Session three in the program now deals with what is new in transcribers and we will be hearing about the likes, trends, thoughts, transcribers, that the technology is offering. First speaker up on the stage is Gondram Leifert from Euro University of Rostock and he will be telling you all the neat and nice details of what a 100-compact recognition costs. Yeah, I will talk about HCR Plus behind the transcribers. HCR Plus is developed at the University of Rostock in the SITLAB team together with Tobias Bruging and some other guys from our SITLAB team. Well, you have what to talk about. I want to talk about some technical parts, probably not that interesting for the most of you. Then I will make a comparison between the old and the new HCR. What can you expect from the new HCR? Then I will tell you something about common errors that you can make when you transcribe and trade in your network, which can make the HCR working in Rostock. Yeah, then I'm ready for a discussion. So, first of all, what is changed between HCR and HCR Plus? Not much for you. The input is still an image and the output is the transcribed text. The whole thing is trained with connection and temporal classifications and algorithm. Yeah, it works very well. What did we change? We changed the software. We had our own software and now we use software based on TensorFlow from Google. We changed the hardware. We were trying on CPUs. Now we're trying on graphical processor units, which are a lot faster. The architecture of the network changed. They became deeper and larger. And also the pre-process we have to change a bit because it has to be faster for the fast networks. Yes, here you can see on the left side the input is always an image and the output is not only a text, it's also the probability of a character at each position over time or from left to right. So, this here, black means 100%, white means 0%. This so-called confidence matrix or confmat contains information what is written in the image. So, this line here, this red here, means that the 3 is wrapped by the neural network to nearly 100%. Here the network is reading the point, here's the space and so on. So, the system is more or less working. On the right-hand side we see the structure of the HDR. It has some layers. And after each layer, the presentation of what is saved in the image is changed, more and more abstract. The input is the image and after each of these representation layers, the representations change until to the end we have this confidence matrix. And with the help of this confidence matrix, we can produce a transcription and we can also use this confidence matrix for the keyboard spotting search. So, this was the technical stuff. Now, what can you expect when you already had a train model in Transcubos? Yeah, we had the data set. I realized there's a typo I get. I guess it has to be a T. The old HDR, this train on a data set, the result was on the validation set, on the test set, it has 21% character error rate. The new HDR in this case comes down to 9.86%, so we can reduce the error by 50%. The time spent for training was not 20 hours like before. Oh, it's 5 to 6 hours in this case. And at the same time, we can train with 8 times more lines. So, the training got lost faster. The same for other collections like from AVP, we have the same. It is again faster and we come down from 19 to 6.35%. The best thing is Conceals protocol of Dr. Albaugh that we come down from 10% at the beginning to 2.6%. So, in this case, we nearly enhance the system by 75% character error rate reduction. I think the HDR Plus is not available for all of you so far because we just have one computer and so many people who want to train. So, you have to understand that we can open it just time after time for everyone. Now to something for you, when you make a training, you have to produce training data. We already said, the more training data the better and you already know that. But another big issue is also the quality of the ground shoes. The perfect thing would be 100% correct lower errors but also you make errors, not only the HDR. When you transcribe, there is more than one people and you have to transcribe. You have to define some rules how to transcribe, how to handle minus between words Should it be separated by spaces or not? Do you have an extra character for hyphenations or do you use a minus or an equal sign? So, if you transcribe with more people, tell them how they have to transcribe. Here's an example. The long S in fracture is, you want to transcribe it as normal S or long S. Please make one of these versions. Either the normal S, this is not the problem for the HDR to say the same S. It's this position and this position. You can also make this but please do not mix it. You know that one cannot know why it has to recognize long S here and not long S here when they cannot read. So, the ground shoes was this year. I found it in transcripts, this was the ground shoes. But you need words to tell me how to transcribe. This is very crucial otherwise the network is also confused. It's the same for abbreviations or diplomatic text. Often the goal you want to have is modernized transcripts like expanded, abbreviation and so on. This does not work very good. So, the network more or less can only read what is on the image. So, do not expand abbreviations like conclusion or file touch trigger. Just transcribe the short path. When there's just one character between like when you have the ID Das and the middle character is missing. This is possible. The network can maybe transcribe one more character in a row or two more character but it cannot expand the abbreviation. When you produce ground shoes there are in transcripts several steps what can go wrong. For example, typical way you transcribe a page then you replace HDR to check how good HDR is working. And then you start a training. Then maybe you start a training with the HDR output. This is there. Not a good idea because the HDR makes errors. So, if you want to train you have to check that the newest version of the file which you can find when you click here in the Graphical User interface. This video is shown. You have to check that the newest version is not a version produced by an HDR. Otherwise, this is used for training. And the best way is to tag pages as ground shoes. This is possible at the top of the Graphical User interface. Here you can select from new to the process and to ground shoes. And afterwards, when you start the training, you can check this button. You use only ground shoes version for training. This checkbox is available on the training window. And when you choose this, you only take these pages where the status is set to ground shoes on the page. So you can be sure that no HDR result goes into your training only the ground shoes pages. Then sometimes the HDR phase. There is one thing you can do. At the top of the Graphical User interface you can show some surrounding polygons. This is a bit complicated to explain. The input of your network of the HDR is a line surrounded by the polygons. This polygons is calculated by algorithm of us. And you do not see them in your Graphical User interface. You have to select the check button and make it visible. And when you make that, sometimes you see that they make errors, especially at the borders of regions at the top or at the bottom. When they surround two lines, for example like here, then the input of the HDR will be two lines. The neural network is totally confused and will not transcribe anything. So if you see some things put on the polygons, this is the reason why your HDR fails. But this is our to-do list. We will try to improve this polygo method. And hopefully it will be no more a problem in two or three months. So the question is, thank you very much. Question now. My phone is coming. Thank you very much for your presentation. My question would be, I'm new to this. Will this HDR plus? Is it also an open source? Can it be integrated to other projects than transcribous? No, it's not open source. But there is the REST API that maybe is possible to use it without the user interface. You can make a request, I guess, at a server and say, use this neural network on this page. And give me the XML result. And why it is not open source? Because it's funded by public money or not? It is funded by public and we have the open access things. But some of the tools which were before, which were REST access, before the project started, does not have to be made open source. So yes, when for example someone comes in, this is how it is. So if you have something before the project started, three years ago, the software or parts, they do not have to be made open source and they are still used to these things. For the questions? A simple technical question. Will it be possible in the future to launch two models in the same page? Because we have sometimes a page with two and writing text different from two hands different. And I guess if it's possible to have two models for something or a combined model. So it's really we have some transceivers interfaces for HDR. And therefore, for example, transceivers supports regions and you can have different reasons. And then you can say use this model for this region and this model for the other region. This is possible in the interfaces but not so far usable via transceivers user interface. So it is already possible but in the user interface not so far. One comment from my side concerning the usability of HDR Plus. As you have seen, we have a new release came out this week. And with the new release you can already use HDR Plus models if they are there and if they are opened up to everyone. The training of the HDR Plus model is working as well. But here we really have to comment that if everyone now is interested, press the button. Our server is from Cache. It's just one server. It is a powerful GPU server but just eight jobs can be done at once. So it takes a while. And therefore we came up with the idea actually that we will retrain all models which are there in an automated way. So this means that we will start with the latest ones and more updated models will appear simply in your collection. And in that way we hope that it can be done... Utilized to serve as the best way because always eight jobs are running and we care about this automatically. So that's the way we decided to do it. And then when the first spy for me is over, then we will unlock the HDR Plus training of course also to you. Thank you. I have a question about the abbreviation. Because you said that the abbreviations doesn't work. I mean it cannot read the abbreviation. But yesterday I heard from Ginter I think that it does. So I would like to... Because I don't know exactly how the computer read the text. So I am curious how it is finally. I mean