So it's my pleasure to introduce Professor Harry Sweeney, who you've heard yesterday. Today you'll hear him again and he will give some words about how to write a paper. And Harry has written some of the clearest and most interesting papers that I've ever read. So although I've heard him talk about this a few times, I'm going to be moved to what he has today as well. Okay, so we're all involved in writing and it's worth thinking about how to communicate effectively. And want to make some suggestions in the next few minutes. Now this is different from proving theorems. This is one person's perspective on writing. There is no rule book and there are no proofs of what works and what doesn't. But we all know that there are some papers and some talks which are better presented more readily accessible than others. And so I want to discuss some of the considerations making your work more accessible to a larger audience. Here are some typical numbers. They're just, they're no exact numbers. It's hard to get figures but in some journals they publish information on the number of people who hit on the title of a paper or download the abstract or download the full manuscript as a PDF. So you have some idea of numbers. In the five years after an article is published, the numbers are something like this. The precise numbers should be taken with a grain of salt but just to give an idea of the response to a paper you write and it appears in the literature that we write. You have in it certain key words. People are doing searches using Google Scholar, ISI, Web of Science, the archive and various other search engines looking for particular terms that relate to their own interests. And maybe 10,000 peruzers of the Web will find a, using their keyword search, your article will pop up. That's not untypical. That's a huge number. When you see that, you think, wow, a lot of people are going to read my article. Well, they read the title and then a few go ahead and read the abstract. The title has some words in it that they're not familiar with. The reader is not familiar with. They have jargon or some arcane terms. But they go to the abstract. Some find it interesting and proceed. And they read the abstract. They read the first sentence. And they have in their keyword search, using Google Scholar or some other search engine, they have turned up a list of 600 articles. So do they really want to read this paper? They start to read the abstract. And then out of these thousand readers, maybe one tenth will go ahead to look at the paper online. To just go beyond the abstract and to begin to look at the paper. Of those who look at the paper, maybe ultimately, if you're lucky, ten people will cite the paper. So you see there's a considerable fall-off in numbers here from those who first see the title of your paper or some key words that are listed in your paper that match their own interest. And of this 10,000, one may be fortunate enough to have five years later ten people cited your paper. So we want to think about ways of increasing this number ten. Having a larger audience appreciate what great work you have done. So let's think about the title. The title just common sense to say it should describe what you've done. You want to have some key words in it that others interested in the topic would recognize and want to look further. In writing a paper, in writing a title, in writing an abstract, in writing a full paper, you want to write for the broadest audience possible. I don't mean water it down and write it in the way it would be presented on Fox News. I mean, write for a scientific audience, but using the, if possible, no jargon, minimal amount of jargon, and words that would mean something to a broader audience. Of course, broad has different meaning if your audience is going to be nature, which really is very broad, or the physical review section B, which is Condensed Matter Physics, a specialty journal that's in, say, the area of general relativity and some terms would be common to that audience, not more broadly commonly known in the scientific audience. Now, you see titles sometimes, especially in specialty journals, that go on 25 words, including some long chemical names and various terms that are unfamiliar. Try to be brief, try to be brief to the point. And as I said already, and we'll say many times, avoid jargon and acronyms. If you're in any field you're in, we'll have acronyms that are very commonly used. We use PIV in our experiment.  Particle image plus the loss symmetry. Well, if you do experiments with PIV, it's part of your everyday vocabulary. If you work on quantum field theory, it is not. So, if possible, avoid acronyms. There are few acronyms common enough that you might use. NASA, N-A-S-A, it's okay. You don't have to write out the National Aeronautics and Space Administration, but not many, not many such. So, now you have the paper. You have downloaded the paper, and you're going to read it. And I want to consider the order in which people read things. And I would like to have seven volunteers from the faculty, some of the people in the back and front, to write the order in which they read things. Well, if you pass out that side and you could pass out this side. So, this is a sheet in which you fill out for yourself the order in which you read things, and like 12 participants to fill this out. And by filling it out, I mean there is a number. One is the first thing we read. Two is the second, and three and so forth. And then you have different sections of a paper that are listed to the right, and you can put yours right up there on the board. Let's get some volunteers. Please come, would you go up and put your list on the board, please?  Need more volunteers just to get an idea? Okay. Yes, please, please come. Well, let's get 12 participants. Would you please? Okay. All right. How about you?  Yes, does everyone have a sheet? If you're not up there, you can fill out the sheet. Would you like to list the order in which you read a paper on the blackboard up there? Just pick one of those columns and complete it on the right side. Pick a column. Okay. So participants, sir? You want to come on this side? I just want to see if there's a difference in participants and the faculty. We need some more faculty. Where are the faculty? Bala. Yes, thank you for volunteering. Yes, over on the right side. On the left side, excuse me, your faculty and participants. There's plenty of columns over here. Yes, I see more here. You're on the right correct side. Sorry. All right. It's missing more thirds. Pardon? That is some more thirds. Are they your friends? Or your enemies? Exactly. Right. Okay. Does everyone have a sheet and filling it out? Done it? Okay. Let's see. You want to go up and then fill out? There's some empty columns there. We have several empty columns. We need some volunteers. Volunteer?  