied shear rate. So this is a new thing and this is the starting point of starting points to study connection between the applied shear rate the strength of the material and the grain size distribution. So I welcome you all to attend the poster session to know more about this thing. Thank you. Yeah, yeah, I know, I know. Thank you, sir. Good afternoon everybody. My work is on painting of three-dimensional chemical waves which is commonly known as straws in the realm of non-linear dynamics. So this work is basically important because of their biological relevance. We know that when straw waves are present in the heart it may lead to some irregular heart beats which is called cardiac arrhythmia and this condition is extremely dangerous and often life-threatening. So what is a straw wave? It is just the three-dimensional counterpart of a spiral. It has finite lifetime and it rotates around one-dimensional curve called a filament. So what happens if some heterogeneity is present in the medium, then the straw wave can get attached to the heterogeneities giving rise to some stationary signals which have elongated lifetime. So if some closed loops are formed as a result of this painting, then it may have even finite, infinite lifetime and it is really dangerous for our cardiac health. So we try to see what happens if the heterogeneity is very large and we used the values of nuclear reaction for our experiments and used a hexagonal mesh as obstacle. Then we found that pinning may occur giving rise to filaments of different geometries and the final shape of the filament depends on the initial waveform. As you can see here these two waveforms initial conditions are look similar shape but different sizes and the final filaments are totally different. This wave period distribution curve indicates that the wave periods are function of symmetries of the final filament shape and finally we carried out numerical simulations using the simple Bartley model and found that it totally agrees with our experimental findings and explains how the filament evolves with time. Thank you very much. If you say Mastun... If you say Mastun... I mean... Yes Wilkins Delibered by Sayeddy Bussavi from Wilkins University in Turkey and she'll tell us about her work on optical reflectance trapping with low numerical aperture lens. Thank you. As most of you know optical twizzle are established technique for trapping and manipulation of particle from non-auto micro-escape and apply to study different area of science such as biological science, colloidal science to observe the forces and dynamic interaction between them. In the simplest case, optical tweezers are generated by using a focusing a laser beam by high numerical aperture objective lenses, and three-dimensional trapping can be achieved. But in the case of low numerical aperture objective lens, only two-dimensional trapping can be obtained, because in the axial direction, scattering force overcome the gradient force, and just two-dimensional trapping we will have. Another technique that we propose to for trapping the particle with low numerical aperture objective is using a mirror in front of the focusing a laser beam. Ray is focused using a low numerical aperture objective, scattered by a spherical particle, and then this scattered ray are reflected from the mirror. This reflected ray can exert an additional force on a particle, which enhance the trapping strength and cause the particle to push the particle to equilibrium position. We show that in some condition, the trapping strength can also be the low numerical aperture objective in presence of mirror can be even larger than the strength with a high numerical aperture optical trap. This technique can be... OK, it's finished. Hi everybody, I'm going to talk about interesting phenomena of spreading and figuring the stability of surfactant droplets. First, maybe I should say that surfactants are kind of material which can lower the surface tension. Imagine we have a droplet of surfactant with surface tension sigma 1 and a liquid layer with surface tension sigma 2. If sigma 1 is smaller than sigma 2, the droplet can spread on the surface. We say that Marangoni is spreading. The interface of two liqueurs, I mean the droplet and the layer, are not uniform because we have fluctuations. So different parts of the interface will feel different amount of surface tension gradient and consequently they will grow differently. It makes such a beautiful pattern we say fingering instability. Here you see fingering instability on kind of polymer, but actually I like to work on fingering instability of surfactant on thick water layers. Here you see spreading and fingering instability on thick water layers. I have done many experiments on this and here just one result. If we measure the radius of the inscribed circle inside the pattern, we see a power loop we have here with the power around 0.4. I have a lot of other results and it's a great pleasure for me if you come and see my results and also my poster and ask a lot of questions. Thank you. And Kano. The pleasure pointer at the top. Okay, thank you. Good team will be delivered by Alejandro DeLoria Kano from the Universidad de Los Andes in Venezuela. He will tell us about his work on how chimeras and clusters emerge in 1D maps with robot panels. Hello, everyone. The name chimera, it's from this mythological animal that it's composed by parts of different animals. In dynamical system, means that if you have a system that system can be divided into different groups. One order group or synchronize it and another disorder group. Cluster, on the other hand, clustering states may occur when the system splits in different order groups but there's no incoherence on the system. And in the natural world we can see many phenomenon that may be related to these synchronization states for example the dolphin to avoid getting drowned he sleeps with part of his brain synchronize it and the other part became keeps incoherent. But the model I'm using it's way, way more simpler than the dolphin. It's just a chaotic map, one demap that presents robust chaos. Here's the robust chaos. There's no periodic window. So when you couple these elements you can see that they've developed these cool patterns. For example, this is disorder state. This is the chimera or the partially ordered just a part of the system became ordered and this is the clustering when you have two order groups and as far as we know this is the first report of a chimera with two ordered groups or two-headed chimera, I don't know he has two ordered groups and the clustering I thought. So one... Question number 16 will be delivered by Divas Mehta from the Indian Institute of Science in Mangalore, India and she'll tell us about her work on crumbling of colloidal membranes Good afternoon everybody. The title of my poster is Crumbling of Colloidal Membranes on Solidification. So the system that I work on is a mixture of non-absorbent polymers which are marked in blue and we use rod-shaped viruses which are highly flexible semi-flexible and highly charged as our colloidal rods. So when we mix them together due to depletion attraction the rods align along their long axis to form what is called one-dimensional membranes called colloidal because they range from few microns to hundred of microns and here is the top view of this colloidal membrane under the microscope. Now recently we found out a new phase in this colloidal membrane system on changing some of the assembly conditions. Now I will show you the time sequence images of how this phase transition happens. So starting with we have a fluid membrane which is flat with a circular edge and then at some point the colliation sets in it grows and have faceted edges and when it grows further the local buckling within the membrane is more prominent and when this growing domain hits the membrane edge the local buckling disappears and the membrane takes up an overall curvature which is more prominent in this rendered confocal microscope image. Now why is this interesting? This is an example of a 2D crystallization which is fundamentally different from the 3D crystallization because of the finite source of boundary. You are welcome to my poster to know more about it. Thanks for your attention. This work presents a practical method to control chaotic systems where no previous knowledge of the mathematical model of the system is required. The systems that are considering this work can be represented by this equation where x are the states of the systems y is the output signal of the system and u is the control input that we have to design but control event condition. To know how the control is realized we need to know what is event condition. An event condition in this work is when the signal output cross over the signal EC that is the average of the samples between two events. When this is secured there is an event. It is marked like this. So the control design is when this equation and the control acts in the system when an event occurs like a control by pulses. For this work this control was applied to KSS chaotic circuit proposed by Kears, Smith and Sprott and we obtain these results these satisfactory results because we obtain a periodic stable behavior of the states of the system. This one corresponds with the output of the signal and this one is the signal control of the system. That's all. Thank you.