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Hello again and welcome back to the Marketing Buzzword Podcast!
This is the podcast which helps you to understand what all of these business and marketing buzzwords actually mean, and how they can helpful going forward, and today's buzzword is "Machine Learning"
I'm your host Ben M Roberts and in this show I am the marketing bee in charge making sure I can get the right guests and ask the right questions to make these words and phrases make sense.
In addition, The Marketing Buzzword Podcast is now powered by Talkative. Talkative is a company that brings live chat, voice calls, video calls and co-browsing together, in one package. This allows you and your business to truly engage with your customers, offer quick and effective resolutions to questions and improve the customer experience. You can find out more at Talkative.uk
So, how does this show work?
Simply, you, the marketing bees let me know what buzzwords you've been hearing, and bring them into the marketing beehive. I then bring on an expert buzzword bee from the field, who helps us identify what these buzzwords actually mean, and whether they are useful or not. Essentially, I want to de-bunk or de-mystify these words and phrases to make the marketing jargon a little easier to understand.
I'm always keen to hear about the buzzwords you are loving or hating right now so please drop me a tweet to @roberts_ben_m or simply use #marketingbuzzword on Twitter & Instagram or if you'd rather you can go on the marketingbuzzword.com website and let me know through there, and take a look at the show notes from previous guests.
Then one final thing before we get onto this weeks guest . . . if you are loving the show, please feel free to leave me a review on iTunes! It really does help boost the shows profile and make it easier to keep getting on these expert guests.
Right that's more than enough about me. It's time to introduce this weeks guest! This episode's expert buzzword bee is the the beautiful and intelligent woman, Elizabeth Clark .
Elizabeth Clark is the CEO and Co-Founder of multi award-winning Dream Agility, an international conference speaker and bestselling author.
Dream Agility is a Google Premier Partner and one of only 35 Google approved Shopping Partners in the world. With 2 patents pending, their award winning 2nd generation cloud based Adtech sits between the clients website & Google/Bing/etc. It optimises data 'on the fly' and makes net profit related bid recommendations, delivering industry beating uplift for retailers, lead gen, and travel sectors.
Based in Ramsbottom, Paris, Atlanta, Melbourne and Seoul, Dream Agility remains at the forefront of it's sector – internationally. Often acknowledged for innovation, the company recently won the prestigious 2017 Global Tech Challenge in South Korea and were also named in the MEN's Top 100 Greater Manchester Tech Companies.
Always looking to develop their software, Dream Agility has the first ever cross-faculty Knowledge Transfer Partnership (research program) between Manchester Business School and University of Manchester, on an AI, machine learning/ neural networks enhancement piece for their platform.
Enough small talk . . . let's talk "Machine Learning"
Machine Learning Transcript between Ben M Roberts and Elizabeth Clark
Ben: Hi Elizabeth. And welcome to the podcast.
Elizabeth: Good morning.
Ben: Good morning. I am so excited to get you on and talk about machine learning. It's such a word and phrase that so used interchangeably with other words and it has so many different connotations and meanings. So I just really was excited, so excited, to get you on to actually bring back some clarity and actually define what it is and what it isn't. So I'm going to hit you straight up with the first question is, what is it and what does it not. Because I tell you what, I'm confused and if I'm curious, I know I'm not the most incredible person. But I thought I'd like, I've got a pretty good grasp of marketing and I still sometimes have no idea what it means so please help me and everyone listening. What is it and what is it not?
Elizabeth: Well, machine learning very, very simply put. It's just a mixture of computer science, economics and neuroscience. And AI, Artificial intelligence, is just something that does a process. It can do a thing and what's happening is people in marketing in particular are talking about using AI in Google. Oh yeah, we're using AI. We've got all this AI going on. We can really improve your processes and results with AI. Actually what they're talking about, It's just a few scripts. And the issue with running a few scripts is there's no intelligence there. And what can happen is they can layer up and layer up and layer up. So an example here, there was a client we looked at and they had an agency that was using AI on their account. But when we looked all they were doing was just compounding the scripts. And you start off with something that was, say the original big costs was £3.25 and there would be a big multiplier on that for London 25% on. That we'll put up it up o £4.06. And that'd be a morning so another 20% on and that would put it up to £4.87. And I'll tell you what, it's mobile, let's put it up another 10%. So all of a sudden, not bid, it's gone up to £5.38 that's a 65% increase. And we'd see these, we call them Frankenstein babies, we'd see them everywhere, all through accounts. Google's got no way to really deal with that. They don't have an answer for that, but the answer is certainly not layering up scripts and layering up scripts. It's not AI, it's the most basic thing that you can do and we need to stop calling it AI because it's confusing everybody.
Ben: And that's the thing. It's confusing to the layman, let alone even people who are working in the industry and it's one of those things. I just at a huge conference and they were talking about AI and machine learning and bots and all these different terms and how you can automate all these processes. And I'm sat there going hang on one second. On said machine is this and another said AI is this. But hang on, I could quite easily flip those round and almost. It almost sound like it's the exact same thing. So how do people know whether they are working with a company that's actually just layering on scripts or whether it is pure machine learning. How do people differentiate that?
Elizabeth: Well, you can start by looking at what types of people do they employ. We have a very small company and we employ 2 machine learning guys. One of them's got a PhD in particle physics and he's worked on the Higgs Boson. So those kind of people are generally associated with machine learning. If you've got lots of people who are google qualified, then not associated with machine learning. So the likelihood is they've got nothing going on that. We also work with Manchester University, we've got the first ever cross faculty KTP. It's the knowledge transfer partnership, just means it's a big research project. So we have one professor who deals with machine learning, one professor that deals with neural networks and he's helping us develop our, Dave projects. We tend to call things funny names when they're in production and the names stick and then we can't think of new names for it. So our visual AI product was called Dave. We've got another product called the violator. We got another project called the purger. It sounds dreadful when we're speaking to our clients, "if we just run the purge on you".
Ben: That sounds really incredible. Its sounds really worrying but incredible
Elizabeth: Haha. The way Dave works, so one of the big problems at the moments, but particularly with Google. I'm supposed to be speaking next week at SX in San Jose, but unfortunately as you can hear from my chest, I'm too ill to travel. So my husband's going to go out, my CTO, he's going out to San Jose and he's going to speak out there. It was one of the best, sort of awarded talks last time on robots and machine learning. Are the robots coming to take us over? Everyone's sort of quite terrified about it. The creatives don't have too much to worry about, but you know, if you're a sort of bog standard digital marketer, you've got an awful lot to worry about. So, we were looking at feeds at the moment, for example. So the big problem is feeds are difficult to generate, they are inaccurate. And the minute you put that into Google, you start showing for things that are irrelevant and you're paying for clicks that you don't want. You get everything, the performance has dropped. So within the industry, what we're seeing at the moment is, big google shopping campaigns going back in house and moving away for agencies. And agencies who traditionally had very good revenues. Google shopping is kind of king at the moment when it comes to retail and those revenues a diving off a cliff. So really big ones at the moment, Google has a thing amongst the premier partners, they're working with 10 premier partners who used to have great revenues and who are falling the fastest and they are working with another 10 premier partners who are growing the quickest. And we're one of those. So out of those 10 premier partners, the average growth rate. So at the top of the top of growing, on average, about 35% – 39%. And we're growing at 156%. So it just goes to show you. Google came in to see us and said, "What is your secret sauce?". The secret sauce is we're just not doing the stuff that Google tells you to do. We've got this layer of machine learning and AI going on. So, basically with Dave he can look at a picture and that he'll see that it's a dress, it's a t shirt, it's a this or that. But it's not that straight forward. So, the person in the picture. So it's going to see the person that's going to see skin. It's going to see a handbag. It's going to see. So it then, starts to work on competencies. In terms of, how confident am I, what I'm looking at. So it brings back all these terms to do with the products. And the idea is we can very quickly build a feed that is very accurate. So we can see it's address, we can see it's place. So, we can see it. So another thing is in different countries, they call it different things. So we have clients that work in sort of 20 territories. And in the UK, it will be a playsuit and in Australia, they call it a romper suit. So you also need to be able to change the language and if you've got to a younger person searching for something, they're going to use different terminology to an older person. So you've got all these things to consider when you're trying to build a feed that's as relevant as possible in order to serve on Google as cheaply as possible. And Dave does all those sorts of things and one of the things we find interesting with Dave is when he comes back with the results because it's looking at everything. So it might be a lady with a picture and she's got a top on and a pair of shorts. But it's a top we want to concentrate on and it's bringing everything back. So we do supervised machine learning, there's two types of machine learning, supervised and unsupervised. And the supervisor stuff is basically where humans checking, what the machine is telling us, to see whether that's correct or not. And then when he's being supervised, we were getting too much information coming back from the image, which is confusing for a human being because really we're only want to talk about the top, not the shores. So we're gonna want to talk about the top, I don't want to see terms relating to the top. And so we removed all those out and then a very strange thing happened last week. It was a picture of a model came on and then all of a sudden was a load terms came back, not relating to the product she was wearing. It was anal sex, porn star or porn magazines, the name of a porn producer. We're looking and saying, "bloody hell. What's going on here?". It was a bit of a surprise, but it's also looking at things the way people have been tagged on the net. So this girl has potentially been starring in something which is a brand reputation issue. So all of a sudden you've got, if we can find that information out then so can of the general public. And if you're a big brand and you've got a model who's very attractive, doing something for you. But she's also done very lewd in other films, you might not want that in terms of protecting your brand. So it's developed this, discovered a whole layer of other things going on that we weren't aware of at the time. And there were some websites associated with it, but nobody wants to click on them. just in case.
Ben: You've just dropped so many knowledge bombs are out there. I'm writing some of this stuff down because I said so many of these things I want to sort of drive in on. I think I want to start on that last one. And I think it's fascinating actually, that we all sort of know in this digital world, nothing's ever private anymore. As soon as you post anything online, even if you've got a Facebook account. Let's be honest, google, Facebook, whoever it is, knows more about you. Probably, you know more about me than I know about myself now at this rate. But it's like, where does, should people be worried about? Is it, should people be worried about our needs. So I know I'm going slightly off topic, I know bring it back into a marketing perspective in a minute, but is there a worry that people who are actually driving the change with machine learning that actually they are going to invade someone's privacy? Is there a worry about that and is that something that marketers need to consider in terms of when they're trying to adopt or build a machine learning platform or work with someone who has a machine learning platform?
Elizabeth: Well, it was a surprise for us. We weren't expecting that kind of information to come back. But anything you put out on the Internet is all typed up by somebody and at some point it will come back. So,the response to that is don't put it out there if you don't want it coming back at some point, don't put it out there. We had no idea. It certainly wasn't saying we were trying to look for. If somebody said, here are all our models, try and find the ones that have done porn movies and it's not something we would have thought about doing. And then we have to also test actually was she in porn movies or was it something to do with the way she was looking or is it associated with somebody who looks a lot like her? So it raised a lot more questions and then we had answers for. Then we said, well, should we find some images of porn stars and put them through the image recognition to say, see what Dave says about it. But we decided we just leave that, we'd park that one there for now. But I think the answer to all these things is, if you don't want somebody to know something about something, just don't stick it on the net.
Ben: And then I think that's an incredibly good point generally. Whether on this podcast or anywhere else in life. I think that's just a general great, great rule to put up there. If you don't want other people, don't tweet something because someone will say. It will be ultimately saved by a robot or someone somewhere and will always come back and haunt you.
Elizabeth: Years ago they didn't have huge twitter warehouses, data, houses, of all the tweets. In order to do all the sentiment analysis, you can think, you can try and retrieve things and put you can't. It's not easy at all, Once it's out there. It's out there. So just don't do it kids.
Ben: Yeah. I couldn't agree more. And then when the, I've got so many points, I've been writing down from everything you've been saying. So when the other things that sort of came to mind is, you talked about sort of the supervised versus unsupervised machine learning. Now, if you implement, sort of a pros and cons approach to either one of those. Now, if you were to have a supervised approach to machine learning, does using machine learning actually save you time? Or is the time almost spent equally? But obviously you get better results than if you were to do this all manually, so do you know what I mean? Because you actually have to spend the time putting all the algorithms together, the process, actually monitoring how the machine, how the bots going trawling through everything and then having to check everything yourself. So you can see that would be quite a time consuming process, but it's still saving you time on doing it manually.
Elizabeth: There's absolutely no way we could do this stuff manually. Some of the feeds we've got anything from a 1000 products in a feed to 2500000 products in a feed. A human being is not going to be able to go through and look at all those images. But so what happens is you train the bot as it goes along. So he's looking at that, looking at the images, reviewing the images. We're saying whether they've got it right or not got it right. And it learns from that. So you don't have to tell us again and again and again. So, we've got this big neuron net going on behind what we're doing. So it's learning everything we're telling it so it doesn't have to be applied again. So obviously that's going to be a rigorous process because we don't want a top coming up with porn star at night at or anal sex or something like that. So, it has to be supervised in that respect. But if you look at the unsupervised systems, they still have a level of supervision over the top. Because there's a big debate about, you know, are we're going to build bots and are they going to kill us. And also driver-less cars, you know, the car is taking in so many data points at once, way more than a human being ever could. But then, you have to make the decision if it's going to crash, does the car choose to crash into the old lady or does the car crash into a lory or something like that. And that's where the layer of supervision has been placed over the top of it by humans can help make those decisions. So that the machines making most of the decisions most of the time. But when it comes to a critical things, that layer of supervision and that helps them inform those decisions.
Ben: It's funny, we literally had almost a really identical conversation in the office this morning. And we were talking about how with driverless cars so basically we're an office with a load of devs that are building our products. And they talking about actually how, with ethics and stuff as automated driverless cars come come to pass. If a developer, for example, puts a couple of lines of code in and that car ends up killing someone. Can have a developer then be done from manslaughter because they've entered a line of code in it. It is a fascinating world and I didn't have the answer for that, but something I'm just got my brain ticking overdrive. I need to find out the answer to it.
Elizabeth: Well, I mean it wouldn't be so much. The developers put a couple of lines of coding because the machine is learning all the time. You put an input in and there's different layers in the middle and then as an output. So a developer could put something in there that's a bit dodgy, but the machine would realize it's just a stupid developer, right? It's not going to be hanging on one line of code
Ben: Well, that was a simplistic example, but the principle of it was where we're going in the future. But then moving, so a little bit further from that then is, with machine learning, is it something that anyone can do? Is it accessible? Or are their really quite big barriers to entry? So if a small medium sized business would want to try and develop some of their own machine learning or programs, how technically savvy do you have to pick? So I'm assuming, it's not something that you couldn't just pick up and run with.