is it worth to write abbreviation if they are easy let's say or totally not. Only the letters which we can see. Because for example let's say that we have some abbreviation which is always the same three letters with the line up. And so we should write for example that in many of our Christos is X per H never mind. But is it worth to write it like it should be or just these three letters? So there's just one letter missing. Or you expand one or two letters to two or three that's fine. But assuming our algorithm works like that. You can say every of these slots here. You can say one character. So assuming you are training with 3rd January. Where should you read the last five characters here in this part here? There's no space to read characters. But when you just want to have one more character the system can put it in here somewhere in the slots. Like yeah when you have some. What do you think about this HDR plus? It's the same for both. It is the same problem for both. So when you have just one character or so that's fine. This is what good can be. But when you have DR for Doctor or other longer expansions then the network will fail. It will try and it will probably match two or three characters but not the old one. And the character error rate will be there. A little bit possible in the future. That I make some rules in the transcription. For example I have XPS for Christmas. And then I say to the training software every time you are reading XPS. And the transcription is XPS please. Yeah make the right it like Christmas in it. That every user makes a rule for it. These things are a lot of work because you have to upload the dictionary. Which have a kind of standard. And then you can apply them. I'm not sure this is how high is it on the priority list. It's really possible yes. Same with abbreviation there. Or with name entities it's the same. Okay let's thank Gondram again. In this really interesting session is our read colleague Erwe Bichard from Navelabs in Grenoval. And he will be telling you about tables and about document understanding. Thank you. This is common work with Petra and Francivia and two colleagues from Navelabs. So just to give you an anecdote. The first time I saw similar images from it. My reaction was not so enthusiastic. And I was really wondering if we can do something for such a meet. One two years later I would say we have some more. So here what I'm going to talk about. So first I would like to define what I understand as table understanding. Just to make sure you are on the same page. And then I'm going to go through several scenarios. Which are strictly the way the table processing a part of the read project has evolved. And then I will go through a couple of examples to show you what we can do. And then I will discuss an initiative we are going to physically build open source data sets for handwritten tables. That we can share with the academic community. And so that everyone is able to tackle the task and share their results. And then quick speech or mixture. Here is a typical table we have from the pastoral collection. And so by basically table understanding. What I understand is basically the recognition of the row structure and the column structure of the table. So the first task is to spot the table. And then to recognize the rows and the columns to get the cells. You can add extra information to the column meters or row meters. And here are textual elements outside the table. And so that then you can automatically access the row structure of the table or column structure of the table depending on your data. So this is what I'm going to talk and how we do this. So this is how we do this. So scenario zero or I would say even minus one. Basically suppose you have just one page with one table. So what you can do now is to use the expert user interface where you can manually design the table yourself. And then you will be able to export this table into an Excel spreadsheet if you want. So this is currently viable. How to do this? There is an how to return by effort that you can download. The second scenario is basically you don't have just one page but you have two. But it's a kind of creative book where for each page you have exactly the same table. Very common in current times. Here the solution designed by Florian in the room. But basically so we add the user through the first page of the document. And then the two will be able to match this template against the remaining pages of the book. And then you will get the book for the structure in terms of what you will get with this tool. This is the column structure of the tables. Because the template in terms of columns is similar from page to page but not in terms of rules. So it's currently viable not through the graphic user API but through the programmatic one, the REST API. So you need to be familiar with this API if you want to use it. Or if you want you can also download the tool and apply the tool on your images. So it's explained in the same how to write about the table. The next scenario is you don't have just one book but you have hundreds of books. And each book will have a different template. So you don't want to take through an each book through a table for the first page and then process it. So the purpose here is to automate this. And the tool we are currently developing is basically a tool which takes a book. Kind of mind the set of pages in order to automatically generate columns to control the table. And then apply the previous template matching tool on these tables. So you can get a column structure for each page. And so you can do it automatically for a large number of books. The quick example here is from the same book you have three different pages. The same table. And basically the tool is able to recognize the vertical organization of the tables. So from this vertical organization what is missing is the horizontal one. The row one. For this we use basically input. So we recognize the text line of the table. So if you apply the level to integrating the tables you get automatically this. As mentioned several times but it's worth mentioning again how the tool developed by Tobias is really, really good. I've been working with this for more than a year and I'm still trying to find page variables which will be changing. So from this set of text lines what we can do is to categorize each text lines with many good information. For instance here the tool is able to recognize elements outside the table and also the column header automatically. And if you want really the row structure the idea we had was basically apply to automatically recognize the text line which are in yellow. And thank you. And which basically starts those text lines in yellow basically corresponds to the first text line in the given cell. So in the row. And with this information we are basically able to generate this kind of output. So here we have the full table structure with the columns, the rows. So from this we generate the cell structure. The headers are computed and elements outside the table are also recognized. So this kind of outputs is currently possible if you know the table from the given book. So sorry the template. So here the template was provided. So the template finding the column for the table was provided manually. And then the row recognition was automatically done. Depending on the tables you have you can also try various over possibilities. So here the graphical lines in the page were recognized. And the idea is basically that from this information you should also be able to rebuild the table structure automatically. The issue is that sometimes you don't have any graphical information in the table so you cannot only realize some graphical information. You have to combine both. So the textual information and the graphical line. This is currently what we are trying to do to merge all this type of information together. So all the methods we are using are based on machine learning. So for this, for the HDR, you need to provide a system with samples, annotated tables. And so we have such a dataset for Passao, for Math as well. And in here we are building a more generic dataset around the table. So we did ask you a couple of months ago to provide us with tables. So we had around 25 different providers. So now the dataset is composed of roughly 1500 images from very various tables. Mostly handwritten, we have also some printed tables as well. And so we annotated the tables. So first we had to write guidelines. It was not always easy when you see a table to know how you would like it to be structured. Sometimes you have different tables in one image. Very similar, you know, if you want one tables or two, it really depends. And so the dataset will be released for the competition next year. And the one question is basically, can we with this kind of data generate kind of generic model for tables which is as good as the text line detection we had in the project. So we'll see. I guess one backup solution is for given collection to annotate samples of the collection and just to train the system on this specific collection. So I don't know if we'll be able to have a kind of generic model for table processing we'll see next year. So yeah, next year. So a schedule is a bit fuzzy, but this is the best I can do. So what we want to do is to release a prototype for table processing, I would say by the end of the year. So it will be available first as standalone to it's written back then. So you will have to download it and turn it on your on your connections. And I get the plan is to integrate this into the transcript server next year. And so Victor is the main conference in the domain of document analysis and recognition will be next year in September. And for this conference we will organize a table recognition competition, which is a data set which will be valuable beginning of next year I guess. So if you weren't interested in this work, we published with a fan for a paper on the last task workshop this year, about the work done for the Pascal collection. I will try to describe as much as I can in the variable we need to write for the read project by the end of this year. If you're interested, the current version of the software is available through GitHub. Don't try to use it currently with couple of weeks at least. And we have already some data which was used for the article and from the Pascal collection. And those data set is publicly available on Xenodoo. So I don't remember the size of it, that's 200 or 300 pages of the Pascal table. It's completely annotated. And if you have questions. Questions on tables. Shape them up now or never. This is your chance. Don't you have to tell the system which way to read it? You read it from top to bottom or you read it from left to right?  