Yes, there's an empty column there. There's no grade given. Everyone can be a winner. No grades. You want to go up? There's still some columns that are empty. All right. Let's fill in as many columns as we can. You can go fill out one of the columns, please. Okay. Okay. Yes, you have a column there. All right. You've done it? Okay. All right. Good. Okay. So let's look here and see if some pattern emerges. There is no right order and wrong order. But what's interesting to think about when we write a paper, the order in which people read the paper. Okay. Thank you very much, all. So we see if we look at the first thing that people read is, in most cases, the abstract. Oops. Not everyone. Here's people who look at the figures. Look at the figures first. All right. Now let's see what's next. Does everyone read the introduction? That's B. Well, if we go across here, here's someone who reads the introduction. Remember, you wrote that paper and you worked days, weeks on that introduction because that would really set the stage for people understanding what you've written. But look, most people skip it. Right? Here's someone who reads the introduction. But there are a lot of people. Look at this. There seems to be a predominance of H's. Right? Those are figures. And if you look over the board here, does somebody have a cell phone camera or something? I'd like to have a record of this before it gets erased. I see lots of H's in the top part here. So people go straight to the figures. They read the title, they read the abstract, and they jump to the figures. Now let's see what is after H. There's one of G's too in the second row. G's. G's. G's. What is G? Conclusions. I would be one of the G's after looking at the figures. I would go to G's. Some people go directly from the abstract to the conclusions. And many who, after they've looked at the figures, then go to the G's. You see, G's would normally be low in the order of the material and the text, but you see G's are predominantly high on the list. People jump to the conclusions to see what the authors conclude is important in the work that they've written.  And I see some people get to, what is, references, and then forget about the rest. Some sections are unnecessary. You spent that time writing. There are people, maybe some of your friends, not anyone in this room, who would put really references up on the first line to see if their name is on the list, right? Okay. No one admitted that here. It means it's very important. It's important. It is. If someone doesn't find me, you'd be relevant. Yeah, well, it's clear. They're lack of understanding of what's important in the field. Yeah, they've demonstrated it. There's no need to read that paper. Okay. So the point is that when we write a paper, we think of people reading it in a serial manner, but that is not the way it's read. People jump around, and therefore when we write a paper, we should think in every section we write about making it as self-contained as we can, explaining terms, or giving reference to a table that has definitions. But if we just use a lot of terms in, say, the conclusions that we've used throughout the paper, well, if they've gotten to the conclusions, you might think the readers would understand exactly what you're talking about. But no, they haven't read anything else in the paper. They've just jumped to the conclusion section and you have all this terminology which they don't understand. And so what would they do next? They would put that paper aside and go to another one, right? They have a whole long list of papers that have come up in response to their search for key words. So why read a paper that can't understand clearly by just looking at the conclusions? What's concluded here? And so forth. So someone get a picture, photograph? Yeah, for references. All right. So what I learned from doing this and asking people was that no matter how much care you take in writing this beautiful manuscript there's written to be read line by line from the first word in that beautiful opening sentence all the way to the concluding sentence won't make sense to a lot of the readers because they've jumped from the first line or maybe from the abstract all the way to the conclusion. So let's talk about the abstract for a moment. Think about some of the things we might want to include in the abstract. We'll be writing abstracts today, the next few days. We'll have abstracts on the posters. You write abstracts for papers all the time. Abstracts are short. If it's some journals, there are a few sentences, three or four sentences. Other specialty journals are more often the abstract is longer, maybe eight or 12 sentences. Still it's important to state what is the problem you're addressing. And then very briefly, maybe even in the same first sentence, why is it interesting, many problems in science which aren't very interesting. Why is your problem interesting? And then you've done something. What did you do? Did you do calculations? Did you do some experiment with a new technique? Did you do some simulations? What was your approach? And most importantly, there in the abstract, you say, what have you learned that is new? What have you found? And given that you've stated what you have found, why is that interesting? Why is it remarkable? And how does it fit within the framework of past work? And what are the ramifications for the future? What are the implications? What further work needs to be done? What prior work was done with certain ideas in mind turned out based on your work not to be correct. What needs to be redone? What needs to be reconsidered? Now, there's no need to make notes on this because I have a handout which has all of this. Also, the same talk as every talk, including one Mark Shattuck gave this morning, is online. You can download it from the ICTB website. If you don't have the URL, we'll get it, distributes it to every lecture given by a share at the hands-on school, is online as a video together with slides. You see the individual. And then I have a little write-up in addition. Now, we saw, by consideration of the way people read papers, that figures are very important. We are, as people in a culture in the world, storytellers. Every picture, every figure should tell a story, to some extent a self-contained story. And it should be understood, it should be possible to understand it without referring a lot to the text. If at all possible, you should have it. So the figure together with a caption is a vignette, a short story of a larger story that the reader can understand without digging out definitions and without going through the detailed text because most readers won't. They will look at one figure, they don't understand it, they won't go to the text in order to understand it and their first read-through of the paper or perusal of the paper, they'll go to the next figure. And if they understand that, that's fine. But if they don't, they'll skip again to another figure and at some point they skip again to the next paper. They'll drop your paper and go on. The figures are not clear and relatively straightforward to understand. Maybe they have to put in some effort where the information that is critical is contained in the figure and in the caption. So the ideal figure is one that doesn't require you to even read the caption, much less the text. Sometimes you can have figures that are self-explanatory and interesting in themselves. For example, do