Elizabeth: Well I've got my colleague, my VP of technology, sitting across from me going, "Oh yes", and nodding away at me. But then Daniel's very clever. So we like say, we've gone to the lengths of actually getting involved with the university because we want the best people around on this. So we want the support of the university, but we've actually, both Daniel and my CTO Glenn, they went and got themselves as massive book. A massive book with tiny writing in and they started reading it. And when the two guys being university came in, we produced this book. "We're reading this, we're up to page 700 and whatever". And they said, "Oh yeah,that's what we actually teach on that machine learning course, but we only use a couple of chapters of it". So already we're streets ahead of what they're teaching university. But there in lies another problem. So, if you'd gone to a machine learning conference a few years back and we've just been full of academics. But now when you go, it's full of people from the big four. It's full of people from Facebook and Google. We're going to have a problem because the likes of Google and Facebook are buying up an entire departments of machine learning people. They're just taking them all, hiring a lot of them and if they've hired them, who's going to teach the next generation? So, you know, there's a disparity going on here. It's not very fair, but the guys who got money could just sweep it and by all these people up. We're very lucky at Manchester. We've got one of the biggest machine learning and departments in the country in terms of the experts and people who've got round here. But then, you know, Turing started up here and went to the computer. So we've got this huge heritage and long may it last. But yeah, in theory anybody could do it. But certainly when I was watching Glenn read the book, I had no desire.
Ben: I think that's an incredible point in all areas. Not even if you look at things like construction, engineering, business. There's so many things were academia hasn't quite kept up with the real world. And this is when we're almost like academia was a head of a practical application. Now practical application and capitalism is almost overtaken the academia, which is almost a bit bizarre in modern world. But it's like, how does. I lost my train there.
Elizabeth: Happens all the time. Just have a moment.
Ben: We're back. We're 100% in the game now. Right, so is there a risk then if machine learning almost petering out? Or they're being a real stunt in the development of machine learning because of these big tech companies buying out the almost the teachers of the next generation? Are we going to hit a point then potentially in your opinion, where we suddenly go because the rate of acceleration is huge at the moment. The growth and the development speed as with technology is incredible. Are we gonna are we close to a plateau or do you think we are still a fair way away from a plateau in terms of where we're going with machine learning?
Elizabeth: There's not enough companies at the moment want too. I think people would like to employ these people in house, but they don't really know what to do with them or how you do it. Because certainly when we started down this route we said, this is such a massive problem. We cannot get the best quality feeds we need and for human being to do this is just ridiculous. But the only way we're going to have to do it, it's actually by looking at the image. And it was a big decision to make because we got very good links with the university anyway. And we had a chat to them about it and said, "is there something you could help with?". And they said, "well, yeah, it's definitely something that can help with". But there's two, you know, it's half neural networks and half machine learning. And we're, like I said, we're very lucky that we've got those resources in Manchester, say they're happy to support us. But we found actually that on doing the project, it's the more, some of the commercial side of things and more the economic side of things that are actually driving the priorities. So they're looking at solutions. How do we solve this problem? Blah blah blah. And we're saying actually, but the commercial application of this, we just want it to be mainly right, not a 100% right. It's just to be mainly right because we don't live in a perfect world. You know, when it comes to advertising online is have you got the stock, in stock. Is it at the right price? So we developed this other bit of a huge bit of kit that's coming out imminently. It's basically a big dashboard. So when people ring us up and say what's happening to my sales have dropped off a cliff, what's going on? And it's always the 80:20 rule. So I mean people themselves can do some very, very basic stuff. So if you parade through everything, then you have a good feel for what's going on. So you look at the best selling products annual, so look at the products that drive at the most cost and you get a good feel for what's going on in business. Because nobody can look at that many skews at once. We're looking at that. It's never our technology because to start with when you build something, you think, it's the platform it's the platform. I don't even realise it's not a platform at all. It's always with the retailer. And it's either because they've run out of stock and they don't know they've run out of stock because the digital marketing guys, they're getting slammed all the time. You've got to advertise, you've got to advertise. We do come across some digital marketing people who we've shown our technology to. And they have said, " I like to work in real time". I said, "well, you might like to work in real time, but Google isn't working real time". You'll have an attribute window. And your attributes window could be a fast fashion. It could be sold to three days, something like that or longer. And like, "no, no, no, no, I know when things are selling". I think, "you don't, you're clearly an idiot". They've got no idea when things are selling because they'd no idea how long in terms of attribution, what's actually working, what's not. So what they're doing is just guessing that sitting there and pressing buttons and guessing. But what we're looking at is actually has the product been in stock because it might be in stock now, but it may have been out of stock. So the dashboards show that that product's only been in stock 45% of the time, so the other the 55% of the time, the best selling products have been available or not been available. And that can have a massive impact on sales. And then the other thing that impacts it is pricing. So how's pricing, have you been competitively priced and has it now completely dropped off a cliff. In which case we can send them an alert to say we're going to drop the bid on this. Because you're not competitively priced anywhere where all you're doing is harrowing money and is haemorrhaging your sales. And that's not a good situation for you. So we're using the machine basically to advise human beings of actions that they can take. Actions that they would never have been, it just wouldn't been possible for them to go and look at all that amount of data to establish that. And that's where we really need to use machines to our advantage, we've got a skill shortage in this area at the moment. That's going to flip on his head very shortly, once everything gets out there and everyone's sort of using machine learning as standard. And they're using platforms as standard. They're using tech as standard and the application of humans reduces massively
Ben: So in terms of the future development then. Where else is machine learning currently being applied or wherever the big areas of growth in terms of machine learning being used in general businesses. We focused quite a lot onto advertising and e-commerce for. What are the other applications? So I know there are huge amount. I'd be interested to hear your thoughts on where else machine learning can be integrated into businesses.
Elizabeth: Fraud is a good place to look. What's going on in how to spot patterns in banking and things like that. Where you do a thing where you've done three micro-payments and all of a sudden your credit card stopped. They're looking at the performance of your account, where you normally do things, how you normally do things. Is there anything looking strange in your account? If you just had a rule that said if you have three tiny little micro payments go through, we're going to close the account down, then that would be lots of unhappy people. Particularly if you make lots of micro payments. So it's using that kind of data and personalising it to you to make informed decisions.
Ben: I think that's a really incredible point actually. Machine learning, I think it can be quite easily construed as it all being big data, big volumes. Actually, machine learning can be applied to almost to the individuals to make sure that businesses can tailor exactly what they're offering for the exact individual. So the right product for the right person at the right time, the right price point, in the right place. And it's that sort of application which people seem to almost neglect and, or don't understand. They can offer that power.
Elizabeth: Yeah. And you're exactly right there. So you hit the nail on the head in terms of product recommendations. You go on a website, you pick a pair of trousers. And it says here are five more trousers like the pair you've picked. I just picked a pair, I don't want another pair of trousers. Well, how about I shirt to go with it. I don't like this type shirt, oh they don't like those types of shirts. Maybe they'll like these types of shirts. Is that sort of intelligent learning about you and your behavior while your on there. I think that also, you know, if you look at things like search boxes. Google pulled out search boxes last year, on site search. And nothing's really stepped up to replace it. So when we're looking at feeds, we're looking end to end. So that data is current. People, when they go onto websites, they're expected to be able to search the way the web designer wants to make them to search. And that's a horrible experience. That's why Google is so popular. There's nothing other than a search box, no faceted nav that was hated that went years ago. So, you know, we need to be looking at giving people the best experience possible. And in your search box, if somebody searched for certain thing, you want to make sure that: A)It's in stock; B)It's a good price; C)It's the right size and we're not doing that at the moment. But it's completely possible because we have the technology to do it. When we run a experiments on clients, such as search boxes, we've been able to discover, you know, hundreds of thousands of pounds worth of uplift. Just by using the feed rather than using such technology on its own. So there's all sorts of applicationsout there, for people to make more money, have better experiences getting the right thing. If you look at the likes of Tesco and Debenhams. They've loaded themselves up as marketplaces and it's really hard to find anything in there anymore.
Ben: I get it. Again, it's almost like it almost helps negate that paradox of choice. Where you've got so many products out there, so many companies, so many offerings, too many choices, even just down to I want to dress. And it's at, well I'm not saying that I want to a dress. But in the context, I did want to a dress, there's nothing wrong with that. If I wanted to dress and what sort of style. What do I want. Straps, no straps, blue, black, gold or don't even get me on. How actually to ask you about that, how your machine learning copes with things like blue and black dresses in white and gold anyway? But yet that reducing that paradox of choice, where people are going, what do I want? I just want to dress, but what colors, sizes, shapes. Whether it sort of tucks everything in. Whether it has holes in it. All these amazing sort of fashion trends. Actually it's really difficult. I mean eight sauce is a huge example. You go in there, look for my girlfriend to get her something, bloody hell. I stared at it for five minutes when I can't, I can't do this anymore.
Elizabeth: It's overwhelming, isn't it? In terms of the point you made on colour before. When people searched for colour, they searched for very basic terms and the issue then have is the colour of your products. How do you get those two relate to those very basic terms? So we built a massive colour library using all the tones and everything. So actually the machine can look at it and with a degree of competence, say which colour we're going to match this into. But again, you know, you might have an older audience who might call green aqua or pink Fuchsia. Because that was a fashionable term when they were younger and they continue to stick with those terms. In which case you can relabel them and do anything you want. So it's all, it's all personalised and it's a, you know, machine learning is great. I love it. It will remove all that sort of overwhelmingness from people. I think if you just want to see the blue one. Yeah. Did you realize that paint, you know when they've all got these crazy names for cans of paint?
Ben: Yeah. Like rat brown and sunset orange and stuff.
Elizabeth: That apparently is a law. You're not allowed to call, it's an IP thing. You're not allowed to call one paint colour, the same thing as another paint colour. So every paint colour has to have a unique name. It's just particular to paint. It doesn't apply to carpets or anything like that. I had no idea where it came from. But when you're trying to sell paint online and somebody wants yellow paint and you've called it moon dust, whatever. It's very difficult because you've got to call it something different to every other paint that's ever been produced. Who invented the craziness, blah. Again, you could just plug that through Dave and he'll tell you what exactly is. So that when it shows, it will show in for the, for the correct thing. Because obviously when Google classifies things, they have these hidden fields, for the colour and material and things like that. So go in there and actually show for the right thing. So you're gonna in breach of calling your paint the same color as somebody else's pain.
Ben: It was amazing and it is one thing that people have taken away to forget all the machine learning and forget all that. Just know that you can't call the same paint, two different things. So the final thing I'm going to quiz you on, though. It's almost like a bit of fun just to finish this talk about machine learning is, how does the machine differentiate? We knew there was a big thing between whether that dress was black and blue or white and gold, everything. How would you want machine be able or do with machines be able to do that? Because that's almost like a human perspective on what it was. How long would the machine cope with things like that that are all sort of almost perspective and people will use it completely weirdly. Did you join some? I'm trying to.
Speaker 2: I'm just saying that's the human problem. That's not machine problem. The machine. We're looking at it and use confidence intervals to decide what color it is or isn't, so they will suffer from perspectives
Ben: what it was blue and black anyway, but that's. That's the end of the dressing, but it never stops. It never stops. Anyway, and before I let you go because you've provided some incredible insights. Real some real clarity on what machine learning is, but I can't let you go yet because I need to find out what are the buzzwords, marketing buzzwords or business buzz words and phrases you either loving or hating right now. What sort of really getting on your gears are? What is one that you are absolutely loving at the moment?
Elizabeth: When I'm hating it at the moment is snowflake. I was speaking at a conference yesterday or international women's Day and the term came up and we've actually discussed it. Anime thing before I go home, because I knew this term was coming up and I wasn't sure whether, um, it was something that meant the same thing to all people as young workforce here. I'm, I'm the mother of two of them. Um, that 23 and 21 of the ages of my two kids and working the business. 10 only five, so he's not coming out, although he did ask for a car for Christmas so he come to work with his big brother and sister. But I sort of said to them, what do you make the term snowflakes, you something you find offensive, but one of them, so just looked quickly at me, mom, I think that's the term for the white weedy guys in jail.
Elizabeth: I said, how would you know that she's up and watching prison break. Oh, excellent. So, um, are informed, you know, media thing, but it is a, it's a term that's being bandied around a lot at the moment. So snowflake feminism, um, Jennifer, what's the facebook wearing that dress out in the cold the other day and all the feminist started on us saying she was doing a really bad thing for women by going outside in a beautiful dress and she said, you know, I choose to get outside in the beautiful dress. Um, then that's me, I, you know, stopped being sexist and then it sort of evolved into a snowflake sexism and it's difficult to know where to go with it. But to me, I think it's, it defines a generation of people who've been brought up with a sense of entitlement that going to university where traditionally you went to university to, you know, spread your wings, it's going with your parents get drunk every night, but up dats and now it's a place you go where people don't say anything offensive, they have safe zones, everything's OK at these poor people are just not going to be prepared for the workplace at all because it's just not like that here.
Elizabeth: Um, so that's the one I would like it to settle down and to actually mean something in particular. So if I'm calling someone up snowflake, I know that I'm really insulting them or I know that it just means something.
Ben: Yeah, it's weird, isn't it? And it gives me is when there's. Tim's almost like out of the podcast is try and bring back some meanings, but snowflake is one that almost has almost so many connotations and I've seen it being used in that sort of prison, that prison scenario before. But I've also used it to her terms. No, no, no, no, no, no, don't, don't, don't, don't make me have a bad reputation on here. No one is snowflake generation in terms of, um, in terms of people just in like a right to be insulted by of things where they feel like they can just, uh, they've been to university, they just insulted by everything that everything's a drama. But I also look at from the other plan to go, actually this is a generation where they funded for the first time people are going, no, it's just not OK to be racist to someone and that that would make me a snowflake because I don't find a black jokes.
Ben: Funny or is it because then I think it's, it's a fascinating subject and one that I maybe maybe I can address on the, on on the podcast soon if it becomes more used, more and more in the marketing or business world are really good ones come up pretty well. Thank you so much for coming on today, Elizabeth. It's been an absolute pleasure, so you're given is just be absolutely incredible. I mean I've made incredible number of notes myself and I think it's, it's a fascinating topic and one that I think is only set to get bigger and bigger and even more meaningful impact upon the marketing and business space. Thank you very much for. Thank you.