Well, I mean, if you have a table, you can read it from top to bottom or you can read it from left to right. The structure of the table will be two dimensional structure. So basically at the end of the process, you're able to do both. It's like in Excel when you will be able to navigate column-wise or row-wise. That's the purpose of the task. And then it depends on the data you have in the table. Sometimes there's the written. The row reading will make sense. Sometimes it's the column reading. It depends on the task. So it's throughout the period. This is not the end of the process. Once you have the table, then if you want to basically feed the database with the information in the table, you have still to do some information extraction process and normalization and a couple of things. But at least you have this two dimensional structure and you can use it. Thank you. Could you say something a bit more about the content? The content at the bottom will be maybe nominal data or dates. So this is what we have done for Basel. Here it will be true in your case as well. You need basically to know, for instance, that in a given column you will find specific information. And then you have to design an information extraction tool usually dedicated to your task in order to extract the information automatically. Here I don't think that's a generic tool. I mean, you can have a generic tool to recognize dates or names. But if you have just one name in one column with a date, then you can put some semantic. You know, it's a birth date and it's fine for you. And that's how in that course, you have the date, but also the burial date. You have to know which one will be the burial and the date. And for names as well, in the marriage readings, you will add the witness as well. For a given reading, you can have four or five names. And then you have to find out the right one. So yeah, information extraction in current is not a generic. Thank you very much for your presentation. Your module, will that be able to use your model of the one you've been developing? I'll say like OCR program as well. We have lots of tables that are printed text. Yeah, for us it doesn't matter if it's handwritten or printed. I would be interested to hear what you are saying about how far it will be a generic tool. Actually, you got the point right in the first talk, if it depends on the data. And actually I think the success of the current layout analysis is based on the thoughts of the BNR team collecting the read that data set, which seems to be very, very representative. That you are probably finding any document that's present, really hard. And with the data set you are already, you are collecting right now. Actually that's a really important step to improve the baseline detection for this table. Now for the table scenario, and to cluster these for the entire, to get the entire complete structure of the table. I think it's not so far away. So basically if you got all the baselines correct, then I think you don't have so much problems to get the root lines, right? Or your tool is working quite well right now. Sometimes you don't have, what do you mean by root lines? The horizontal boundaries between the rows, parameters depending. And when you see the different kind of tables in the data set, you are not at that point currently. And we'll see. It's always hard to say. I would guess it's within the next year based on the data set. If it's so representative and it can work with it, maybe I don't find the word representative because the feature type is there. And therefore it's cool and it's necessary that these algorithms as well are trainable and are adaptable to the needs of the users and the different tasks. And another to avoid this annotated data problem would be a frame. Frame now is to use sensitive data. Basically we are able to automatically generate tables which are annotated. And then we can train the system with this sensitive data. So if you know from all the time of the tables you have to process, you can generate tables which are very similar. And then the first results are running correctly. So you just have to give some parameters to the generator and then this is the way you can generate the data here. So we'll see if it's focused now. Well, thank you very much, Avi. I think there's a lot more things coming up on tables and on HDR. So let's give Avi a hand. Pleasure to welcome to the stage our head marketing person for Keeber's Backup. I'm going to move back, we'll also be speaking about sharing HDR models and about the new fancy interface the transfer was back up. Okay, so this was a good introduction that I'm marketing Keeber's Backup and you will hear more about Keeber's Backup tomorrow morning and also see the nice implementation of Keeber's Backup application for the band time project. So, and this is the best marketing you can think about it. But actually I'm now telling this story about Keeber's Backup since a year or more. And interestingly the reaction of the audience is often more interesting but then it stops actually. And so I thought I give you a quick one more try and also going to show you what was integrated already in Keeber's Backup. And then I would like to talk quickly about with you what to do with the many HDR models we have now in Keeber's Backup and how to enable sharing. And also quickly I'll look to turns Keeber's back into things to start with today already. And I think you will also experience it in the workshop so I won't be very brief about this. Yeah, Keeber spotting. Usually searching is performed via a good transcription but for large collections also this HDR plus we will have the situation that you need a lot of training paper that you can process millions of pages. And if there are hands we've never seen by any chance the recognition rate will be not as good that the usual full-text search will produce good results. So that's a matter of fact I would say. And in many cases you will not have the resources through tens of thousands of pages and also a case where the recognition rate for unseen hands will not be so good. And here comes the idea of Keeber spotting. Is it possible to search not in a transcription but directly in the image? And this is the main idea of several approaches actually. It sounds a bit like magic. How can I find a world which is not actually recognized by the engine? And therefore I created a little presentation which tries to visualize this a little bit. And let's assume you have dogs, cats and birds and we want to train a neural network recognizing these nice animals.  We expect that the neural network learns and outputs this in a correct way. And that would be, I guess, a typical student work at the university in your course. And other applications, of course, recognizing images which have not been seen by the computer, by the neural network before. So the question is what is on this image? And this magic box is working and produces, as we have heard, a confidence rate. And in that case it says something between null and one, 0.6, and let's assume it says this is a cat. So this is the correct answer. This is something in between a dog and a cat. I was very happy when I found it. So let's assume it's not a bird, maybe a cat and this confidence of 0.6 is a dog. So the highest confidence level is the cat, but the correct answer is the dog. Okay, so if we transform this to the transcription and searching, show the transcription is incorrect. Because the system would say my highest value is cat and that's incorrect. But if you are now searching, I will say give me all images which are above a certain threshold. And it would return this image as a dog. If you are now searching for dogs, it would correctly give you this image because it's above a certain threshold. That's the main idea I think of figure spotting and the transcription still would be wrong, but your search results would appear on a relatively high rank. That's the main idea and this technology is now using the alphabet. So cat, dogs, birds are the single characters in your text or in your text. And the transcription are the characters with the highest confidence, but keywords searching provides you the string which is above a given confidence. That's again the magic of this technology which makes it so powerful and is not based on the text. It is based on the kind of indexing of the image. In Transcritos, we have now implemented this in two ways actually. One comes from Vostok, from the Citadel, one comes from Spain, Alejandro and from the Greeks. One uses the confidence matrix, so this what you have seen before, this character based equivalences. Or both are using this in a different way actually. So that is the implemented keywords spotting in Transcritos. You can direct the search after you have performed the recognition. This means that which is a very nice thing because you just run the recognition and you can immediately search afterwards. The way it is done is that each confidence matrix is open and this dynamic programming, the best matching strings and so on are formed. This is fast, but for large collections it is probably not really fast or it requires a strong computing power behind it. The other way comes from the team in Valencia here a lot of work goes in creating an index. So the index is a reduced confidence matrix based on some highly sophisticated processing. In former times they used words, now they are using n-grams as far as I understood. Therefore, the auto-propeller rate problem which always appears with indexes can be avoided. The good thing is that we have a really quick response time and we can use standard full-texted engines for implementing this. It looks like the interface is more or less always the same. It is not a final interface, it is really more for demo. This is maybe also one of the reasons why we are not working that much with student spotting. The user statistics and they are always very low. So this was one of the reasons why I wanted to mention this here as well. In this upcoming project with the National Archives of India we will implement student spotting and we will thinking goes in a direction that how to use this kind and how to design the user interface and currently we believe that it will look similar to what I have shown you here. So on the one hand you have a tree level which is for my point of view very important for archives because in archives what commands are typically ordered in a hierarchical way. The users which are searching for a word will get an answer on how many hits are on a specific hierarchical level starting with level one and then we will come to the sub-collection and so on. Then you can likely order the snippets or the hits in the usual way and on the right hand side we will have some facets like narrow research according to the document