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Book Review: A Kiss of Lies by Bronwen Evans
A Kiss of Lies , the first book in Bronwen Evans 's The Disgraced Lords series plunges into the plight of Lord Christian Trent, the Earl of Markham. He is wrongfully accused of raping Duke Barforte's young daughter. Like the other disgraced lords whom Christian attended Eton with and befriended, he is charged with a crime he did not commit and sets out on a course to prove his innocence, calling upon the help of his six college buddies nicknamed the Libertine Scholars and a new woman that enters his life introduced to him as Sarah Cooper.
The author makes it apparent that Christian and Sarah are physically attracted to one another during their first meeting face to face. In fact, their physical attraction is emphasized to the point that it leaves the reader wandering if their relationship will go any further, or if their surging hormones are the only factor bonding them together. Evans elaborates on the situation by creating a short history which the two share. Sarah, a voyeur at her father's soirees, spied Christian on the dance floor garbed in his military uniform when he was a young soldier during the Napoleonic Wars. She had indulged in fantasies about him not knowing that her father had put into motion for her to marry a hedonistic plantation owner. The story clenches the reader's imagination as Christian escapes Barforte's wrath and Sarah escapes murder charges for the death of her husband. Their circumstances consequently bring them together in York, Canada.
The stage is set in the first two chapters as Christian is harnessed with the task of finding a governess for his ward, Lily Pearson, the 12-year-old girl whose parents took Christian in when he arrived in York with only the clothes on his back. Christian embraces his role as Lily's guardian after her parents are killed. The author uses the situation to accentuate his endearing qualities putting doubts in the reader's mind that he could ever rape Barforte's daughter. While interviewing applicants, Sarah Cooper appears to have experienced a similar loss to Lily's and empathizes with the child.
Several chapters into the story, it's unveiled that Sarah Cooper is really Lady Serena Castleton, the daughter of the Duke of Hastings. This opens up the story to her upbringing with an unbearable father and a deeper connection to Christian who also endured a difficult childhood living with an abusive father. The revelation expands the basis for their relationship so it's more than a physical attraction, although the author alludes to the pair holding back even more secrets. Developing full-bodied characters is Evan's strength.
New surprises pop up from various corners of the story, although Evans provides them to the reader in small spoonfuls so they aren't overwhelming. There are moments of stillness in the story when the reader wishes for the scenes to progress more rapidly. When they don't, the story builds up anxiety in the reader causing some to jump to the next chapter. Nonetheless, Christian and Sarah (aka Serena) are a couple that audiences will be inclined to cheer for and like to see happy.
Holiday Movie Month: "Kiss Kiss Bang Bang" Review
The Lies We Tell Ourselves: Eliminate the Lies, Discover Your Truths, Design Your Success
Book Review - "Necessary Lies" by Diane Chamberlain (2013)
Book Review: the Last Kiss Goodbye by Karen Robards
Do NOT Kiss the Monkey: 'No More Kissing' Children's Book by Emma Clark
Luke Evans to Play Dracula, Remembering at the Best Dracula's of All-Time