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Has it ever happened to you that you are scrolling and stalking people on a social media platform and find a post that makes you rack your brain. Like whatttt?! That's what I saw. Sigh! It is something related to women and girls going nude.
An encounter with a post
I recently encountered an account on social media that belonged a girl who attends the same college as I do. Her last post's caption was conveying that she had posted it because it was very much liked as a story, by people. I don't know what kind of people liked it or it was just something she imagined. I hope the latter because after reading the post I was so shook that my impulse was to hack into her account and find "those" people. After all where do we find such people?!
Okay, let me reveal the mystery. The post went something like-
"Girls are going nude all over and talking about respect and dignity, not so cool. Trying to be at par in the gender race, fine! Trying to go nude and gaining respect, not happening!
If you want to show you curves and your back but not your tits. Doing that is equivalent to a man showing his private parts in public".
My Impromptu Reaction
Instantly after reading this I felt two things. First, a twinge in my breasts since they were shattered after realizing that this has said by someone who bear their friends, the other pair of breasts. (God save them! :P)
Second was pity. I felt immense pity towards the girls who wrote this. Since she had no idea what she had written and moreover, what she conveying to other people. And one can't blame her as she is simply hit by the pseudo writer-slash-blogger-slash-"bold"-girl syndrome. No worries, it happens. I understand.
Now let's get down to business (after completely absurd explanation of the scenario). She after all had somehow started believing that nudity and respect are interrelated. May be they are but not in the way she described. And it's not about her. It's about every person, every girl who interprets the concepts like feminism, anti-sexism and other –isms in their own way.
My justification for women going nude
As far as I have observed, girls who go nude either do so very casually on naked beaches et cetera where they are judged very rarely or because they want to convey the world that their body is their own property, not somebody else's like that girl to comment upon. They are free to expose or cover any part of their body they like without being judged ruthlessly by others. And then people read such posts, other boys and men read them. No one knows how they will take it in their minds or we very well know how they do.
What a labyrinth it is. As much as we are trying to detangle the misconceptions about the freedom of a woman's body and more importantly their minds, we are getting more trapped inside a similar spiral. Before making men understand our problems, we have to make our fellow girls understand the true essence of such acts. It is high time that women stop shaming or degrading other women. Even if they find themselves incapable of supporting them, then they should at least try to not become an obstacle in other's path. Peace is all that is required to resolve every issue.
Otherwise there will be more perceptions than then there are people and many more mouths than there are minds.
And then I plead to these bold and beautiful women to understand the grievance of my girls always trapped inside a tomb like suffocating, available in different shapes and fabric structure preferably called a bra. They need freedom! Yours too. *Wink*
Don't you agree?
Okay, so that was my opinion and I would like to know yours. Whether you want to appreciate me or yell at me, use the comment section for it.
ⓘ Want to publish your startup or branded story? Submit your details here. For all the latest news related to startups in India and MENA, follow us on Google News, Twitter and Linkedin, and like us on Facebook.