to the archive unit or to places appearing on the same page or to keywords appearing on the same page as you were looking for. And in the center of the interface I would imagine an image snippet which shows two or three lines so that we get a kind of context where we already have a first look at the hit at the result and decide, and I think this is very important, decide if this is relevant for you or not. Because this is something I'm currently missing very much with all kinds of user interfaces in the archival and library world that you stop researching until it's very seldom possible to export and to take the data with you. And that's, I think, is really important. So one other idea is that this is really just the first idea is that if you have maybe already decided that this is interesting for you you might even add a command or a tag for this snippet or you can start to correct this deadline because you know that's relevant for me and afterwards save it and also export it either in GES and extra documents which are still used because you want to work on these pages or to export PDF or whatever so that we can make something with you. So that's our really thinking. We'll see what we will really realize that probably is smiling because he knows that this will be unstable. I skip the demo and come to the sharing HDR models. Yes, I think you have seen that there are really a lot of models now available but the only ones who can see this are us and that's not a very satisfying situation. So I know that many of you want to share your models and that really makes sense and it also would, of course, lead to the situation that more people are working together with single users in Transcubus but that we are working together and that we get the feeling, oh wow, someone trained a great Latin model for medieval stuff and I am benefiting from that and that of course makes the group much more group and I think this is really great. So I'm happy that we are now in this situation that we can think about that and the question is of course how to make it. So I'll share some ideas on this. I think we will need some metadata so the language does not play a direct role for the HDR but on the other hand since the neural networks learn the context the distribution of characters will have an influence so language will be an idea then the kind of writing is actually very hard, often to say because it's just fussy medieval stuff or late 18th century but on the other hand we have heard today that people are training models for early writing, data writing and so on. Then the script, I mean definitely to print it and hand writing is something which makes sense but also specific writers styles maybe from the Middle Ages maybe in German, Korean, or Switzerland similar styles probably would exist in other languages as well. What is very helpful I think is the description of the document for training that's because the experts know what is specific with their document and other experts will understand exactly this thing, a short narrative for all the two lines I think will always be helpful but I think to have an example of the pages is of course the easiest way to share the knowledge models or to attract other users to use them but here we have to see that or we will see that of course some of you will be happy to share test data so if you have a test set you just say okay I'll share it to everyone then it's fine and we can show all the data to everyone but others will say well I got the images from a library I'm not sure what is the legal situation so I cannot say just actually act with everyone which means more or less like a publication or distribution so we came up with the idea maybe of sharing just a few lines which is likely enough so this interface now and here it would have more or less just a button that says share this model which is in the community and the idea is the lines could be that some random lines are selected from the document and if these lines do not contain any names or anything what you say is some more complications you will select some lines and the user will see at least some lines and add an idea of the one style of this model and the consideration is also that what this is really proved for us model that you just need to then scribe some lines and specify maybe the period of the language and then that there is a button to run this against all available public models and so that you get a base on the contours of several lines of the best model available for your specific document that I think can also be done with the most effort so these are some ideas on how we could do it and soon everyone of you will have the chance to have a look to this own document via the My Collections website so this means that you see all your documents on the web as well and then you can select the document and the document pages and here are the two main modes the plain text mode which means it's also mainly for transcription and it really allows you to concentrate on the transcription and you have the same options as with the possible expert type that you can add special characters that you can superscript the underline for and so on but you also can and this is also configurable or will be configurable that users can use annotation or an extended version of this tool and this means that the annotation can also be done in here including the properties so the attributes for the text and that's currently more or less all but we believe that with this we will be able to involve people who are not so much familiar or who do not want to get familiar with this expert type but want to complicate the infrastructure ok, thank you very much Günther it's the nerve of everyone in the crowd so let me just get a quick show of hands for open questions just a little question Günther do you think that it is possible that annotations are also part of the training that the machine itself in the future will recognize names etc so this problem is well known as name entity recognition and it depends on training data so we are of depth yeah, we really need good training data for name entity recognition or tagging and then we can maybe provide somewhere something I know that the company is working for us actually it's right now quite high at our priorities so we would be happy about some more we have some data sets some academic stuff but if there are a few more from the historical problems then we are we think we can provide something within the next half year thank you very much again Günther will be here as well as the other speakers


How do we make better content?  Now, I know not everybody loves that word content, but just try to reinterpret that word. If you don't love it, it's just simply sharing. It's simply sharing your knowledge and sharing your experiences, sharing your thoughts and point of view with the world in a way that helps you explore and also you hope will help others as well. So here are five ways and if you basically work on each of these five ways bit by bit, your content will become better and better over time. So let's get started. The first one is care. I start here because as you know, I am always trying to bring a way of doing business into the world that is more nurturing of our inner life and of the inner life of other people. So it makes us feel more love, essentially. So care is why the first factor I wanna bring in. So how do you, well, you might say, what does care mean? So how do you get your audience to care about your content? How do you get them to care about your content? Well, there's different ways which I will talk about, but here in this factor of care, you get them to care about your content by showing them that you care, by showing them that you care. Okay, so I find that a lot of people that I've worked with over the years, I just watching people do their content, they have a Facebook page or a YouTube channel or whatever it may be, they might have a lot of subscribers or however many subscribers they have, they haven't been able to get those subscribers to really care about their content. And I think this is a one big missing factor is that the creator isn't making the audience he'll cared for. It feels like you're just kind of delivering content and delivering content and that's it. So how do you make the audience he'll cared for? You get to know them more deeply. Really, so in the first couple of years when I was creating content from, when I started the consistency, consistent rhythm of creating content, 2004, 2005, I was doing what I call audience research conversations, one-to-one conversations. I tried to do one every week, if not twice a month. I would basically ask one of my audience members, somebody who was commenting on my stuff or somebody who was reading my newsletter or whatever it may be, I would ask audience members and if you don't have any audience members, start with your friends. Your friends are your audience at the beginning, right? But you ask an audience member for a one-to-one conversation and in that conversation, you split it in half. The first half, you're really asking them about what they are needing at this time, what they're looking for at this time in their life, in the areas that you can provide something for. Maybe you have a product or service about a particular topic. Well, have they ever bought anything, a product or service on that topic and what worked for them? What didn't work for them? And if they could design, if they could imagine a really perfect offering, a perfect solution to support them where they're at right now in their life, in the area you help them with, what might that solution look like? Is it some kind of coaching? Is it some kind of, is it a book? Is, what kind of coaching would it be like? Is it some kind of accountability program? What would that look like? So you basically try to find out, by talking with them, what are they really looking for that you can help them with? So that's the first half of the conversation. So if I do a 30-minute conversation with someone, the 15 minutes would be me asking them questions to try to figure out what it is that they're really looking for that I could serve them with. And then the second half of the conversation, they can pick your brain, because they're part of your audience, so they have some interest in the things that you create content on. So let them pick your brain, ask you questions about, maybe you can help them with something. So care can be done with that one-to-one conversation, or it could also, part of how your care could be done is when you're creating content, try to pause and bring your heart to it. Don't try to be like, oh, how can I create this content so that people will buy from me or hire me? See, that's not really caring about them. That's caring