you need a caption? Do you need a ten-page paper to describe the situation? Now there are a lot of people who have written guidelines for making figures, but one that I particularly like is a book by Edward Tufty entitled The Visual Display of Quantitative Information. And Professor Tufty or Dr. Tufty also goes around the world giving lectures on how to make figures, how to display data. I regularly get web announcements for $300 I can go hear him lecture or something. But the information by and large is in his book and the book is pretty widely available. But it can be summarized very briefly, not the whole story, but that when you make a figure you want the figure to show results, data. Not a lot of labels and great detail, not a lot of numbers on the ordinate and abscissa, but emphasize the data. So you look at the figure and the result of the data pops out. And that's what catches your eye. So you can make a graph with ten curves, one solid curve, one dash, one blue, one red, one with green triangles and so forth. And you make labels to explain all these differences, but it quickly becomes a quagmire and you move on. You want to make your point as simply as possible without a lot of curves and as far as a legend is concerned that little box over in the top right of the graph that has explanation of the twelve different symbols that are used, that's the kind of figure that people skip to the next one. Because you're trying to figure out which points go on which curve and at some point becomes tedious and you just move on. So now here's a graph by a very famous scientist, chemist, Linus Pauling, Nobel Laureate, and just everyone is familiar with Linus Pauling's work, and this was a graph he had in 1947. Now I want you to think about how given what was said by Tufty, guidelines of Tufty, how can this graph be improved? So pair up with your neighbor and talk about, I think there are probably ten ways that this graph can be improved. Same information, same data points, no new data points, but make this graph communicate better to the reader more eloquently, more succinctly. So they look at the graph and some information about the science pops out. Okay, we'll take two or three minutes, talk to your neighbor, list how many things would you change in this graph? Everyone should be able to list at least six things to improve this graph. If you're not sitting next to someone, move next to them. You want to go sit next to someone there? Yeah. Make a list. Yeah. Okay, make your list of things that you would change. Okay, so let's get some suggestions of things that Nobel laureate, Linus Pauling, overlooked. He should have known better. But you do know better, right? Yes, sir? Yes. The plus signs add nothing, and that's a response also to the admonition of Edward Tuft, maximize the ratio of data ink to other ink. That other ink in those plus signs adds no information. Right? Yeah. Okay? That would be a first step. Very good. Someone else. Yes, sir? Use colors. Well, in 1947, that wasn't so. But what would you color? What would you color? Pardon? I mean, you can make it look prettier in the artistic sense, but what way could you use color to add information for the reader, to make it more accessible, make the figure more accessible to the reader? Yes. Say it again? Instead of dash lines, use smooth curves? Yes. I don't know why they're dash lines. Why not use smooth curves? Okay. That's reasonable. Dot and contrast between dot and dash. Okay. Yeah. You have the dots of the data point. That's the one thing we do not want to remove. Yes, sir? There are some different sets of points. But the result will be in the graph. Yeah. Okay. I don't have an answer. Why does this dash line not go up? It goes up here, but not on the left side. I don't know. Pardon? Do you see any relationship between the numbers identifying the peaks? Maybe you could put the numbers down next to the peak corresponding to the value of the atomic number at that peak. Okay. Maybe you could put the particular element corresponding to the peak. Good idea. Good idea. Yes? You can have four or five reference values and larger font on the axis as well. Right. You could have larger font and certainly could get rid of, say, all these odd ones, 10, 30, 50, 70, 90, or you could even maybe zero, 50, and 100. But certainly fewer numbers on the axis and the same on the ordinate. Right? Yes, sir. Why didn't he put units? That's a good point. You teach your students to put units, right? What's the volume? Here, this is a volume. What's the unit of that volume? I don't know what the unit is. I thought it might be cubic more radii, but it didn't work out. I don't know what the units are. Does anyone have an idea what the units might be? You should have put units, right? And as we said, in the horizontal axis, you could have fewer numbers, zero, 20, 40, 60, for example. And I would certainly, since it's to be read in an article, I would put the numbers horizontal so the reader is not doing like that to read the numbers. Here, it's pretty simple, but just as a matter of practice. Anything else? Yes, sir. Good. If you're reading in a journal or on a web page, most of the time now, we read on the monitor or a laptop or something. Why not make this horizontal? Put it up higher. Atomic volume. Agreed. Others. Yes, sir. Yes, there's no, like this extension here. What does that mean, that dash line there? I don't know. This dash line goes up here. Right. Okay. So, those are very good suggestions. And here is what Tufti did to improve. And we made some further suggestions, I think, are good, which Tufti didn't pick up on. But as was suggested, label the element that is the peak and you immediately recognize that these are the alkali metals, right, that are the peaks. And you have this section right here, which is different, the rare earths. And notice that he's gotten rid of the odd 30, 50, 70 here. He didn't put in, he didn't know what the units were either. A graph in unknown units. Sometimes people put arbitrary units, which is okay. Anything else we notice from this? It's so much cleaner. Yes, sir? He ignores the origin and he makes a point of that. You don't need the origin. Well, I haven't the disagree. I like to see where the zero is because sometimes people offset the origin from zero. But Tufti says you don't need that. Another thing that he emphasizes is you don't need the, oops, you don't need the side and the top. See this bar across? That's extra ink that doesn't add anything to the understanding of the data. I tend to put it aside in the top, but it's a reasonable point. It's more ink that is not contributing to the data. Okay. So this is a graph you can look at and immediately interpret. You learn something by seeing this graph. Okay. Now Tufti has an example of a graph which is not as good. Okay. Yes, he's rotated. Yes, but I still like the horizontal. I mean, this is often written, the axis label is often written vertically. Particularly if it's long and you have units after that, then it's necessary because you don't have the space out to the left. But you can frequently write it horizontally like this. Anything, any other