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College football odds and lines
Kansas comes back from 25 down, falls to Arkansas in third overtime of Liberty Bowl
It was a furious rally in Memphis for the Jayhawks, but they came up one play short of a winning record in 2022.
By Collin Sherwin@CollinSherwin Dec 28, 2022, 7:00pm PST
Share All sharing options for: Kansas comes back from 25 down, falls to Arkansas in third overtime of Liberty Bowl
Photo by Justin Ford/Getty Images
The Kansas Jayhawks were down 38-13 to the Arkansas Razorbacks with four minutes left in the third quarter of the 2022 Liberty Bowl. But another furious second half rally for KU head coach Lance Leipold and the early-season darlings of college football saw them force the game to overtime with a Jalon Daniels 21-yard touchdown pass to Luke Grimm to tie it at 38-38 with just 41 seconds remaining in regulation.
But in the third overtime period, Arkansas was able to make their two point conversion while Kansas threw a pass away, and the Razorbacks won 55-53. With the win Arkansas moves to 7-6 on the season, while Kansas falls to 6-7.
Daniels was magnificent for KU, finishing 37-55 passing for 544 yards and five touchdowns with two interceptions. After an opening drive TD for the Razorbacks to start the second half, the Jayhawks held them to just two more first downs and no more scoring in regulation.
The game appeared to be over in the second overtime, as Daniels appeared to come up a yard short from a needed two-point conversion. But a targeting call on the play gave the Jayhawks new life, and Daniels ran it in on the extra snap to tie the game at 53.
Arkansas called for targeting on the Kansas 2-point conversion attempt.
Hogs had Daniels stopped. pic.twitter.com/QEEflncsgQ
— Trey Wallace (@TreyWallace_) December 29, 2022
If Kansas would have been able to complete the comeback, it would have been the biggest turnaround in a postseason game since the 2015 Alamo Bowl, which saw the TCU Horned Frogs rally from 31 down to beat the Oregon Ducks in three overtimes.

redpajama_set_name: RedPajamaCommonCrawl


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November 17, 2019 (Edited: November 17, 2019 ) - Entertainment
15 Best Shows You Should Definitely Watch on Netflix This November
Finding a show to watch on Netflix is certainly akin to finding a needle in the haystack! With thousands of options to pick from – and with quite a lot of them added each month – the act of actually finding the show from the list of offerings can certainly be an overwhelming task. Of course, nobody wants to feel overwhelmed just to watch a show – they want to relax.
To make your job of sorting through the pile easier, we have compiled a list of 12 new Netflix shows that you should definitely watch this November. With temperatures dipping, you don't have to worry about finding excuses to stay up late on a Friday night to watch new Netflix shows. So, take out your diaries because there's really a ton of exciting new content to watch on Netflix. Without further ado, let's check out the list now!
Queer Eye: We're In Japan!
The Fab Five are back, and this time they are going to visit the city of Tokyo in Japan, where they will spread the message of love and compassion while exploring the country's rich culture and lip-smacking cuisine.
Holiday in the Wild
After getting divorced with her husband, Kate ventures out on a solo honeymoon to Africa. There, she rescues a baby elephant and helps it regain its health. This inspires her to explore more of the natural environment.
A story of two womanizers who are fond of gatecrashing, find themselves in a tricky situation when one of them falls in love with a bridesmaid.
The End of the F***ing World – Season Two
A show that found great traction amongst the audiences, The End of the F***ing World is set for a release of season two. Based on a comic book series written by Charles Forman, the story revolves around two seventeen-year-olds, Alyssa and James, who venture out on a trip to find Alyssa's estranged father, who left and went away from her and the family when she was just a child.
An author decides to ghostwrite a semi-autobiography for her husband. However, the success of the novel inspires her to fight for the creative ownership, and to try and overcome the twentieth-century societal constraints a woman has to face.
A group of high school students is brought together because of a snowstorm on Christmas Eve, which collides their friendships and love lives. Christmas morning will change their lives, and nothing will be the same again.
Jumanji – Welcome to the Jungle
When a group of four students decide to play a magical video game, they are pulled to the jungle of Jumanji that traps their avatars. In order to return to their real selves in the real world, they need to finish the game.
A young expat woman is accused of murdering her missing friend that also involves a love triangle with a local photographer.
Pitch Perfect, Pitch Perfect 2, Pitch Perfect 3
All three installments of the Pitch Perfect movies – Pitch Perfect, Pitch Perfect 2, Pitch Perfect 3 will be available on Netflix. Pitch Perfect follows the story of an all-girl acapella group, The Barden Bellas, who compete against other such groups to win the Nations.
Iliza Shlesinger: UnVeiled
Iliza Shlesinger is back with the fifth stand-up special for Netflix, and this time she unveils weddings – revealing all the obnoxious and weird clichés about wedding traditions.
Bikram: Yogi, Guru, Predator
Tracing the rise and fall of hot yoga guru Bikram Choudhury, filmmaker Eva Orner examines a number of details that were talked about in the 30 for 30 miniseries.
The Knight Before Christmas
A tale of a medieval knight who is transported to the modern era and falls in love with a high school teacher.
The Crown – Season Three
A show about the life of Queen Elizabeth II that spans from the early 1940s to the modern-day, The Crown is based on an award-winning play by Peter Morgan, The Audience.
After the death of his brother, a young King Henry V faces numerous troubles – deceit, war, and treachery. Set in 15th century England, this historical epic has been highly anticipated.
A crime epic set in the 1950s, The Irishman is a highly anticipated movie that stars Robert De Niro, Al Pacino, Joe Pesci, Ray Romano, and Bobby Cannavale in leading roles. The movie is directed by none other than Martin Scorsese.