about you, right? You gotta say, well, how can I create this, even if nobody ever buys from me, from this piece of content, they will still feel served. They will still feel ministered too. So I really see content, as you might know from following my content for a while. I see content as a cause. It's a ministry. It is a way to serve the wellbeing of others, not to sell them on things. You still, of course, I sell all the time too, not all the time, but I sell on a regular basis. But when I sell, I sell, I don't like beat around the bush and go, blah, blah, blah, oh yeah, by the way, buy this for me. No, I sell. I'm like, hey, this thing coming up, would you buy this, or I have this offering, would you buy this? I'm very upfront with it. But when I'm creating content, I'm just trying to express my thoughts, something that I find interesting, and I'm hoping that they'll be helpful for you as well. So care, that's the first factor. The second factor is topic. So one of the secrets I found after having written over a thousand blog posts, made over a thousand videos, this is a very important learning. It doesn't matter how on or off I am that day in terms of how I'm speaking, whether I'm showing up good on video, or whether I'm a brilliant writer that day, doesn't matter. If the topic is a good match for my audience, they will like what I put out there. It's really interesting and it's really true. So even if that video, I'm like having a bad day or having a difficult, something difficult emotionally just happened before I started making the video, and I just, I'm not on, if the topic is good match for the audience, they'll love it. On the other hand, if I'm like feeling really grounded and feeling really good and got a great sleep and I'm just really on, but the topic isn't a good match for the audience, it'll be a very mediocre response. Same thing with writing. So the topic will save the day. It doesn't matter how skillful you are as a communicator, you have to try many different topics for your audience. Things that you think might be interesting, things that are interesting for you that you think might be helpful for them. Try different things and see what works, what really works for them to go, oh my gosh, that was amazing. Oh really, I didn't know. Okay, so now you'll make more things like that going forward, you see. So that's the second factor is topic. The third factor is style. Now what is style? Style is basically if you're making videos, it's how you talk, how you gesture the way you dress, the background of your video, that's video. If you're writing, whether you write long paragraphs, short paragraphs, I would recommend most of the time on online writing, you should do shorter paragraphs. But anyway, it might be, are you a bit more formal in your language or very, very casual? Do you generally just like to bring humor in or you'd like to have more gravitas, it's more serious tone? Your style and on a website, a style might be the types of colors you really enjoy that you have on your website or yeah, so style is all of that. Personality, feel the feel of your presence, et cetera. And everybody has a different style. What happens is some people say, well, this and that person's successful. So I'm gonna try to emulate their style, try to copy how they do things. And if it's not genuine to you, you're going to burn out, always pretending to be somebody else. So how do we find our authentic style? You've got to try different things. Sometimes try, what does it feel like when you are very energized? Naturally, it might not be that you talk fast and that you just you're a lot like I do. If you're energized, it just might be that you have bigger eyes or whatever it may be, right?   You don't have to be anything other than who you are to that person. Can you imagine someone like that? Some who just loves who you are. Maybe it's a friend or family member that you can kind of borrow that idea that they've loved you well.  How would you speak to them? How would you be with them? You would be telling a story that you really are interested in. How are you being in that moment? Try that when you're on video. Try that when you're writing. You're writing an email to an unconditionally loving audience member. How would you write on the topic? So try different ways of being. Sometimes you try what's like to be lower energy. Sometimes it's very excited and see how it feels and then see what feels really genuine to you and also what the audience responds well to. If you can find the intersection between what feels genuine to you and what the audience responds well to, then you've got your authentic style. Keep doing it, step into that. Really double down on that, okay? And so that's care, topic, style. Fourth one is format. Format is basically how is your message being conveyed? Meaning is it in a long article on medium.com or is it in a tweet, 280 characters? Is it a medium sized text post on Facebook? Is it gonna be an Instagram post with an image?  Is it gonna be a long video on YouTube? Is it gonna be a short video on Instagram? So these are all different formats. Have you tried the different format? This is gonna be a podcast, right? If you haven't tried different formats, you haven't really given yourself the chance to experiment with what content format would really work for you. And so I really encourage you to try it out because you never know. Maybe the Instagram will work really well for you. Maybe you really like doing Facebook live. I don't know. You don't know either until you try all these different ways. So if you look at the article below the video, I have notes associated with this video. If you go to the article, there's a list of formats that you might wanna try every single one of them a couple times, okay? So format, because sometimes a message is brilliant in one format and in another format it falls flat. It's not necessarily the message. It's the format makes a big difference too, okay? So that's number four, it's format. And number five is reach. Reach. So if you're doing all these things well, you're showing care to your audience. You have the right topic. You have found your style. You're expressing it. You're doing it in a really good format, but it's not reaching enough people. Then it's not really gonna help anybody, right? Some of you, what I've noticed, right?  Did you know you might as well not use Facebook business page if you don't run ads. It reaches almost nobody. That's normal. That's Facebook business pages. You reach maybe up to 10%. Sometimes a little bit more, sometimes less. 10% of your audience if you don't run ads. You have to run ads on Facebook business page. Otherwise, how are you getting the reach to actually help people, right? To have people find you, discover you. On Instagram, very easy to run Instagram ads. That's a really wonderful way to get reach too. Another way of getting reach is partnerships. As you probably noticed, if you follow my content, I'm interviewing people all the time to help them get more reach. These are all my clients that I'm interviewing. Sometimes it's my colleagues that I trade interviews with. If we have a similar sized audience, I would trade interviews with somebody. So if you have a similar sized audience as me, we should consider doing a partnership. So yeah, so basically paid ads, Facebook ads, Instagram ads, easiest way to get targeted reach, reaching 1,000 people for $10. I think you can afford that in your business. $10 to reach 1,000 people. I think I definitely would recommend that. And then partnerships. So these are the five ways. Care, topic, format, style, reach. Work on these five, each of these baby steps. Just work on a little bit every month. Work on, you know, what is your, what are you gonna work on this month? Are you gonna work on care? Are you gonna work on trying different formats?  So I hope this is helpful. I'm George Kow, authentic business coach and I'm just gonna take a look right now to see if anybody is commenting on my Facebook live video that I'm making right now. Thank you for joining me by the way. And I'm always very grateful for your comments below. So I'm just taking a look here to see who's joining me. Okay. So I am actually not seeing anybody joining me for this video. I hope it is working. But anyway, like I said, if you have anything you wanna say about this, if there's anything that I've said that is inspiring you to actually try different ways to get to you, let me know. And this is interesting. Okay, there he is. I do see a couple of people joining me. Thanks Ian and Heather and Sarah and Alicia. Thank you so much for your comments there as well. All right, that's it for today. And I will see you in the next video. Thanks Yvonne Kuzwell. All right, take care.


Mae'r event yn ystod haner. Silydd yn gwneud ar gynnig ffordd gyda'r popution ar y cyfeiri'r sydd ffordd. Dwi'n fyddi'r môl gwirio'r cyfeiri, ac iddo dwi'n meddwl bobl mae'r cyfeirihedraeth. Mae hwn i'n gwybod maen nhw'n weithgrif yn dweud. Roedd y gallwn y gallu a pheth gwaith ydyddol fod ydych yn meddwl siweth ar y cyfeiri'r cyfeiri hwn yn cyfynnwys yn gwybod i'r cyffredin yn deall i'r cyfnod i'r cyflymu. Everywhere Coach has that all people have been able to take something from tonight, and I think the key message that Martin has delivered this evening is that keeping things simple, not over complicating practices, and letting practices flow, and letting players learn from their mistakes in a number of different environments. We created a really positive learning environment and speaking to some of the coaches on the sidelines, they have said that they would pick up one of two things they can instantly instill into their practices, even as soon as this weekend's games. You have a huge belief as a football club we have, we are required to go out and support the local grass roots community. Without grass roots football none of any of the above at the elite level would be possible and to be able to support coaches to enhance that experience I'm working in the best out of the game and the enjoyment of the game. It's that for us is job done. If we can help out those kids, stay involved in football, enjoy the football and play for many more years to come, they'll do so because of the environment that their coaches have created for them. So, if we can do any of that and we can provide those experiences for young players and for coaches to develop, then it really helps us out as a football club. Ar flynywch hwn yn fwyaf ar y cyfrifigio hwnnw. Fyddwn ni'n fawr i gyfrifigio'r cochei cyfecilol a'r ddweud â'r ceffylo ddechrau ac yw'r lleoedd cynychoddiu mynd dda'n rhaid i'n rhaid i'n fawr i'r cyfrifigio'r cyfrifigio a'r holl erioed ar gyfer y dweud o地 offer o tuithwch yn cyfrifigio'r cyfrifigio sy'n byw ddiwleda.