subset: commoncrawl


text: Nels L. ClangFeb. 12, 1934-May 7, 2019Nels L. Clang, 85, of North Platte, passed away May 7, 2019, at North Platte Care Center. He was born Feb. 12, 1934, to Fred A. and Ellen (Pettis-Tyson) Clang at Broken Bow.He graduated in 1952 from Anselmo High School. Nels served in the Army from 1954-1956. He was united in marriage to Loretta Kieborz, May 29, 1960. To this union five boys were born, Robert, Joe, Daniel, Ronald and James. They moved to North Platte in 1968 where Nels taught heating, ventilation and air conditioning at Mid Plains Community College for 33 years. He also owned his own HVAC business in North Platte for many years.Nels enjoyed music at all levels. He played for dances at the senior center starting with Butch Kilmer Band and ending with Golden Classics. In 1976, Nels and his Uncle Charlie Pettis, were chosen to represent Nebraska at the Smithsonian for a Bicentennial Celebration. He loved Blue Grass music, playing with the Sandy Rivers Boys for 10 years. He was inducted into the Nebraska Country Music Hall of Fame in 2013. Nels was a master luthier, working on all musical instruments. He belonged to the old car club, building his late 1920's Dodge Brothers car. He enjoyed hunting and taught hunters safety courses. He was an active member of the Wesleyan Church and most recently Bethel Church. Nels lived a full life and everything he did was geared towards his family.He was preceded in death by his wife, Loretta; parents; and sister, Wanda Seevers.Nels is survived by his sons, Robert (Judy) Clang of North Platte, Joe (Yvonne) Clang of North Platte, Daniel (Tamara) Clang of Greeley, Ronald (Marjorie) Clang of Colorado Springs, and James (Stefini) Clang of Broken Bow; grandchildren, Larry, David (Tina), Jamdan, Aaron (Sara), Caala, Emma, Matthew, Renee, Timothy, Jonathan, Benjamin, Brandon (Nichelle), Tasha, Abigail (Camron), Guydon and Charlie; great-grandchildren, Gavin, Baylee, Rowan, Fynlee, Joseph, Parker, Brody, Miley, Ella and Hazel; brothers, Fred (Laura Mae) Clang of North Platte and Don Clang of Denver; sisters, Vera Veith of North Platte and Clara (Jack) Connely of York.Online condolences may be shared at www.carpentermemorial.com.A memorial has been established in his name.Services will be at 10 a.m., Thursday, May 16, 2019, at Bethel Church, 2700 W. Philip Ave., North Platte, Neb.Burial will follow at Fort McPherson National Cemetery, 12004 S. Spur 56A, near Maxwell.Visitation will be from 1-7 p.m., Wednesday, May 15, 2019, with family receiving friends from 5-7 p.m. at Carpenter memorial Chapel, 1616 W. B St., North Platte, Neb., which is in care of arrangements.


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|"Cancelled Game"
This article is about One Week at Flumpty's, which was cancelled by Jonochrome. Please note that no official game can be played.
For more information go here
Lasers were a planned mechanic that were to be added in One Week At Flumpty's before its cancellation.
Functionality Edit
The lasers would act as vents from Five Nights at Freddy's 3, as you could use them to temporarily block or trap characters, depending if the hallway is turned or not.
Advantages Edit
- They trap characters.
- They also stop characters from reaching certain rooms.
Disadvantages Edit
- It uses power.
- After a while, the door goes away.
- You can only use one laser at a time. Even pressing laser buttons on the office counts.
- Easy to Forget. (You might not remember to turn the lasers off, and that is a lot of wasted power)
Trivia Edit
- The lasers can easily be abused by trapping a character and as soon as it stops you can turn it back on.
- The lasers are useless since there is no way to win or lose the unfinished game.
- The Lasers are supposed to be present in The Office, however, they were not implemented by the game's cancellation.
- The lasers were also were not very good, as most of the time, Birthday Boy Blam would just go in those rooms anyway.
- This could just be like this due to the game being incomplete.
|Game Mechanics
|One Night at Flumpty's
|The Office • The Doors • The Clock • Monitor/Laptop • Night • Game Over Easy
|One Night at Flumpty's 2
|The Office • The Clock • Monitor/Laptop • Night • Game Over Easy • Vents • Hallway • Light Switch • Exposure Meter
|One Week at Flumpty's
|The Office • The Clock • Monitor/Laptop • Game Over Easy • Photography • Lasers • Rotatable Hallways
Community content is available under CC-BY-SA unless otherwise noted.


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Bed Bugs Treatment Melbourne
Sleep tight – don't let the bed bugs bite. This is not just a good night's wish; bed bugs can in reality rob your night of a peaceful sleep! But worry no more because Pest Disturbers Pty Ltd are here to provide their clients in Melbourne effective bed bugs treatment so they can enjoy a relaxing and rejuvenating night's sleep!
Are Bed Bugs your Bed Mates?
Bed bugs are usually active in the night and they go on about doing what they do while you sleep, unaware of their presence. Bed bug bites seem quite harmless in the beginning since they do not cause much pain initially. However, as time passes by, the bites become a source of itching temptations and that's when they begin to hurt.
If you are not sure whether you require bed bugs treatment by us, here are a few signs to look out for, which are a clear signal that you need to give us a call:
- When you go to sleep itchy spots free but wake up with different spots on your arms, legs and other body areas that begin to grow into itchy spots;
- When your bed has suddenly developed an unusual kind of unpleasant odour, it could be from the bed bugs glands;
- When you see small blood spots on your sheets, bedspreads and pillows that you cannot figure how they got there;
- Small evidences of eggs, excrement or faeces on your bed, pillows and sheets. Chances are that they could have been left there by the bed bugs.
Bed bugs are great escape artists and experts at hiding from your eyes. They can usually be found hidden in your mattresses, couch cushions, bed boxes, bed frames, bed headboards and other similar places. Their bodies are teeny tiny, which is why they could have remained undetected by you till they spread out their modus operandi and became a problematic pest infestation!
Bed Bugs Facts
Whichever area of Melbourne you are living in, do not get fooled by the small size of a bed bug and think you can do without bed bugs treatment. Bed bugs are equally annoying and dangerous pests. Their size allows them to occupy the smallest of crevices in your home and then spread out in all your rooms and gain access to your entire home. They can also be found hidden in the fabric of your furniture.
They feed on your blood, mostly while you are asleep. They attack any exposed area of your body and create itch spots on your skin. This makes your face, arms, hands, legs and feet victims of bed bug attacks.
A bed bug bite looks like a small bump on your skin and you may dismiss it off as a mosquito bite. Normally, one does not take the bed bug bite seriously since it is painless. You can get rid of the bump by applying a prescribed ointment if it becomes too itchy or painful.
Bed bugs are nasty and children are well justified in being scared of them! If you are not sure whether your home is infested with bed bugs, our team of experts can survey your property to study the signs. In case you do have bed bugs in your home in Melbourne, we will get rid of them with our top quality bed bugs treatment. So just give us a call and handover your pest worries to us at Pest Disturbers Pty Ltd!