comments about this graph? Ways to improve it? So let's go to the next graph and see what you learn from looking at this next graph. See if you can figure out what the author wanted to present here. Time is moving on so we're not going to spend much time. This is clearly junk graph, right? So let's get some suggestions of things that are wrong with this graph that you would, the labels, yes, are very tiny and you have 28, 29, what are these numbers representing? Age structure of college enrollment. So these students in the bottom part are under age 34. And these are the years 72 through 76. What about the color? How much have you learned by the color? Nothing. It's gratuitous cover. It adds color. It adds nothing, right? Now, do you see any similarity between the bottom and the top? They contain the same information. It's a reflection, right? There is no information there. So there's unnecessary three-dimensionality. Yeah, it's subtraction, OK. You're right. Well, and we've got this three-dimensionality which adds nothing. And we have numbers like this 28 connected to the 29 with this curve. It curves, and then there's a flat line. And then there's a curve and a flat line. But that's not based on any evidence. That's an artist's rendition making these flowing curves, right? The top certainly duplicates the information in the bottom. The fonts are too small, we said, and so forth. So let's think of ways this data, these same data, could be presented in a way more accessible quickly. And you could do it with a table. There are only five points, five coordinate pairs, right? Five pairs. So this is a percent of college students over age 35 through some period, these five data points. That's it. So you really don't need a graph. You could have a table or you could have a graph. One wants to have a graph. OK. Now, this is a nice image I like with a figure that was made by Paul Umbenauer. To make a graph, a nice graph takes time.  And the example I'm going to give here is this picture that was made more than 20 years ago when experimentalists used cameras with film, ectochrome film. And Paul Umbenauer, who took this picture, set up on a Monday morning to make this picture. And he spent the whole day Monday moving the lights around to take picture of this oscillating structure. I showed a movie that Mark Shattuck made that oscillates up and down. This is a snapshot in time.  And the lighting wasn't quite right the first day. In those days, we took photographs during the day, all day, and the camera shop closed at 5 p.m. If you got the roll of 36 exposure ectochrome film into the camera shop by 6 p.m., they would have it developed by 8 a.m. the next morning. So it goes by the camera shop the next day. And the pictures weren't so good. He did that five days. He spent a whole week obtaining that figure. But it's a nice figure, and it ended up on the cover of Nature and in the New York Times and in Scientific American, American Physical Society calendar in various places. You make a nice figure. I mean, this is an image, but also a nice graph. It will be reprinted by other people who find the information useful and illustrative. So we could talk about the graph itself, but it's simply enabled. And there is a more recent graph. It's not exactly following the guidelines of Tufti, but my colleague Michael Martyr made this and won some award for it because fracking, hydraulic fracturing is widely used in Texas and they want to know after the first yield, the first few months or first year, how much gas is going to come from this well. Can they predict? And in this analysis that Martyr and his student did there and colleague, he was able to take the data from 6,000 wells from this particular shale and he did it for other shales. He has 100,000 data points or so from different barnet shales, the different shales that are being explored these days and he found that within a short period of time he could predict with reasonable, with some uncertainty, with appropriate scaling and the key was the scaling, the long-term total yield of gas and that's used all over the petroleum industry now. Okay, now to writing. We're talking about papers where you do have to have writing but figures are very important and figures are easier to interpret than writing. The eye was developed after the great dinosaur disappearance in 65 billion years ago, then various species developed eyes, about 25 species including our ancestors, developed eyes that are similar to ours, similar in structure, so it's a very efficient kind of light detector, image detector. So 65 million years ago, that's millions of generations that the brain has had to interpret images. So we're very skilled in interpreting images. That's why one reason why figures are so important. We're much less skilled at interpreting symbols and making meaning of a set of symbols that is writing, which was developed relatively recently. 5,000 years ago, a short time in history by the Egyptians and Sumerians and even after it was developed, most people were not able to read. Even in 1850, just five generations or so ago, only 10% of the world could read. Most of us in this room including myself had ancestors at that time who were not able to read. So the development of the brain and interpreting the symbols that are read when we read a journal article is much less than the development to recognize that there is a bear behind you about to attack you. You've got the peripheral vision. You can see that bear. But interpreting symbols is much more difficult and that's why we look at figures. Most of us look at figures first. So only a few generations ago did people begin to read. Right, widely. Okay, any paper if it's scientific must be reproducible. That means it must have the information. I'll skip through this quickly, but it must have all of the information that is necessary for another person to reproduce the results. Otherwise it's not science. Right, if you do simulations and don't give the initial conditions on some nonlinear system like many of us study, then different initial conditions can lead you to different attractors, different behavior. If you have a theoretical analysis and you make certain assumptions and approximations and recently we were reading a paper we could not understand. We read it for months. There was a change of variables that used the new variables used the same symbols as the older one. And one of my colleagues, Philip Morrison, after looking at the paper the multiple times realized there is a change of variables between that line and the equation that followed from that line in the next. And the author never stated that. The work must be reproducible. If you have detailed sample preparation you have to describe what was done. References are important. American Physical Society has made a statement about it and I think I ascribe to this 100%. Omission of a partner author or reference is unethical and unacceptable. We all have access to Google and we can find the relevant articles. If a person is written on the same subject but you don't like their work or you've had a conflict with that person that does not mean that does not