Ever since Chris Avalon left Obsidian Entertainment, I've had my share of doubts about the company's ability to follow up the great RPG classics of the previous decade it helmed. Some of my favourite games fall out New Vegas in the Night of the Old Republic too, among others. Pillars of Eternity, even with Avalon working on it as a narrative designer, lacked a certain depth. I'd come to expect from the studio, and while Obsidian's second isometric RPG, here in the remarkably strong premise and opening, it drew to a close at the worst possible time.  So of course I'd been worried. What you get in other one of my favourite developers has gone off the deep end, has gotten extremely greedy, put an accent on business first and player experience second, third and last. After playing through the introductory world, or if you'd rather the introductory settlement of Edgewater in the region around it, I'm happy to report my fears seem to have been greatly exaggerated, even misplaced. There is depth here and in all the right places, let's just get the basics out of the way. I love the customization, but even more so, I love the look of the game. Possibly, the vegetation is thick enough that I sometimes lose track of the veritable mountains of corpse's eye, a space freelancer slash recently awakened colonist who spent 70 years in crowd sleep, reduce. The visuals of this first planet are stunning, none of that bleak brown as you might remember from the opening of New Vegas. Bright colors, gorgeous vistas, a sky that fills you with wonder and appreciation for the artistic direction Obsidian has taken with this one. If the look of the world draws from the brightest, most hopeful of science fiction, boy, does the story have a fun time of dipping into the most dystopian scenario I could think of. In short, corporation is king. Here's the deal. The player character has spent 70 years in crowd sleep aboard the Hope spaceship, along the best and finest humanity has to offer. Over the 70 years, corporate culture has promulgated itself in extreme ways, like for example by poisoning the water supply of a small town in an attempt to extract the natural riches of the world, without a moment's thought for the suffering inflicted on all the innocents who live there. Uh, that actually happened. What? It did?  That's awful. Uh, okay. The salt-tuner thing? That didn't happen to her, did it? 100% in game. Oh thank God, corporate overlaws for that at least. Raise the mouse. The outpost town of Edgewater is a salt-tuner colony. It only produces salt-tuner. Its citizens are on an exclusive diet of, you guessed it, salt-tuner. There's also a plague in town, wonder why that is. And the cure for that plague, according to the outpost administrator, hard labour, is kind of like Stalinist Russia, come to think of it. What left the strongest impression on me, too? Even more so than the bizarre ways in which corporate interests have taken centre stage in human life has to be the characters. Plenty of colorful ones from the mad scientists attempting to make things right for all the colonists' finiest wells. Is that thing wrong? Not to worry. I've pumped your body full of a special concoction I devised to keep you from dying so horrifically, hopefully at all, but I guess we'll see it. To read Thompson. The man in charge of the settlement with corporate interests at heart in a very particular view of people. Even if he cares about them and often refers to everyone in Edgewater as one big family. I say he cares, but he obviously does so in his own very strange, somewhat twisted way. The leader of a renegade faction outside Edgewater, meanwhile, seems a kind and matronly figure, and has the greenest thumb in the universe.  Which is scary, needless to say. And don't even get me started on Ada, the ship AI who, an article headline I glimpsed somewhere on the internet called Outer Worlds Yes Man. I haven't read the article, but that's a great way to nail the essence of that character. I will require some time to process this information. Thank you for your patience and for your honesty. I am programmed to take orders exclusively from Captain Hawthorne. If I accept your orders, then you must be Captain Hawthorne.  But you know who the most precious, adorable, bestest character is? Parvati. The engineer and our first companion. She is the best. Just the best. This shy engineer isn't liked by all her neighbors, hardly by anyone, but I, for one, appreciate everything she brings to the table and can't wait to get to know her better. I knew some of them before they left. I don't know anybody well. I mostly listened to them talk, kept my head down. There was a boy named Thomas who used to follow me around, asking questions about the stuff I fixed. He was real sweet to me. Not any sort of dissident. Life's hard here, especially for them. What Obsidian has managed is, they've given each of the big players in Edgewater in a fair amount of the minor ones, too, some memorable quirk. Or even a few, something that's hard to forget, harder yet to ignore. And that's more than Bethesda ever seems to do, at least in the last decade. Then, of course, there's the choices. I've missed interesting, complex choices. First, the freedom to walk away from a quest you don't like is here, as in most other games. And I did that early on when a gravedigger, pardon, a junior in humour, let's deploy the corporate doublespeak already, asked me to collect the coin of the recently deceased's families and account that the graze are on corporation-owned land. And as such, they are rented. I refused, disgusted and haven't looked back since, and my first playthrough is guided by my own moral compass. But the ideas I've got for characters after that one. Boy, you are going to love them. But the big choice was between cutting the power of the city of Edgewater or that of a small settlement of renegades who've left their workstations in search of a better life. It's not exactly a binary choice either, since it's more than just about one faction or the other picking one over the other. It's about two different ways of life between picking the status quo and being completely radical or trying to find a middle way. Favourite side quest? Saving this runaway from a life among marauders inspired by space western serials and mostly from herself. How did I persuade her to go home? Simple enough really. I reminded her there's a new episode of her favourite space marauding show waiting at home. Wait, you're telling me he's got a copy of the mass market here? Why didn't you say so? I'll take my stuff and head on back I suppose. Grace is going to be glaring knives at me so I've got that to look forward to. Kids these days. Insufferable binges, am I right? At any rate, there's plenty to laugh about this one and I'm really excited to play more of it. And you know what? From the sight of it there's plenty to replay as well. And I rarely scratch at the itch to replay most games. For this one I just might. But not before I tell you all about whatever is ahead for me and my space of friends. Until then, see you next time. Thanks for watching. Don't forget to like, share, subscribe. Bye. Only the most dashing champion of private enterprise ever to don a mask. Until I get my start that is.


Will you be in education and public service exploration? Are you interested in learning, helping others, teaching, and enriching the minds of the future? Are you interested in community service or political activism? If so, you should look into education and public service exploration. This meta-major explores majors such as nutrition, special education, early and middle childhood studies, family studies, and public affairs. Students in these majors graduate to be teachers, youth services workers, social services coordinators, parole officers, event coordinators, and natural resource managers. This is the perfect place to start for those interested in education but unsure of whether K-12 is the right path or those interested in policy, law, and social justice. It's also good if you are debating whether to choose a licensure program or major in a content area like English, history, and math before pursuing a graduate degree in education. If this sounds like something that you would enjoy, it's time to ask, will you be in education and public service exploration?


Thankfully, it's November and Appalachian Wireless is offering the Samsung GS8 or the GS8 Plus for $100 off the regular price with two-year agreement. Better service, bigger savings. That's today's Appalachian Wireless, an East Kentucky network company. How do you get 13 tons of toys and food onto the Santa train? It's simple.  Saturday will mark the 75th running of the CSX Santa train. Wednesday evening, volunteers from all around Tri-Cities, Tennessee and Virginia gathered at Food City in Kingsport, Tennessee for the annual Santa train packing party. The volunteers ripped into boxes and bags and divided the food and treats into plastic bags that would fill totes, that would eventually be loaded onto the Santa train. This is our vendors, partners, and just people donating food. We got a lot of food, a lot of plus shawry on the truck, so we got about 400 totes like I said, so a lot of vendor partners. And AIDS was not a consideration for volunteers at the packing party. It's really fun because you get to bag and you get to help people if they need help doing something. I really want the chocolate covered mankind's because I love chocolate. It's just a lot of fun. Food City really allows us to get involved in this and Food City, like I said, is a big sponsor, but it's because right here, what you see behind me, you got all these people out here that is the reason we do it and helps us. The items packed Wednesday were loaded onto the train on Thursday in preparation for the trip north to Shelby, Kentucky, where the Santa train originates. And with this being the diamond anniversary of the Santa train, which began under CSX predecessor rail line, the Clinchfield Railroad, CSX is putting something special on the head end. The Clinchfield Railroad number 800, the very first diesel electric locomotive that Clinchfield ever owned. The engine was repainted into Clinchfield colors specifically for the Santa train, and this year will mark the first time in decades a Clinchfield painted engine has led the train. The engine was showcased for railroad enthusiasts and media on Thursday, and she even got to stretch her legs on the rails formerly operated by the Clinchfield. The Santa train schedule of stops for Saturday is available on the Santa train Facebook page or at EKBTV.com. In Kingsport, Chris Anderson, EKB News.