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Annette Beck-Sickinger
University of Leipzig
Insights in the Binding mode of Peptides, Activating G Protein Coupled Receptors
Peptides hormones play an important role in the regulation of manifold activities in the body. Many of them transmit their activity through G-protein coupled receptors, GPCR, which are among the most promising drug targets nowadays.
By means of ligand modification, receptor mutagenesis, NMR spectroscopy of recombinantly produced receptors and molecular modelling, we have identify the ligand binding site of agonists and antagonists of peptide GPCRs. Furthermore, in combination with X-ray crystallography, cell-free receptor expression and photo-cross-linking we identified the different binding modes of peptide agonists and non peptide antagonists, as well as different downstream pathways.
Knowing the specific binding mode allows the selection of appropriate sites for chemical modification of the ligand, including fluorescence labelling, lipidisation and PEGylation, which significantly modify the activity of the ligand, and leads to effective compounds in vivo. Current application expand the direct effect of the peptide as drugs but allow using them as shuttling systems for intracellular targets, for example in cancer or metabolic diseases.
Lecture Images


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'#WeDontKnowYou': Mariah Carey Breaks Social Media Silence Amid Breakup Rumors
The star has had several public appearances since her rumored split from her Australian billionaire beau
Mariah Carey isn't letting her breakup with fiancé James Packer get in the way of her Halloweekend. But she has finally broken her social media silence — sort of.
The star, 46, took to Instagram to show a photo of herself dressed in a cleavage-bearing black lace-up top and sharing a tight embrace with manager Stella Bulochnikov.
"#realfriends who don't read Woman's Day #wedontknowyou We love you #Australianlambs," Carey captioned the photo.
In the post, Carey is referring to the Australian magazine Woman's Day, which reported on her breakup from the Australian billionaire and with an article titled, "IT'S OVER: James Packer dumps Mariah Carey." The article also includes rumors about Carey's alleged wrongdoings in the couple's relationship.
She makes it clear, however, that she loves her fans — better known as her adoring "lambs" — from Down Under. Her hashtag "Australian lambs," refers to her loyal followers living in Australia.
While sources told PEOPLE that the pair actually split last moth during a vacation-gone-wrong in Greece, Carey gathered together her friends, including the backup dancer Packer was reportedly jealous of, for a night out at Nobu on Thursday. Carey was spotted again on Saturday night with the same backup dancer, and the two got dinner at Los Angeles' Catch restaurant with a group of girlfriends. The star opted to swap hands and wore her $10 million engagement ring on her right hand.
After the end of their two-year romance was announced, reasons for the breakup have been swirling. A source close to Carey recently told PEOPLE the split was directly related to the mogul's mental health.
"James has not been in a mentally healthy place," the source said. "His behavior was not a desirable situation for Mariah so she unfortunately had to leave him."
RELATED VIDEO: Looking Back at Mariah & James Packer's Whirlwind Romance – and Her Epic Engagement Ring!
A source on the Packer side refuted the allegations, however, telling PEOPLE that it's "typical Mariah to just twist things that don't sound good to her. They split because she has issues. James is definitely an oddball, but a brilliant great guy. To put her issues on James is ridiculous."
"James is very private, and doesn't need the media to be successful," the Packer source said. "He doesn't want to be a part of Mariah's reality show."
A source close to Packer adds that the two haven't spoken since the breakup news and that the Australian businessman is focusing on his work.


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Workshare launches new Transact interface, the innovative transactional collaboration technology
Today marks the release of a brand-new interface for Workshare Transact, the innovative transaction management application bringing organization and efficiency to legal deals. Supported by Workshare's powerful comparison engine, Transact is being used internationally by top global law firms including Clifford Chance and Simmons & Simmons.
The new version has been designed to deliver a faster, cleaner and more intuitive process for both legal teams running Transact workspaces and external participants. The application has been completely rebuilt, providing stability, security and flexibility across the deal process, and with new technologies that future-proof Transact for the accelerated development of further capabilities and integrations going forward.
Immediate improvements within the new Transact interface include:
- The introduction of deal dashboards so that everyone can quickly understand what's going on in the deal.
- The "collapsed" checklist view, which enables participants to easily scroll through the entire checklist, giving a unique overview of the whole deal.
- Detailed content is now provided within clever pop-up windows that appears over the top of the checklist, leaving users in context in the checklist as they work.
- An updated and improved search/filter function giving you a fast and thorough search of the entire checklist and providing matches against all text fields. Never miss a keyword again!
- Comprehensive audit logs now track every user action, providing a complete electronic record of the transaction for long-term storage.
A checklist generator has also been added for the fast creation of Transact workspaces from CP schedules drafted within the principal deal documentation, typically reducing time spent on the checklist creation task from around 2 hours to around 20 minutes.
Barrie Hadfield, CTO of Workshare, commented: "We really looked at what people are having trouble with, understood all those key workflows, and built a simple and elegant solution designed entirely around the user. I'm proud of what we've achieved and can't wait to see where we take it."
Owen Oliver, Product Manager for Transact, added: "Customers that have implemented Transact are now able to see the long-term benefits in terms of efficiency, write-off reduction and ultimately profitability. The new Transact interface gives us a great opportunity to maximise those benefits for our customers and the transaction community into the future."


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Genres Accepted: Flash, short story, creative nonfiction, and irregulars (genre-crossing writing)
Medium: Digital (2/year)
Established: 2009
Tagline: Ice Crystal Rain? Why don't you just call it Sleet?
Payment: None
About: Sleet hails from the Minneapolis-St. Paul area. We love language and the written word, and we welcome both the beautiful and anti-beautiful.
Sleet seeks the unexpected. Make us laugh, cry, think. Our crew possesses a wide variety of tastes and styles, from classic to center to edge, but it is craft and passion that drive us.
Calvin Connection: Calvin grads Bethany Tap('12) and Jake Schepers ('12) have both published in Sleet.
Hekman Availability: No, but full magazine available free online at Sleet's website


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This morning my personal trainer…okay…so she is not really my personal trainer..she is on my "netflix of workouts" and is training thousands of other people online at the same time…but I feel like she is my personal trainer when I'm working out in my living room….well this morning that personal trainer said, "Let's train the quit out of you."
That is a theme I've been hearing often this week: in my audio book I'm listening to as I chauffeur all these minions around (Girl Wash Your Face), and again in some training I'm doing with a new nutritional mindset program, where Ilana is teaching us coaches how to change those emotional eating habits we all struggle with.
Everyone struggles to stick with things. It's easy to start, then fall off, then start again. We are quick to set high goals, start a new plan, pump ourselves up, then before we know it, we fall back to into old habits, habits that have been emotionally ingrained for years and years. That's just our pattern. That's just what we do.
We have trained ourselves without trying to in so many ways throughout our lives. Maybe when you go to your favorite restaurant, you've ALWAYS gotten the amazing french fries they have with your meal, or you ALWAYS binge on the cheddar biscuits before your meal, because, well, that's what you've always done. That's your habit. That's what you and your mind expect when you go to that particular restaurant.
What happens if you order a salad instead of the fries or ask them to hold the biscuits? IT WILL FEEL WEIRD AND AWKWARD! At least the first time. It will be hard to say those things to the server. Yet, if you just do it that one time…you might feel good afterward. That might make you want to do it the next time you go… just to see if you can again. Before you know it, your mind might "expect" you to say, "Please hold the biscuits" or, "Can I substitute a salad for the fries." That might become your new habit and your new expectations when you go to your favorite restaurant.
Habits aren't going to feel natural the first time you start changing them. You have to go through that awkward stage. Yet if you just try that first step and keep it simple, you will find you have more success. You have to give yourself permission to change your habits. You have to BELIEVE you can.
Do you quit a workout or eating program consistently after 1 to 2 weeks? What happens if you decide, just this one time, you are going to go past that 2 weeks…one day at a time. You're going to get to that point where you usually quit, and you are going to tell yourself, stick with it 1 more day. Then the next day, you are going to try that again. In your head, you might be telling yourself, "I always fall off after the first 2 weeks." What would happen if you tried to change that voice in your head, that mental block of letting what you've always done in the past stop you from believing in yourself. What would happen if you made it through week 3? It would probably feel amazing, and you might want to do it again. It might become a new habit.
What would happen if you fall off one day, and instead of getting discouraged and proclaiming you will restart next month, you just picked yourself back up and started back the next day? What new habits would you begin instilling in your mind. What new goals would you begin getting closer to reaching?
What could happen, if instead of the normal habit I have of snacking in the evening while I watch my favorite show, I did my nails (my nails I'm usually embarrassed to let people see because I never take time to care for them). The first night, it would be hard, because my mind would be telling me I need to be snacking. The next night might be hard too. Yet if I keep trying this NEW habit, taking care of my nails and doing something positive instead of my usual snacking, I might start expecting it. It might become my new norm. And the next day I'll probably feel less tired, less bloated, closer to my fitness goals….and by golly, my nails will look nice for once!
Quit quitting. Start new habits. Don't expect it to feel natural or come easy, but just start. Try to stick with it a little longer than normal. Try to pick your new habit back up immediately if you fall off track one day.
You don't have to be the person you've always been. You have the power to overcome those mental blocks holding you back. I don't care if you have quit everything you've ever started…today you can quit quitting if you decide to.
Make the decision. Start with small steps. Find a new habit to take it's place (doing your nails, reading a chapter, taking a bath). There are so many books on changing those habits and learning to stick to your goals. If you need any recommendations, feel free to reach out to me.