give you permission to omit them as a reference. Full referencing is the ethical and required. Oh, yeah, and you should reference other works. Here's an example that I showed before. And we were surprised to see the cover of this magazine, a journal every month, has a picture that looks rather similar. It's grayscale, not color, and it's been flipped over. See the two particles there? But no one ever asked us for permission to use that. So, now I'll skip this. I think there's far too much emphasis on journal impact factor. Journal impact factor is based on the citations in the first two years, but for most articles, typical article, 6% of the citations over the long term are in the first two years. The papers that we, some of the papers our group has had only a few citations in the first two years and a couple of papers that I had mentioned yesterday in a talk have thousands of citations, one of them 4,000 and another 2,000 citations. But the citations didn't come until a decade later, or even later. You take Einstein's papers in 1905, the famous series of paper. There are very few citations to those for a long time. It took a while for people to appreciate something. It was different from what they know. Now, if you publish a paper on cancer, a new cure for cancer, you'll immediately, in nature, and it's a cover article, you'll immediately get a huge number of citations. There's a large body of scientists working in the field, and it's of interest to many people and be rapidly cited, and maybe not much later. But many times, work that is really innovated is not innovative, is not cited very much in the first few years. That's just a couple of reasons why I think impact factors no significance. I'm not concerned about impact factors. So I'm through. The most important thing is to write and rewrite and rewrite. Ask others to critique your manuscript. Read a text aloud yourself or read it to a friend or get them to read it. When you read it aloud, you pick up errors and ambiguous expressions. Transitions from one paragraph to the next, which make no sense. And lastly, you should cut extraneous material. You spent six months working on an aspect of the experiment that didn't pan out or it turned out to be a blind alley. All that effort, you feel like you have to say it? No, you don't. Cut it out. Make the paper as safe as you can. So writing the paper is not something, a good paper is not something that you do quickly. It takes time. It is really, I feel, an integral part of the research. In writing a paper, you find, or at least I find, that some of our arguments have holes in them. Some results we present are incomplete. You learn a lot from the writing process and it takes time. It's important to start early putting together the paper thinking about the story. Come back to we're storytellers, a paper should be a story. It should unfold like a novel unfolds and at the end you have this beautiful result. Thank you.


What's up, everybody? Ricky Caruth here. Look, today I want to talk about the coronavirus, its effect on the real estate market, and what you need to be doing right now until this is over. And check out all these Remake signs I got to throw away. Horrible, isn't it? So I just did a walk-through on a condo. We're closing tomorrow $500,000. I got both sides of that. I'm closing another one Wednesday. Friday I did the video on the one that almost got away, the $90,000 commission, where the buyer almost walked away over the coronavirus. But we did close it. I'm going to do a video tomorrow when I pick that check up. Now, I've been getting all kinds of messages from you guys saying, should we circle prospect during this coronavirus scare? All the schools are shut down. A lot of businesses are shut down. People are just staying home. Should we circle prospect? Should we continue going on with business as normal? And the answer is yes. Look, here's the thing. The coronavirus may cause real estate to slow down. It might not. We don't know what's going to happen. Prices could adjust. Prices could go down. If prices go down at all, houses and condos and property is going to be so easy to sell. If prices go down at all, condos, houses, land, it's all going to be so easy to sell because there's so many people on the sidelines waiting for prices to go down. So please do not be scared of this. If it does get bad enough where prices go down and adjust, that's going to make it easier for us to sell these properties. This reminds me of 2010 when the BPOL spill hit and everybody got so scared. And I remember telling the agents in my office, just stay calm, continue calling your clients, calling new property owners, telling them what's going on and helping them through whatever it is that they want to do during this crisis. So either way it goes here. If the coronavirus flattens out and the market gets back to normal, great. If it affects the market in an incredibly negative way, that's okay too because prices will adjust to the price that people will continue to buy. Let me tell you, people have a lot of money. There's still a lot of cash on the sideline.  Now as far as circle prospecting, we're going to still continue to call. We're looking to build relationships, see what we can do to help people. We're going to say, hey Mr. Johnson, hey Mr. Johnson, this is Ricky Kruth, the local real estate agent. How are you doing today? Good, me too. I'm just staying inside trying to stay away from all this craziness out there. It's nuts, isn't it? See, that's how I would adjust my script. And it doesn't have to be exactly like that. But we're going to adjust my circle prospecting script found at zero-to-diamond.com to fit the current situation to have that conversation in a low pressure manner.  We're not going to talk about real estate in the beginning. And then we're going to slide right into real estate. Hey, well look, I don't want to take up too much of your time, but a house around the corner just sold from you didn't know if there's anything in the world I could do for you. See how easy that is? See, you can take the circle prospecting script and alter it to whatever's going on in the market, in the world. Whatever's happening, you can adjust the script to whatever it is and you can continue to make calls and build the relationships that you need to build your business. So the main thing today is I don't want you guys to freak out. I want you to stay busy. If you're quarantined and you're at the house and you can't leave, make calls. This is a great time to make calls. Everybody's at home. They have nothing to do except re-answer the phone and talk to you about the real estate market. So stay on the phone. This is when you gobble up so much market share. When all the other agents are freaking out and not doing anything, they don't know what to do. This is when we make our calls and we meet more property owners who will do business with us now or later. I hope that helps. Hit that thumbs up. Click that subscribe. Shoot me a comment. Let me know what you think. And I'll see you guys tomorrow. Tune in as I pick up the largest single check that I've ever picked up in my life. Let's go!