Good afternoon everyone and welcome to the Stockswish show play of the day. This is Blocks. It was a great gap here, one of the top watches this morning. And actually, I thought it would go to 11.50, it's not going to make it there today, but it did go to 12 dollars, which was one of the targets. The dream target was 11.50. And you know, some days things go to the dream target, some days they don't. But the real target was 12 dollars and I felt certain that it would get there. And it did. So it was a good gap. And you could have played this hard today. You could have played it a couple of different times and really maximized the move in this. It allowed for that because it gave several different setups. So let's just go over it. But this gap for a lot of reasons today actually, there was a lot going on with this gap. So what did this do? Well, it broke immediately. And if you did this immediately out of the game, you might have gotten stopped out. I actually didn't do this play. I was looking at something else, but either way, the gap was good enough to retake it, which you can do. And sometimes you have to do with stocks. Sometimes the first play does not work. I always usually do the first setup though, unless I'm watching two things or three things in a morning. At any event, this ended up being terrific still. So if you took it, you got stopped out. It rallied. It rallied up and had a beautiful rally in here. And this did not reverse swoosh. All it did was a nice concentrated rally here, up to the resistance, did knock it over 1350. And the stock was down a lot of the day. So a rally was perfectly fine for this. It was still good. It went over the high of the day, but it did reverse swoosh, and it was still very, very, very good. And then here's the entry. Okay? I also had an entry in the two-minute as well, and just came right on down. Nice move in here. Me just followed it all the way down, down, down, down, down. And actually, this looked like it was going to get to $12 in the first move. Crazy, but true. This is almost a dollar here from the entry, and it looked like it was going to get down to the very first target by the first move, before 10 o'clock. So there was a lot of weakness in this. Then there was a second set up in here. Let's go over it. Actually this looked like this was going to break down right in here in the five minute. However, it did not. Okay? It did not. And when it rallied back, it made a nice topping tail here. It didn't hold $13, which isn't that big of a deal. It was still valid there. It did hold this area here of the resistance. You can see it. It's very clear, actually. And the stock did trigger in here. And I thought that in this move here, it was going to go all the way down to $1150, but it didn't. It did bleed down down to $12. And it's one of these things where you kind of got a money-managed yourself as the day goes on. I do really watch things closely. If I happen to be in them in the afternoon, I don't do that often. I did stick with this today past the time I normally trade in the morning because I wanted to get as much as I could out of this, basically. And I feel that I did for the later play. As far as the morning goes, though, this could have been played very hard in the morning here. It actually behaved very well. Wasn't wild and whippy, and it really did everything right today. It had a little bit of a spread in the morning, but it wasn't that big of a deal. And it was a nice short. It was a good short. And actually, I have no idea what this does on Monday, but I wouldn't be surprised if this follows through on Monday. I mean, I really, really wouldn't, or it may just not do anything, I'm much of anything on Monday. It had a good move in it today, and it's going to close under $13. I mean, the stock is still lower. You know, every once in a while, you can get a trade, a new entry and something, or an ad around 1.45, 2 o'clock, 2.15. This stock just didn't do it today, and you can tell by the way that this flipped here in the 15 minute that this move in the stock was done today. And this $1,201 is the low of the day. The stock rallied up in here, tried to go down again, couldn't do it. And then when this bar happens, you've got to realize that you just have to say sayonara for the day here. Stock rallied up here, still held $13, but too late now to go any further. This would have had to kind of squash around in here if you wanted to look for another setup. If you wanted to get in it like a third time in the day, you know, you just really had to hold in here. This way that this is scooping here now tells you you can't redo it. So I actually was thinking about taking another trade in this here this afternoon. But it really needed to be around 1.45, 2 o'clock, 2.15. I think there needs to be a rule where you almost don't even take any new trades after 2.15. It gets to be too late. Oops. It's too late for then stocks to move and continue. If you're still in something, you want to watch it and you're honored to dine and you're ready to have money on the day and you have your stock lower, that's a different story. But to actually take a brand new trade at 3 o'clock and 3.15 is just too late to do. It's just way too late to do it. But every once in a while stuff will set up, you know, 2 o'clock, 2.15, sometimes even 2.30, but they've been that kind of late. But this did have a beautiful move in the morning. It did everything right they were supposed to do. A lot of weakness in this block. Really nice play here and was one of the two top picks for the day. So good job, everybody that did this today. Good job, everyone that traded this in the morning and made the profit in this and stuck with it then in the afternoon to get it down to the whole number. Very, very good job if you were able to do that. This is Melissa with TheStocksWish.com. It's 3.15 on Friday. Have a fantastic weekend, everybody. And I'll see you next week doing a webinar on Monday if you're interested in more information on coming to the webinar. It's 4.30 Monday afternoon. If you'd like more information on that, email me at Melissa at TheStocksWish.com. Thanks, everybody. Have a great day.