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Lullula by Studio Emily Broom
Dimple by Anna Karlin
House with Black Ceiling by Toru Kashihara Architects
May 16, 2020 / Interiors
Lullula is a minimalist studio located in Berlin, Germany, designed by Studio Emily Broom. The studio has recently completed the interior design of a studio for voice, music, and education situated in a former 120 year old pharmacy. Upon entering the studio, heavily woven linen floor to ceiling curtains quieten the space both aesthetically and acoustically, whilst natural linen sheers in the front and rear classroom windows provide privacy from the outside world and bring an almost serene quality to the space. The floor plan is open and flexible to allow for an easy transition between group classes, private lessons, workshops, and a curated calendar of events on weekends and evenings.
Sand colored walls serve as a neutral backdrop for the glossy black C. Bechstein grand piano, which takes centre stage in the front classroom. Along the main wall, three full-length custom-made mirrors backed with solid oak resemble an arcade, bouncing light around the space and playing with the scale of the room. The sideboard opposite is one of the few remaining pharmacy cabinets that underwent restoration with the addition of a new marble countertop. The composition of natural stone, wood, linen and woven yarn creates a soft, warm and restful environment to experience the joy of music. This is extended throughout the studio, right down to the props for classes: drums, tambourines, rattles, and rhythm sticks for the babies and children are made from wood and natural materials while yoga mats, blankets and bolsters for adult pre and post-natal classes are all responsibly sourced.
As a nod to the original floor tiles in the bathroom, a large trough style enamel basin becomes the focal point when set against the new half-height wall panelling and topped with a natural stone shelf. The soft curves of the sink are echoed in the custom-made oak mirror that adds a contemporary touch to the room. In the rear studio, the mushroom colored walls create an intimate environment for private rehearsals. A Reform kitchenette in 'iron' linoleum occupies a corner of the studio with an arched natural stone splash-back behind. It was important for us, that the kitchenette didn't feel out of place in the rear studio and so we chose to celebrate it with the arched stone splash-back that becomes a piece of artwork and echoes the arched theme throughout the project.
Jan 31, 2023 / Interiors
by oftn studio
House B
by BLURKER design studio
Austin Nichols Penthouse
by Morris Adjmi
Casa Palacio Paredes Saavedra
by TUÑON Y ALBORNOZ ARQUITECTOS


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Benjamin Stambouli (nascut el 13 d'agost de 1990) és un futbolista francès que juga com a migcampista defensiu per a Paris Saint-Germain FC a la Ligue 1 francesa.

Referències

Futbolistes del Paris Saint-Germain
Futbolistes del Tottenham Hotspur FC
Esportistes marsellesos
Futbolistes francesos

redpajama_set_name: RedPajamaWikipedia


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Q: Where is the IIS Express install directory? I have recently started an asp.net tutorial, and I want to test my page that I made with WebMatrix. How ever, there's an error:
The Web server is configured to not list the contents of this directory.
So it suggests to Enable directory browsing and go to the IIS Express install directory and run a command.
So where is this located exactly?