At the media event a little bit earlier this week we got a preview of MacPaw's Hyder 2 and now we're in the booth with Philip Struchkov. I gave it my best shot. I told you I might not get it right but I would try. So tell us about MacPaw and Hyder 2. So MacPaw, we're a Ukrainian software development company. We developed Mac application for already six years. Our main protocol clean my Mac 2. We released it last year in Macworld. Then we also have Gemini as a duplicate finder. The application which lets you find and remove duplicates from your Mac and here's our third application called Hyder 2. It lets you hide and creep files and folder on your Mac so no one will be able to find them or access them on your Mac so it's completely secure. So this is for the example of you're coming across I don't know the Canadian border. I think they like to open up your Mac and look at stuff. They just simply wouldn't realize those files are there. Yeah sure you won't be able to find it in finder, spotlight or even terminal. Okay so is it using any of the built-in tools of OS 10 that you can do? I mean I think you can do this sort of thing through the terminal right? Yeah you can do but it's still so don't know these files will be able to find them. Okay all right so we're gonna do a little demo here and we'll hopefully be able to describe it for the listening audience as well. Okay sure. So the app itself is password protected. In order to unlock the app you need to enter your password. It's got a really cool combo lock fake combo lock on it that looks really cool. Yeah so once you unlock the app you get the list of files and folders which you have hidden with Hyder. In order to add another file you can simply drag the file under the application window and then file will be the file will disappear from its original location and will be moved to our secure vault. So you won't be able to find this file through spotlight file for example go to spotlight type in the file name and we won't see the file which I just hidden. It also works the same way with folders so you can just drag the folder and it will disappear from its original location. If you need to unhide the file or folder you simply click the button to unhide it and the files are back at their original locations. So do they actually physically move location? Yeah they do actually physically change the location because we are copying our files into our internal library and encrypting them with AES 256 encryptions. Okay cool so it looks like you can show some as visible he's toggled some switches and some are hidden and you can also choose to hide all when you're done. Yeah yeah there is also a global search card so you can hide all files with just hidden three buttons or you can log the app with the same combination. Very good well I've got a copy of of Hyder 2 and I hope to give this one a good test how much is Hyder 2 cost? It will cost $19.99 it will be available on the Mac App Store starting from 2nd of April next Wednesday but we are introducing 50% launch discount for first week so you can hurry up and buy it for less than 10 bucks. I hope we get this interview out before then. Well thank you very much Philip and the company again is MacPaw and the product is Hyder 2 the number two. Thank you Alison.


This is theCUBE live in Barcelona, Spain for HP Discover. SiliconANGLE and Wikibon's exclusive coverage. This is theCUBE, our flagship program. We go out to the events, instruct us in the film of noise. I'm John Furrier, the founder of SiliconANGLE. I'm joining my co-host, Dave Vellante, co-founder of wikibon.org. Our next guest is Rene Meyer, VP and GM of HP, integrity, servers. Welcome to theCUBE, again, CUBE alumni. Yeah, been here, I think this is the third or fourth time at various shows. Last show, you were on with Dave and Rick Lewis. I had to bounce it out because one of us too, I get the hook or sometimes Dave gets the hook, I'm going to bounce him out on the next segment. So I missed that on the chat, but you got to be excited. Server market share from what I'm hearing is looking good right now across the board. Yeah, we're actually seeing significant improvements and I think that's a testament to great products, great technology and then executing, working with our customers to find out what they need and deliver on that. So it's fun to see promises. Tell us what's going on here for you at the show. Integrity servers, your role, what's going on with the big announcements. Oh, so cool. So integrity servers. So I have a collection of businesses underneath that. So it's our Unix business, HPUX obviously. It's our non-stop business and it's also our scale-up X86 business that we've kind of embarked on here in terms of bringing some of the goodness of high-end clustered Unix into the X86 space. So all three very different businesses and you look at that, lots of stuff going on. One of the great parts about coming here is we get to interact with our customers face-to-face and hear about what they want to do and Unix customers, it's fascinating. You talk to them and they want to take risk out of their business. They're saying, I'm running a manufacturing. Risk as in RIC, RISC, risk like processors or like risk as in like, yeah. Risk as in business risk. No, they're looking at saying, I run a manufacturing plant. I run a hospital. I run a retail operation. How do I do that? Because you know what? IT is what drives their business. You think about going into a store. If you can't pay, if you can't find the merchandise you need, if you can't go to the e-commerce site and say I want to buy this thing and have it delivered to me in the store, they don't make money. So they're looking and saying my need for transactions, all these things are going up. And at the same time, the more change you apply to an infrastructure, the more business risk you induce in that. So they're looking at ways to say, how do you go manage that? How do you say, I want steady growth, I want predictability, I want stability? So they're looking at the fact that we've got increased capacity, our latest role to our I-4 server base. So we've got customers seeing three times performance improvement over where they were with the previous generation. That's huge. Dave and I always talk about the trends. And one of the things that we always talk about is that the old is now new. And we were talking about that with the Brocade folks yesterday at the storage party, the three-par and storage party last night. And systems management's back in. So I mean, the UNIX is back in. The mindset of large scale clustered computing, AKA whether it's big data or whatever. And we joke the mainframe never went away. So now the software mainframe, which is the cloud, as Paul Moritz once said. So I mean, this is music to your ears. I mean, maybe not buying as many boxes, but still the concentration of compute. Well, and what you've seen, the everything old is new again is exactly right. It's as we've gone where everybody's got a mobile device. There's a kiosk everywhere. You can turn your phone into a payment device. The taxi drivers are carrying around a PayPal or a square device and taking