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Entry requirements
Please visit our website for the entry requirements of this course.
Months of entry
Course content
The emergence of new digital communication platforms has had significant impacts. Audiences are transforming into media producers; new business models are emerging; social media campaigns create new forms of politics; digital culture highlights practices of sharing and participation; and data collection and analytics affect an increasing part of our lives.
This offers new possibilities for digital citizens, but it also raises new questions regarding classic notions of privacy and freedom of expression, and it renders information and digital infrastructure a key resource.
The MA Digital Media and Society addresses current challenges of online communication and internet studies. It enables you to develop specialist knowledge in areas such as social media, big data, citizen journalism, digital culture, the creative industries, internet governance, and digital rights. It also provides a theoretical and methodological grounding in media and communication studies.
This course provides you with a thorough understanding of the current transformations and with the analytical skills to investigate digital media in the context of social, political and economic change. We ask how online communication is shaped by users, states and businesses, and how our society is, in turn, affected by digital media.
This course draws on the strength and diversity of Cardiff University's staff, giving you a unique opportunity to work with academics whose research explores issues such as citizen journalism, online activism, big data, internet surveillance, internet governance and digital rights.
You can get involved in our Research Group Digital Media and Society and thus become part of a dynamic research environment.
Please note this course focuses on academic research and does not provide extensive practical training.
Qualification, course duration and attendance options
- full time12 months
- Campus-based learningis available for this qualification
Course contact details
- Name
- Postgraduate Enquiries
- firstname.lastname@example.com
- Phone
- +44 (0)29 2087 0084


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Mental Health Awareness Week – Kindness in Cardiff Central
This week is Mental Health Awareness Week, the UK's national week to raise awareness of mental health. The week, which is hosted by the Mental Health Foundation, is in its 20th year and runs from 18-24 May. This year, the theme for the week is kindness. Across the country, people will be celebrating kindness in a range of digital and …Continue reading


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By: Lisa Mead, Founder, Arizona Women in Healthcare
More than 13% of the US labor force currently work in healthcare, and jobs in this sector are projected to grow more than twice as fast as the general economy by 2020. Women make up 80% of healthcare workers, earn 84% of bachelor's degrees in the health professions and comprise more than half of the enrolled medical students. Why, then, do women remain underrepresented at every level in corporate America, despite earning more college degrees than men for thirty years and counting? There is a pressing need to do more, and healthcare as an industry is among those that need more women leaders.
The 2017 Rock Health State of Women in Healthcare Survey reported that not a single woman serves as CEO of a Fortune 500 healthcare company and nor do they have executive team gender balance. Women are well represented in the healthcare workforce—just not at the top. At a leadership level, it will take twenty-five years to reach gender parity for senior-VPs and more than one hundred years at the C-suite level. That is way too long!
While commitment to gender diversity is high, organizations need to make a significant and sustained investment to change company practices and culture so women can achieve their full potential. Arizona healthcare organizations will benefit from having more women in top leadership roles. Diversity leads to stronger business results, as numerous studies have shown, and women have the skills to lead.
Arizona Women in Healthcare, Inc. is partnering with non-profit Take The Lead to provide women the tools to claim their power and create diverse conversations that advance our careers and move our businesses forward. Join 50 Women Can Change the World.
The program's curriculum addresses women's ambivalent relationship with power, dealing with internal as well as external barriers, and changing the equation from the outdated "power OVER" to a more current, collaborative and creative "power TO," an approach better suited to the very women's leadership styles that are bringing higher profits to businesses.
Developing female leaders is imperative for organizations that want to perform at the highest levels. Arizona healthcare organizations will benefit from setting a goal of leadership parity by 2025. Now is the time to develop women leaders and 50 Women Can Change the World will do just that. Register now for our program that begins in April 2019. Our healthcare organizations need more women on their leadership teams in the C-Suite and the board room so we can fill the pipeline for future positions. Women in healthcare may not be better off but they have all the opportunity to recognize they have the Power to change the world and improve healthcare.
About the Author:
Lisa Mead, RN, MS, CHPC, CPHQ
For more than 30 years, Lisa has worked in healthcare, first as a registered nurse providing nursing care and then as a leader in a variety of healthcare settings. Currently, Lisa is a healthcare consultant and leadership coach providing services across the country. She is the founder of Crowne Healthcare Advisors and Arizona Women in Healthcare. As part of her commitment to developing leaders, she is a Leadership Ambassador for Take The Lead, a nonprofit focused on leadership parity by 2025.


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Equal Exchange
Equal Exchange Coffee 1 lb
Sisters' Blend-
With a return to this popular blend, Equal Exchange honors women coffee farmers who are active in their cooperatives and women across faith-based denominations in the U.S. who advocate for small farmers. Drip grind only.
Organic Congo Blend-
An inspirational blend of East African Coffees that is smooth and balanced, with rich chocolate, sweet vanilla, brown spices and a hint of fresh berry. Whole bean only.
Sourced from various countries.


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- SPACED on DVD! Whoo! And about damn time, too! And it's not even that horribly overpriced as BBC series collections go.
- This t-shirt. WANT!
- The infamous musical It's a Bird, It's a Plane, It's Superman to be performed at the Arlington Center for the Arts in Arlington, MA, in June. On purpose!
Three Cool Things
at May 12, 2008
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One day,while flipping through the Cable channels, I suddenly ran across a SPORTS competition on JUGGLING! This struck me as both an unusual and delightful surprise because Juggling happens to be one of my hobbies. But I never expected it to become a competitive sport.
Although it does Not involve any Clashing with your opponent and so is still a Solo sport, so each Juggler is judged according to perfection and creativity of their performances.
To just give you one of the basic principles, there are Three categories of objects that can be juggled. (1)spherical, and (2)cylindrical, and (3)flat. Spherical is obviously objects such as tennis balls and apples. Cylindrical would be stick-like objects such as those Pins which resemble bowling pins, and for the most difficult would include machetes and flaming torches. Flat objects would include plates, which are difficult because the fingers canNot curl around the object like the other two categories.
In the competition, the finalists were briefly interviewed, and one juggler said that he actually fights against the objects that he juggles. Actually, for myself, I totally DISagree with him because I had always found that when I juggle that I always strive to be "AT ONE" with the objects. I always found that when I both physically and psychologically merge with the objects that I then find myself "in a FLOW" with them, the result of which is that the juggling goes much more smoothly. So I have to DISagree with that juggler.


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James Sajdak isn't a familiar name...that always makes me think it's a debut. Doesn't matter...it was an enjoyable Thursday puzzle. I wasn't up for a rebus tonight...bone tired again...so a theme just added to my enjoyment factor.
The theme was revealed at 57A: Where things are freely bought and sold...and what the starts of 17-, 23-, 36- and 46-Across do (open market). This is Pike Place Market in Seattle...the very best open market I've seen. When we were there a few years ago, we bought...among other things...all kinds of seafood, including giant crabs, and shipped them home. It was heavenly.
The theme answers:
17A: Tiny sideshow attraction (flea circus).
23A: Old weather forecaster (Farmers Almanac).
36A: When a big game is caught (Super Bowl Sunday). Sweetly deceptive clue.
46A: Roosevelt group (Bullmoose Party).
Most of the theme answers came readily. I have no idea how I could be on anyone's wavelength tonight...I can barely keep my eyes open.
Favorite clues and/or answers include 5A: Clothing retailer on the New York Stock Exchange since 2006 (J Crew), 15A: "A Dog of Flanders" novelist, 1972 (Ouida), 16A: Rapper with the gold-record album "O.G. Original Gangster" (Ice T), 21A: Short race, for short (one K), 29A: Israel's Olmert (Ehud), 32A: Citynicknamed Gateway to the West (Winnipeg), 40A: Remove, as a mustache (shave off), 41A: Title film role for Robin Williams (Garp), 52A: Guiding beliefs (ethos), 62A: First name in horror (Bela), 1D: Daily trippers? (oafs), 2D: Sign of treble? (G clef), 3D: Radio host Gibbons (Leeza), 10D: Do anything to help (lift a finger), 24D: Like land in urban renewal (redeveloped), 43D: "Wouldn't It Be Loverly" lyricist (Lerner), 44D: Missing links? (apemen), 46D: Arty topper (beret) and 48D: Disputed holy city (Lhasa).
This next week is going to be nonstop...delivering furnishings to the apartments, having documents signed by the residents, getting things together for the dedication. If you're interested in guestblogging, drop me an email and I'll get things set up. Otherwise, I may be in and out for the next week or so.
Here's the grid...
...and I'll see you soon.
Linda G
Wednesday, June 4, 2008
Thursday, June 5 - James Sajdak
Labels: James Sajdak, Thursday
2 comments:
That was a fun one. I had COld for COMA, and didn't know ATTIC, so Farmer's Almanac took some doing.
In "Fierce Invalids Home from Hot Climates", a Tom Robbins novel partially set in Seattle, there is a wonderful description of Pike Place Market. It makes one want to reread it, read it aloud, try one's and at writing, buy fish, and start using the word "one" instead of "you". Pretty remarkable.
- June 4, 2008 at 10:43 PM
- NYTAnonimo said...
We miss you Linda. Hope the work/moving is going smoothly. Looking forward to your return.
- June 7, 2008 at 8:51 PM
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How to pick up arrows
In horseback archery, when you are undergoing normal training, you can hold the reins in your right hand and, holding the bow in your left you can use the [string nock on the] siyah of the bow to pick up arrows that have fallen on the left (and vice-versa for arrows falling on the right[C14]). If the arrows are stuck in the ground, catch them between the string and the bow-limb to get them out[C15].
If you have the stirrups secured together with a leather, you use a different method. Suppose the arrow is on the left, secure your right foot in the stirrup and free your left foot, then it's very easy to lean over and stretch down to the ground to pick the arrow up. (And the opposite for arrows on the right[C16].)
This is not only useful for picking up arrows: it's also handy for cutting off enemy heads as proof of your kills. In battle, the last thing you want is to dismount from your horse[C17]!
[C14]I find this hard to credit. Even after our discussion in Sydney, where you pointed out that some bows had special nocks on the tips of the ears for this purpose, I still think the target is too small to aim for when on a restive horse in a lull in battle. We are talking of trying to pick up a 9-12 mm wide object at the end of your bow while sitting on a horse. The position of the string nock on a Chinese bow would not allow you to pick up an arrow from the ground without the modification you mentioned. Many steppe horseman had games which involved picking up items from the ground, while galloping past on a horse. This, though difficult, is more likely. However, you might spill the rest of your arrows in the process.
Perhaps this would have been a good examination subject because it would test so many aspects of the archer's coordination of horseback.
The Indians had a special device, the length of an arrow with a split end, with which they picked arrows up. The surviving examples have a sliding ring which locks the end of the device once the arrow is captured. It was carried in the quiver. When I get too lazy to pick up arrows, I'll make one.
[C15]This might work, though I have never tried it on horseback. I think it would depend on the angle of the "neck" to the string. In Ming times, some bows had long necks with shallow angles to the strings, which would have allowed this practice.
[C16]In Afghanistan and other places, where their stirrups aren't secured, they lean out of the saddle to pick up objects such as coins, kerchiefs and stuffed goats. I think any riders can be taught this and it can even be done at the gallop by the better ones. With an open quiver, it might not be worth the risk, unless the quiver was empty and you really needed an arrow!
[C17]A valid point. Even in everyday life, nomads try to avoid dismounting. Being on the ground puts you a disadvantage and remounting can be difficult with an excited horse.