Hello and welcome to NewsClick. Today we have with us Dr. Satyajit Rat of National Institute of Humanology to discuss what has become extremely controversial. Two months back, we had the controversy about publication of the modified H5N1 virus papers where it has been suggested that key sections on the virus modification be actually taken out of the text, be redacted and then only science and nature should publish them. The two researchers, Ron Fuchier and Kawaoka, have both suggested that these things are not as complex as they've been made out. There are really no dangers to these papers and they should be published in full. After the National Science Advisory Board and Biosecurity suggested redaction of the papers, a number of scientists met under WHO ages and have suggested that releasing the key sections only to few researchers would involve processes which are not clear and therefore they should not be followed and actually the papers should be published in full. So we have two completely different positions taken both of very well known researchers in the field and now we have a position that we do not know which way the scientific community is going to go. Satyajit, could you explain to us what is the transformation that has been done for the H5N1 virus and why is it being considered so dangerous? In the first place, the Kawaoka experiments at the University of Wisconsin in Madison and the Fuchier experiments at Erasmus Medical Center in the Netherlands deal in a certain sense with two different viruses. The Kawaoka virus puts together components of two completely different viruses. It puts together a component of the H5N1 virus, it's along with non-H5N1 viruses and it builds therefore a virus. This virus is the one that they've used. The Fuchier virus is a virus generated in the lab from the H5N1 virus. What is common between those two viruses is the fact that it carries the H5 marker which is a prominent characteristic of the H5N1 avian flu, bird flu virus and is transmissible in a mammalian model system. What do I mean by that? There is a general opinion in the virology community that ferrets as an animal model seem to be similar to humans as far as transmissibility of influenza virus group members are concerned. All that means is simply that viruses that are transmissible in among between humans by droplets by aerosol are also similarly transmissible in ferrets. They cause a disease in ferrets that looks similar to the disease in humans, the normal influenza symptoms and H5N1, the avian flu virus has so far not been transmissible by aerosol in humans. The 500 plus cases that have occurred worldwide since over the past eight years or so have all been as a matter of contact with poultry which presumes a far more intimate and strong exposure to the virus than simply droplet exposure would provide. For the first time the H5 containing influenza viruses in both these experiments have become ferret aerosol transmissible. Now why is the ferret aerosol transmissibility of the H5N1 being seen as so dangerous considering that this virus clues are there in any case all around us. What makes this specific virus so dangerous? The simple answer to that can be provided from the Fuchsia experiment. The Fuchsia experiment takes H5N1 which is the bird flu virus. It passages it from one ferret to another and from one ferret to another in a situation where none of these ferrets were aerosol transmitting the virus. But eventually after I think about 10 passages the resultant virus that had I think two or three modifications in its gene sequence was actually aerosol transmissible in the ferret and was virulent kill the ferrets. Now you can make the simple leap which almost everybody who worries about the security aspects of this work is making which is that prima facie we have a bird flu virus that has an extremely high fatality rate as high as 40% that is now aerosol transmissible and therefore can spread in human populations and can cause pandemics. Though it is supposed to be WHO claims more than 50% fatality rates. One of the arguments has been that this is only among recorded cases and where you have actually sequenced what has been the causative agent and so on. But it is actually far more prevalent than this is shown by the WHO records. Would that be possible to argue that this is actually seen to be far more virulent than it actually is? Well it is certainly possible but I would argue that the relative virulence of H5N1 is likely to be correct. And what I mean by relative virulence is that it is more virulent than many other influenza viruses because exactly the same uncertainty about the denominator will apply to all influenza viruses regardless of whether it is H5N1 or something else or something else. So, if the same degree of uncertainty applies to the denominator then the relative virulence meaning that the numerator of fatalities being relatively high still provides you with a trend in which it is a pretty virulent virus. Now whether pretty virulent means it kills 40% of infected cases or 20% of infected cases 10% then becomes a matter of detail. One of the important issues that has been raised is that this kind of transmissibility being added to the virus in fact is a part of what the FINK report which started the NSABB that these are the kind of experiments which are dangerous which needs to be regulated which needs to be monitored publication needs to be again monitored and so on. Now do you think that there is any really any significance significant benefits who would get out of making this virus is transmissible this kind of research do you see is it as something that is positive in terms of trying to prevent it and trying to understand it or do you think it is something that the scientists are doing out of there just out of their need to publish papers and do more research. So, you know this notion that scientists are doing something just out of their need to publish papers and do more research is a little odd because clearly there is a large community out there not five scientists very large community out there which is interested in having these papers published that is why papers get published papers I mean if I simply want if I simply wanted to publish a paper I will I would put it out into cyberspace and it would be available to everybody are scientists doing that no they are not they are desperate to get their papers into nature into science and to that end they are trying to persuade as large a community as possible of peers and others that this is worthwhile. So, this notion about just wanting to publish needs to be taken in context especially in the age of the internet where if all we want to do is put things out into the public domain the simplest thing is to blog it such it let us be clear if you have a publication of course it has to your prestige of course there is other but as a consequence of that need you need to persuade a fairly large and diverse community that this is important and second value. So, what would be the value of such so again the fuchsia virus in this particular context provides us with an interesting answer to that question and that is H5N1 the original H5N1 is not aerosol transmissible we have been arguing for a long time that aerosol transmissible pandemic influenza viruses require an intermediate passage through for example pigs in order to do assortment between different influenza virus strains so as to create a large alteration in viruses so as to create a pandemic capability virus. Now H5N1 in the fuchsia experiments has undergone these two or three gene changes really very specific changes and has become aerosol transmissible. What does that say about our understanding of how the host virus relationship on a population scale operates in real life messy nature. So, what you are saying is that this understanding is important to fighting the influenza possibilities of the pandemic at the very least it teaches us not to take certain things for granted and to be perhaps even more cautious than we would have been if this information was not there is that not value. Now the question comes up of what the WTU experts have said that if you accept there is a value to the research then what NSABB recommends that only selected people should get access to this material how this virus is made transmissible and not others then becomes extremely problematic because then who decides what is who are the people who are worthy of the recipients of this what should be the mechanism of releasing it to them is science and nature the journals concerned do they have the ability to do it these are the kind of questions the WHO committee has raised. So, what do you think is the method then if you think there is a danger and there is a value what do you think the scientific community should do in order that the value does not get overwritten by the need for fighting what is called bioterrorism or the threat of possible bioterrorism. So, consider what the argued risks of this kind of research are one straightforward issue is simply a matter of containment you have dangerous viruses you need to maintain them and under appropriate containment because if there is an accident and if there is release then all sorts of terrible things can happen this is a relatively simple matter to deal with and nobody disputes that so called BSL 3, BSL by safety level 3, by safety level 4 containment appropriately monitored is adequate to deal with this. So, the real problem that everybody is talking about is bioterrorism what exactly do we mean by bioterrorism? We are talking about poisoning wells using mustard gas we pretty much done all of this been there done that we have decided some of us that we are not going to do this any longer. If that is how it is then all the information that is available of the old bioterrorism weapons is out there in the public domain why on earth is somebody inimically minded waiting desperately for a paper to be published in nature to indulge themselves in bioterrorism using modern weapons when old weapons will work just fine. The issue here is not so much to do with the bioterrorist as much as to do with our fears. Now our fears are to do with the flavor of bioterrorist of the day and every few years if not every if not more frequently than that our targets of whom might be an appropriate bioterrorist changes the axis of evil have a peculiar way of shifting angles fairly rapidly under these circumstances which government is to be exempted from the label of potential bioterrorist and which government is not. How do we decide in a global community of scientists who has connections that will eventually lead to this information becoming available to terrorists and who does it? Essentially you are going with the WHO trend of argument which is that there is really no point in trying to create the so-called filters and if somebody can do this kind of transmissibility by reading a paper he probably can do it much more simply doing other things. Now coming back to the last point that you had raised about the security biosecurity levels Canada has already said that H5N1 should be done only in biosecurity containment level 4 while most of the others are still sticking to biosecurity level 3 accidental release issues. Now it is also true that if you do it in biosecurity level 4 many much fewer labs than have the ability to do such research the research is valuable doing it in biosecurity level 4 actually makes it more difficult to do the research. So do you think level 4 level 3 seems an esoteric question do you think there is an appropriate discussion that we can have? We get into a level of technical detail you see remember that biosecurity levels as they are defined level 1 level 2 level 3 level 4 although they sound as though they are unitary definitions are in fact component melanges they have multiple components so you so it is possible to have in between levels between biosecurity level 3 and biosecurity level 4 for example just as there are levels between BSL 2 and BSL 3 which of these components is absolutely essential the components that go into BSL 4 which of them is absolutely essential which of them is dispensable these become issues that at a certain stage we are talking about people sitting down in the particular structures that we are in the particular laboratory that we are dealing with the proximity of the laboratory to other structures how near how close how big is the building what are the containment facilities therefore that may be needed in one and not be needed in the other beyond a certain point these are local ad hoc decisions that need to be made certainly BSL 3 is needed certainly BSL 3 with some care would I think be needed am I willing to argue that absolute extremely high security BSL level 4 containment is biologically mandatory my guess is that that is not the case my guess is that anybody who argues for BSL 4 is arguing not only from the biological containment point of view but also from the security containment point of view because BSL 4 level establishments carry with them also the security paraphernalia not simply of biological containment but of human malifies also quite possibility to restrict the number of teams working on the research and that would be clearly to see as far as possible for it to work as a dissuader I think this has been something that we need to follow up continuously we are also seeing various attacks coming on synthetic biology so not only on the question of justice transmissibility of the virus we will discuss this as further as the issues develop thank you Satyajit hope to have you again with us thank you.