payments. Always on, mission critical. Serve the customer 24 by seven forever is way back in style. The cool part of that is you start to look at, you say, now what can you do when you say I've got this huge transaction engine? I've got this huge data engine behind it and link that with big data analytics coming in. Link that with mobility. So you say, I know where you are. I know a lot of things about you. How do I go make that all work? I mean, we're talking about my nonstop business just before we got on here. A great example is a car rental agency. Their whole back end reservation system runs on a nonstop environment. What have they done? They've put a web front end and they've put a mobile front end on. You get off the plane, you get a text. Here's your car. Would you rather have a full-size model? Would you rather have the SUV instead? Just send me a text back and I'll deal with all that before you're gone. Drive right out. Great opportunity for them. And I've noticed as I've been a user of this service, they're starting to know when I'm traveling on HP business, which is when I get, here's the full-size instead of the mid-size versus when I'm traveling on vacation and here's the convertible of the SUV instead of the compact that you bought. And that's nonstop sequel you were saying. Yeah, that's a nonstop application sitting behind on the back end managing all those reservations and you can't offer that. Think about that. The analytics lets you know what you're doing but if you make me an offer but then can't deliver the car, that's no good. That takes a... You got to go into a legacy system. Yeah. Get some data. Absolutely. And you have to marry the mobility part of it. You got to marry the big data part of it to know what I'm doing and where I'm going, what my rate plan might be, what cars you actually have an inventory so you can offer that to me and you do it right at the point of interaction. You know, when the wheels touch down, boom, the text shows up. So Randy, break down your businesses for us. You got the nonstop piece, the UNIX piece, the X86 piece, just describe a little bit what their business looks like. Yeah, so if you think about that, so the UNIX business talked about it a little bit. Really focused on lots of different customers from the smallest kind of businesses that are running, you know, some rack mount servers to run various things, could be in store controllers, whatever else, into bladed environments where people that want this converged infrastructure up into the biggest super dome things for really big applications. Typical customers, manufacturers, hospitals, retail chains, lots of places like that where they're dealing with business process, transactions, database. The nonstop piece really focused on some specific business applications, payments. If you make a payment anywhere in the world with a credit card, debit card, whatever it is, 80% chance that's going to go through a nonstop system either on the acquiring or the authorization side, or both, mobile phones. Almost 400 million subscribers around the world, their mobile phone runs through a nonstop system on the back end, and it's what lets you know what you can do, what your data plan looks like, all the services you get, how you make it work. If that system's not running, your phone doesn't work. So start to look at that. You look, again, we talked about things like reservation systems for trains, for cars, all those different sorts of things, high-end transaction systems that you see all over the world, and then this scale-up x86 business, this is fascinating. This is where the world's moving to for a variety of applications, and there's really two different models here. One of which is you're seeing people like SAP get a big focus on in-memory database. They're saying, I want to take and do my business analytics, my business processing, and instead of having it be kind of distributed all on disk, I want to move that all into memory so I can do it really fast. Guess what? If you want to put it in memory, you need large memory footprint, you need large core footprint, and you need huge I.O. because there's still storage behind that. So we've designed some appliances, and you had Tom Joyce on here earlier, so out of his Converged Systems Group, we go and say, build these engineered solutions for SAP HANA, where we can go build large-scale systems, and we're doing some exciting work around that up into the 6, 8, 12, 24 terabyte memory footprints. And for somebody who grew up where 10 megabyte disk drive was a big deal, all of a sudden, all in memory, had one customer that moved from where they were with their SAP R3 installation to moving everything into memory on the scale-up x86 architectures. They watched a 300 times improvement in their business analytics processing. It was just unbelievable. Things that were taking days were taking seconds. So that scale-up x86, that's what's known as Project Odyssey, and then there's Project Kraken, right? What is that? Project Kraken really is something we've embarked on with SAP around these large-scale memory things. So, again, large core count, 16 socket systems, and up into these 24 terabyte kinds of memory footprints. And we've paired that with our SAP HANA environment, and at Sapphire, in fact, this year, showed that and got rave reviews from people saying, I'm trying to get into that high-end business analytics and turn my SAP engine into an analytics driver for my business, and it's all about time. It's all about compressing that. So we're asking some questions about the Unix business. So this is HPUX, right? And the platform's been around for a long, long time. A lot of people might ask, well, why are people still using Unix? And so, as you said, you mentioned manufacturer. Manufacturers, you mentioned hospitals, for example. Is there a lot of custom code in there, right? So- There can be. Some of it's custom. A lot of it's still lots of ISVs. Okay, so a lot of stuff off the shelf, or, you know, medical type of software. So talk a little bit about that ecosystem, right? You don't hear much about it in the press anymore. If you think about why people used Unix in the first place. One, huge skill base out in the marketplace. You want to find a Unix operator easy to find, right? You want to find somebody that knows how to put a database up in that environment, easy to find. What are they looking for? They're looking for resilience. They're looking for reliability. They're looking for scale. And in particular, they're looking for scale in a scale up dimension, where you say, I want the whole application to be talking about the same data set, looking at the same data structures. So to do that, I need lots of cores. I need lots of memory. I need lots of IO around that. So in addition, they look at things like clustering. They look at things like failover. So we forget sometimes it's not just the box. It's not just the operating system even. It's things like service guard that say, okay, I can build higher levels of resilience into that because if I get a component failure, I don't want my business to stop. I don't want my hospital to stop. I don't want data to be wrong. Especially if I'm in it. That's it, that's it. Your doctor's looking at the electronic medical record and he either can't see it or the data's wrong. Not really a good outcome. So people are looking at that and saying, that's exactly why we chose those sorts of things. I got big applications. I need the ability to have a high degree of resilience and deal with that.  