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Surprisingly there are small items that we may not realise contain harmful plastic. Some of these are :
Contact Lens, Cigarette Filter tips, Cotton Buds with plastic stems.Glitter. (more details in this Recycling section)
These small items can easily get into water courses, so small that they cannot be filtered and then break down further and harm water life/fish and may return to the food chain.


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So the first thing to be ticked off the list for the 40 Project was to eat homemade faggots from a Black Country butchers. Admittedly, I never really ate them as a child – My only knowledge of them was seeing the adverts for Brain's Faggots on TV. It wasn't even the thought of what was in them that put me off, but if the only version I knew of were mass-produced and/or frozen, I'm pretty sure they're weren't the gourmet delight that people depicted them to be. Sure, I remember seeing Diana Rigg on a talk show once mention how when she was appearing in a play, they used to have "proper homemade butchers faggots" and not only were they cheap, but they were actually delicious and wholesome – Not like the frozen gunk you get now.
Fast forward a few years and I'm working in a kitchen in Birmingham City Centre and we recruit a new chef de partie – Woody. Now, Woody had the thickest Black Country accent I'd ever heard and he often used to talk about "fagguts an' pays". I didn't have a bloody clue what he was on about but it took a while until I had to get him to explain to me how it's quite a Black Country thing to have foggots and mushy peas – With lashings of vinegar. Still, never got to try one… So it took the opening of Pure Bar and Kitchen in Birmingham – The first bar to be opened by Purity Ales and the food served there was in consultation with Andreas Antona from Simpsons – Sorry, I should address them by their full title: Michelin-Starred Simpsons restaurant for me to see faggots on the food menu for a mainstream bar. I must confess, I've started to get into craft ales and I'd seen mutterings about Pure Bar and Kitchen on Twitter, so I was curious to see what it was like; Well, I could go on about the post-industrial looking interior, or the really fantastic choice of ales, or even the fact that they serve their own homemade pickled eggs and pork scratchings which are served in a half pint glass as bar snacks. But the reason I'm on about Pure Bar and Kitchen? The fact that when they first opened, one of the small dishes they had was a home-made faggot with mushy peas and onion gravy. And yunno what? It was seriously good: The faggot may have been quite meaty rather than offaly, the onion gravy may have had a touch of craft ale added to it, but when you got the trifecta of faggot, peas and gravy in one mouthful – It was just sensational. Seriously, them faggots were one of the best things on the menu and not only was it dark day when they took it off the menu, I'm pretty sure some angels died as a result.
Although I'm still hopeful that faggots will return on the menu at Pure Bar and Kitchen soon, it was the faggots at Pure Bar and Kitchen that got me thinking of this for my 40 Project: It got me thinking of Woody and seeing Diana Rigg on TV all those years ago and well, if I'm going to try faggots, then I should get them from a butchers in the Black Country that have been making them for centuries. Once that was decided, it was simply a matter of where I should buy them from… The place I really wanted to go to – The Cook Shop on Old Hill sadly closed late last year so I just missed them. So it was a case of asking Paul Fulford, restaurant critic and columnist for the Birmingham Post if he knew of anywhere and he very kindly put the message out to his followers: First up was a suggestion of Don Guest in Halesowen (along with the suggestion to try the black pepper sausages). It was certainly Black Country enough in that it was in Halesowen and some quick research showed that it was easily accessible by public transport. Next up was Bowketts in Oldbury which may not strictly be Black Country, but they looked professional enough with their sausages and well, they did make their own faggots. Finally, there was Broadbents in Bilston which boasted of selling 2 million faggots in the past 6 years. You can't much argue with that.
To be honest, I only needed to try one of the places suggested but for some reason, I tried buying faggots from as many places as possible as if doing a taste comparison. Of course, a lot of this was made possible by the fact that I was joined by my good pal The Foodist who very graciously drove me to all the different butchers (and in the process of doing so, got us taste-testing pork pies, too). But I do have some comments about the places we visited: Don Guest – Probably my favourite butchers of all we visited. I loved how it was an old-fashioned butchers in the middle of a row of houses that opens stupidly early (6am) and closes mid-afternoon. Their window display actually invited you in and by the time we got there mid-morning, they had already sold out of the black pepper sausages. What's more, all their food is homemade so the faggots were from a recipe over a century old and they didn't pre-cook the liver before making the faggots. There may have been a slight raising of the eyebrow when they said that they didn't use pig's cawl to wrap the faggots, but these were by far the best of all the faggots I bought – The liver wasn't overcooked and the bits of bacon really added to the overall taste. There wasn't any overpowering smell of offal and well, these were a pleasure to eat. In fact, everything I bought from Don Guest was very tasty and I am very envious of people in Halesowen whom can say that Don Guest is their local butchers.
In terms of the other butchers we visited:
- Bowketts – Although the roasted meats and crackling looked very tempting (we were really hungry, too), the inside of the butchers was really steamy. Sadly, the sausages weren't that great – Or rather, they suffered from the fact that they were cooked alongside the sausages from Don Guest which were better. Similarly, the faggots were a bit dry and overcooked and when drowned in gravy, were OK. But they weren't standout.
- Broadbent – Sadly, they didn't have any Faggots when we got there as they stopped making them over the Festive period.
- Michael Kirk – Late addition and to be honest, the faggots were a bit dry and needed a bit more seasoning.
So there you go, I can honestly say that not only did I venture into the Black Country (We had to type in a WV postcode into the Sat Nav at one point!), but I got to try several homemade faggots from a Black Country butchers. And yunno what? They were pretty good. First item ticked off the list!