If you want to go get the maximum kind of availability in that environment, that's where you go to get it. So people looking for, how do I take my existing environment? The people who know what they're doing. And again, we talked about earlier, business risk. How do you minimize that for somebody running these critical applications? And you say you change as little as possible. You add capacity to make sure you're staying ahead of the curve and you invest in what you need to do to make sure it's not just the box. It's the people, it's the processes, it's the software, it's all the tools that make that ecosystem sing and dance. And again, we see people continuing to invest in this at a large clip. And one of the things I think is important is you offer people choice. One of the things that's cool about my business is tell me what your problem is. Tell me what your requirements are. Guess what? If you're trying to run and scale up a Linux application and get that or consolidate a bunch of Linux servers into a bigger footprint, we know how to do that. If you're saying I'm trying to get maximum availability for this Unix-based application, I know how to do that. Saying I'm trying to run the biggest infrastructures in the world running transactions and 400 million mobile subscribers. I know how to do that with nonstop. Tell me what the problem is and I think we have a great solution for you. Because it's not just about, in my business, it's not just form factor or box. It's the solution. It's the business solution, the business problem, the business process that drives that decision making. So, obviously you're talking to a lot of customers this week. Yep. What is it, coming by your zone? What is it, the nonstop zone? Yep. Well, they're all together, right across the way. What is the zone called? It's the Mission Critical Server Zone, I think it was the title on it. What are customers asking you? What are they talking about? What's the conversation sound like? So the conversations. Conversations are about, here's where I'm seeing growth. How can you help me with that? Where's my next capacity coming from? How do I get more memory? How do I get more storage? How do I leverage things like the new three-part technologies that are coming out? How do I take advantage of all the cool things that are out here? How do I leverage, in my blade's environment, how do I leverage Unix as a component of that converged infrastructure? In the nonstop space, lots and lots of excitement, one of the things we did talk about about a month ago, so we didn't announce it here, but we've now committed to, in addition to all the stuff we're doing in the integrity space, we're going to also port the nonstop entire stack top to bottom to an x86 architecture. So our customers are going to get tremendous amount of choice, and those customers are saying, well, if you're doing that, how can I link applications, maybe running on Linux, more tightly to my nonstop environment? So, okay, the mobile device management that's handling my home-making application or something else, how do I link that tightly to the nonstop SQL database, and make that even more resilient? So lots of excitement in that space. That's awesome. All right, well, listen, we really appreciate you coming by. I don't know, John, if you're... Yeah, well, my final question is two questions. First one is, what do you see as the next step in your world? Because, obviously, the world is shifting, cloud is here, we're hearing it, but again, we're not going to see any kind of erosion if you will, of mission critical definition may change a little bit, but in the end of the day, mission critical means, mission critical around your business. Obviously, is anything going to change? What's around the corner? Share with the folks your vision of what's around the corner and how you're attacking that. Well, so I think the important part is always on mission critical, absolutely, the demand for that is going through the roof. And it's a business process discussion. These business processes need to be always there. So the question for us is, how do we serve that? As things move to the cloud, there's going to be applications sitting out in the public cloud. There's going to be private cloud technologies deployed inside of companies. There's going to be traditional IT that has a lot of existing data and a lot of legacy business processes around them. How do you take and integrate all that so that at the end of the day, it looks real-time, modern. It looks real-time, modern. And to the end user doing the transaction, it's totally seamless. To the IT person, you say, I get flexibility so I can manage my cost. I can be more agile. And if I want to bring up new ideas, it's faster time to market for a new business idea. This idea of, okay, leverage mobile, leverage big data, how do I get all of that and connect it all in the- I was talking with Jim Compton, who's the executive vice president at United Airlines at the GE event. I hosted with the CEO, Jeff M. Alt of GE. And you know, it's all about big data and anything. Anywhere you're talking about, there's all this big data machine coming off the airplanes and turbines and all that stuff. And I asked him about the same kind of questions. He says, you know what? We still have COBOL. Yep. We have COBOL code running a lot of the backend reservation system. It's so bulletproof. It's so real-time tied into our current big data real-time system. We just can't replace it. There's no way we could actually replace that in any kind of timeframe without disrupting our operations. And that's the question. How do you take those core systems that people are running? One, you make sure they're bulletproof, make sure they're resilient. But now, how do you make a modern in this world where there's so much you can do with mobility, big data, cloud, all these different things? So how do you take and magnify that effect of this cool bulletproof stuff and link it all into the other fascinating things that are out here? Everything from software-defined storage into cloud, you pick it. A lot of opportunities for entrepreneurs to write those emulators using virtualization and cloud. There you go. This is theCUBE. Randy, really appreciate you coming in. Again, mission-critical systems, integrity servers, you guys doing great. We're here from Jim Gonti tomorrow, who's going to give us an update on all the market share numbers. Can't wait to have that conversation and how they compare against Dell on the other side of the business on the industry standard side. Great to have you. This is theCUBE. We'll be right back with our next guest after this short break. I'm John Furrier with Dave Vellante. We'll be right back on SiliconANG and Wikibon's theCUBE after this short break.