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The First-Time Home Buyer Incentive launches September 2, 2019*.
* Barring any unforeseen circumstances the program will launch on September 2, 2019. The first closing will take effect on November 1, 2019.
Program Details
How does it work?
The Incentive enables first-time homebuyers to reduce their monthly mortgage payment without increasing their down payment. The Incentive is not interest bearing and does not require ongoing repayments.
Through the First-Time Home Buyer Incentive, the Government of Canada will offer:
5% of a first-time buyer's down payment for the purchase of a re-sale home
5% or 10% of a first-time buyer's down payment for the purchase of a new construction
How do I know how much I have to pay back?
You can repay the Incentive at any time without a pre-payment penalt="sunlite mortgage"y. You have to repay the Incentive after 25 years or if the property is sold. The repayment of the Incentive is based on the property's fair market value:
By changing the terms of your mortgage loan you can help you maximize your monthly cash flow.
Use of Refinance Calculator tool to see how a refinance could save you money monthly and over the life of the loan.
Note: If your property value goes down, you are still responsible for repaying the shared equity mortgage based on the current home value at time of repayment.
|Incentive by Property Type
|New Construction
|5% or 10%
|Existing Home
|New or re-sale mobile/manufactured home
Funding Available
The First-Time Home Buyer Incentive works on a first-come-first-serve basis. The total amount of funding will be $1.25 billion over 3 years.
Who can apply?
Canadian citizens, permanent residents, and non-permanent residents who are legally authorized to work in Canada
Borrowers must have a maximum qualifying income of $120,000
Total qualifying income cannot exceed $120,000 per year
This is subject to qualifying income requirements set out by lenders and mortgage loan insurers
At least one borrower must be a first-time homebuyer, as per the definition below.
Are you a first-time homebuyer?
you have never purchased a home before
you have gone through a breakdown of a marriage or common-law partnership (even if you don't meet the other first-time home buyer requirements).
in the last 4 years, you did not occupy a home that you or you current spouse or common-law partner owned
IMPORTANT: With the 4-year clause, it is possible that you or your spouse or common-law partner qualifies for the first-time homebuyer incentive (if you are in a married or common-law relationship). Even if you or your spouse or common-law partner has previously owned a home in the last 4 years.
How does the 4-year period work?
The 4-year period begins on January 1 of the fourth year before the year you purchased your home. It ends 31 days before the date you purchase your new home. Here are a few examples:
- if you purchase a home on March 31, 2015, the 4-year period begins on January 1, 2015 and ends on February 28, 2019
- if you sold your home you lived in in 2013, you may be able to participate in 2018 or if you sold the home in 2014, you may be able to participate in 2019
Are there other mortgage details?
Total borrowing is limited to 4 times the qualifying income. The combined mortgage and Incentive amount cannot exceed four times the total qualifying income.
The amount for the mortgage loan insurance premium is excluded from this calculation.
The Incentive will be a second mortgage on the title of the property. There will be no regular principal payments, it's not interest bearing and has a maximum term of 25 years.
The Incentive will have an equity-like payout, where the Government of Canada will share in the upside and downside of the property value upon repayment.
Mortgages must be eligible for mortgage loan insurance. The first mortgage must be greater than 80% of the value of the property. This is subject to a mortgage loan insurance premium based upon the amount of the first mortgage.
Mortgage loan insurance premiums may be subject to provincial taxes.
Minimum down payment is 5% of the first $500,000 of the lending value. It is 10% of the lending value above $500,000 from traditional down payment sources.
Traditional down payment comes from the borrower's own resources and may include:
withdrawal/collapse of a registered retirement savings plan (RRSP)
non-repayable financial gift from a relative
Note: Unsecured personal loans or unsecured lines of credit used to satisfy minimum down payment requirements are not eligible for the program.
What properties are eligible?
The Incentive is to help first-time homebuyers purchase their first home. Eligible properties include:
1 to 4 unit residential properties which includes
new construction
re-sale home
new and re-sale mobile/manufactured homes
The property must be located in Canada and must be suitable and available for full-time, year-round occupancy.
What are the terms of repayment?
The first-time homebuyer will be required to repay the Incentive amount after 25 years or when the property is sold, whichever comes first. The homebuyer can also choose to repay the Incentive in full at any time, without a pre-payment penalt="sunlite mortgage"y.
How is repayment calculated?
If a homebuyer receives a 5% (or 10%) Incentive, he would repay 5% (or 10%) of the home's value at repayment.
Repayment is based on the property's fair market value.
Let's look at a specific situation
Anita wants to buy a new home for $400,000.
Under the First-Time Home Buyer Incentive, Anita can apply to receive $40,000 in a shared equity mortgage (10% of the cost of a new home) through the program. This is on top of the minimum required down payment of $20,000 (5% of the purchase price) from her savings.
This lowers the amount she needs to borrow and reduces her monthly expenses.
As a result, Anita's mortgage is $228 less a month or $2,736 a year.
Years later, Anita has sold her first home for $420,000. At this time, she would now have to repay the original incentive she received as a percentage of her home's current value. This would result in Anita repaying 10%, or $42,000 at the time of selling her house.
* This example is for illustrative purposes only. All property values and home prices used in this example are not an indicator on how property values are forecasted.
Here's another situation
John Ying has an annual income of $83,125.
To be eligible for Canada's First-Time Home Buyer Incentive, he can purchase a home up to $350,000. John still has the required minimum down payment of 5% of the purchase price, $17,500 from his savings. He can receive $35,000 in a shared equity mortage — 10% of a newly constructed home.
This would reduce John's mortgage payments by $200 a month or $2,401 a year.
Years later, John has to decided to sell his home, but it is now worth $320,000. When he sells his house at the price of $320,000, John will have to repay the original incentive he received as a percentage of his home's current value. This would result in John repaying 10%, or $32,000 at the time of selling his house.
* This example is for illustrative purposes only. All property values and home prices used in this example are not an indicator on how property values are forecasted.


text: W waqas409 New Member Aug 28, 2015 #1 Hey guys my laptop has 7000 max value as shown in HWInfo, is it safe to max it to 7000 or should i stay near 4500-5500? Will it damage my laptop fan if i go max? Specs: core i7-2670QM 8gb Ram GT555m 3GB Windows 8.1


text: K.FLAYwith HOUSES and DENNY Tuesday, September 17, 2019 at 6:30pm$25.00 advance$30.00day of show18+Presented by: Go 96.3Venue: First AvenueMainroom Info TabsDetails PerformersPerformer: K.FLAY WEBSITEFACEBOOKTWITTERSOUNDCLOUDWhen facing the daily maelstrom of concerns, complaints, and calamities in the news, in conversation, and in social media posts, a smile signals real rebellion. Eschewing self-centered woe and melancholy-for-the-sake-of-melancholy, happiness becomes the brashest, boldest, and ballsiest move—and the sought-after answer. Recognizing this truth, two-time GRAMMY® Award-nominated singer, multi-instrumentalist, songwriter, and producer K.Flay sticks to a powerful, passionate, and positive mission statement on her third full-length album, SOLUTIONS [Night Street/Interscope Records]. Read more about K.FLAY Special GuestsSpecial Guests: HOUSES WEBSITEFACEBOOKTWITTERSOUNDCLOUDThe first Houses release in five years, Drugstore Heaven, marks a major artistic shift for L.A.-based songwriter/producer Dexter Tortoriello. Abandoning the heady concepts of his previous records for some of his tightest songwriting yet, Tortoriello is embracing the most fascinating character in his musical universe: himself. Read more about HOUSES DENNY WEBSITEFACEBOOKTWITTERSOUNDCLOUDThe ultimate goal for the three Minneapolis-based artists that make up Denny has always revolved around one thing: being their own favorite band. Their brand of sensually cinematic pop music and unapologetic commitment to creating exactly what they set out to create has earned them a growing and dedicated fan base. Read more about DENNY


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The little kickboxing club punching well above its weight
PUBLISHED: 15:14 28 September 2016 | UPDATED: 15:14 28 September 2016
A Gravesend kickboxing club has two more titles under its belt
A Gravesend kickboxing club is running out of space to display its belts after claiming two more titles.
On Saturday, Star Kickboxing's Tina 'The Machine' Harvey became three times world champion after a bruising fight against Northern Ireland's Cathy McAleer.
Meanwhile, Phoebe 'The Mighty Atom' Cumiskey' defeated Molly Walborn to take the TFC European Cadet K1 title in just two rounds.
Senior coach Leigh Howarth said: "For the past three years we have been on such a massive run of success and won 50 title belts.
"For a little club that is tucked away in Gravesend it is amazing what has been achieved.
"I am running out of room where I can hang the titles up!"
Mr Howarth claimed teamwork is a big factor behind the club's remarkable success.
"We train extremely hard – we really do put the hours in," he said.
"All the fighters help each other out. If they see someone doing something wrong they will help them.
"The general cameraderie is very good. As a consequence, it brings the level of the people below them up."
He added that the sport is becoming increasingly popular among both men and women.
"Years ago it used to be boxing but now people are drifting over to kickboxing and K1, where you are allowed to kick the legs.
"We do the training not necessarily to fight, but also to tone up. You can burn up to 1,000 calories per lesson.
"It is quite common we get children being bullied at school, and we give them confidence," he added.
"We get lots of children with ADHD, Asperger's and other conditions. Their parents bring them to us and we teach them and they do really well."
If you value what this story gives you, please consider supporting the Gravesend Reporter. Click the link in the orange box above for details.


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One of the reasons free online dating sites are so popular is that paid sites sound like a ripoff. Who wants to shell out hundreds of dollars to meet the love of their life when other sites offer the same services for free?
Last spring, OkCupid argued that people should never pay for online dating because there aren't enough people willing to pay a fee for dating services. Since fewer people means fewer matches, online daters should stick to free sites that may have a larger base of active users. Online Dating: Where To Start
Although OkCupid are right in that people hate paying for websites, others argue that those on paid dating sites will take the service more seriously in order to make the most of their financial investment. The Big Think cites a study published in Current Psychology that tested this idea on a group of undergraduates last year. 7 Biggest Turnoffs In Your Online Dating Profiles
Researchers gathered a group of 145 participants (86 female and 59 male), and asked them to simulate signing up and paying for an online dating site upfront. Afterward, participants were told that the website had found a match, but the person was missing a couple of preferred qualities. Then, researchers informed them that a friend was offering to arrange a blind date with someone who sounded like their perfect match. Participants had to go on dates with both matches, but were given an hour to split between them. 6 Tips For A Perfect Online Dating Photo
More Juicy Content From YourTango:


text: Special Introductory Offer. The original cleansing cream used by the professional acting trade for over 75 years. The only effective way to remove stage makeup and a secret age defying solution for all skin types. Contains one each of the Crowes Cremine original 200ml size and the new travel size 75ml.


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Updated annually, WATERWAY GUIDE'S CHESAPEAKE BAY edition is the indispensable cruising companion for cruisers exploring the Bay's 12,000 miles of shoreline.
The Waterway Guide Chesapeake Bay edition is for boaters exploring the Chesapeake Bay, the Delaware Bay and the Delmarva Atlantic coast from Cape May, NJ, to Norfolk, VA. The Guide features over 400 pages of mile-by-mile navigation information, aerial photography with marked routes, marina listings and locater charts, anchorage information and expanded "Goin' Ashore" articles on ports along the way. Helpful cruising data like GPS waypoints, detailed planning maps, weather station maps, distance tables and tide tables helps get cruisers there safely.
Flexible spiral binding and heavy laminated covers with bookmarker flaps ensure durability and easy use in the cockpit and at the helm.


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St Albans counsellor offering free sessions for Mental Health Awareness Week
PUBLISHED: 10:50 09 May 2017 | UPDATED: 11:11 09 May 2017
A St Albans counsellor will be running free sessions for Mental Health Awareness Week tomorrow.
Laura Hollywood will be at her practice on Bedford Road between 11am and 2pm on Wednesday.
She said: "I think it's really difficult for people to admit that there is anything wrong.
"Anxiety and depression make you feel hopeless and also you don't deserve to be helped.
"I'm running the event to try to change this and show people that help is available and things can improve."
She's asking anyone struggling to cope with anxiety, panic attacks, or relaxing, or knows anyone who is, to come by for a chat.
The theme of this year's Mental Health Awareness Week is 'Surviving or Thriving?',
The topic of mental health was recently brought into focus by Prince Harry's admittal he suffered from mental health issues around the death of his mother.
To book a place on the service, email Laura on email@example.com or ring her on 07507 850 787
To find out more about the event, visit www.facebook.com
If you value what this story gives you, please consider supporting the Herts Advertiser. Click the link in the orange box above for details.