A: The user Data files are present here:
C:\Users\[username]\Documents\IISExpress

If that's the error. Then you might have got the error 404.13 (Forbidden) on your browser.
You can try to edit the web.config file and add this:
<system.webServer>
   <modules runAllManagedModulesForAllRequests="true"/>
</system.webServer>

This would allow the server to read the files and process them. This is a server settings error. And I think this might help you out.
Update
As suggested by jamiebarrow, you can get to that directory directly using the following path in your Windows File Explorer,
%userprofile%\documents\IISExpress

A: Locate the registry key:
HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\IISExpress\<Your version>

and parameter "InstallPath".

A: My directory is located here:
C:\Program Files\IIS Express

A: ☢ ☣ ⚠ If you are using OneDrive with Document Sync check the folder:
C:\Users\[your-account]\OneDrive\Documentos\IISExpress\config

The common way on %userprofile%\documents\IISExpress said from @Afzaal sadly not works for this case (OneDrive)
Also, remenber to make the folder always on the computer (right click on folder... onedrive option)

redpajama_set_name: RedPajamaStackExchange


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Q: Adding a static cell to a UICollectionView I have a UICollectionView that displays cells from an array. I want the first cell to be a static cell that serves as a prompt to segue into a create flow (eventually adding a new cell).
My approach would have been to add two sections to my collectionView, but I currently can't figure out how to return a cell within cellForItemAtIndexPath if I do so. This is my attempt:
func collectionView(collectionView: UICollectionView, cellForItemAtIndexPath indexPath: NSIndexPath) -> UICollectionViewCell {
    if indexPath.section == 0 {
        let firstCell = collectionView.dequeueReusableCellWithReuseIdentifier("createCell", forIndexPath: indexPath) as! CreateCollectionViewCell
        firstCell.imageView.backgroundColor = UIColor(white: 0, alpha: 1)
        return firstCell
    } else if indexPath.section == 1 {
        let cell = collectionView.dequeueReusableCellWithReuseIdentifier("mainCell", forIndexPath: indexPath) as! MainCollectionViewCell
        cell.imageView?.image = self.imageArray[indexPath.row]
        return cell
    }
}

The problem with this is that I have to return a cell at the end of the function. It seems that it won't be returned as part of an if condition. Thanks for helping!

A: Elaborating on Dan's comment, the function must return an instance of UICollectionViewCell. At the moment the compiler can see a code path where indexPath.section is neither 0 nor 1. If this occurs, your code returns nothing. It doesn't matter that this will never occur logically in your app.
The easiest way to fix it is to just change the "else if" to an "else". As in:
func collectionView(collectionView: UICollectionView, cellForItemAtIndexPath indexPath: NSIndexPath) -> UICollectionViewCell {
    if indexPath.section == 0 {
        let firstCell = collectionView.dequeueReusableCellWithReuseIdentifier("createCell", forIndexPath: indexPath) as! CreateCollectionViewCell
        firstCell.imageView.backgroundColor = UIColor(white: 0, alpha: 1)
        return firstCell
    } else { // This means indexPath.section == 1
        let cell = collectionView.dequeueReusableCellWithReuseIdentifier("mainCell", forIndexPath: indexPath) as! MainCollectionViewCell
        cell.imageView?.image = self.imageArray[indexPath.row]
        return cell
    }
}

Now if there are only two code paths, and both return a cell, so the compiler will be happier.


There are a few events that everyone should know about, and today I'm writing about one such event which I attended in Bali.
DMSS, Digital Marketing Skill Share, just concluded the 2nd edition of the event in Bali.
It was my friend, Andrea (VagabondCEO) who told me about the mastermind event.
He was flying from London to speak at the event. He had attended the first edition of the event in 2017 too, also as a speaker.
Upon doing some due-diligence and seeing some of my favourite companies and people like Gael from Authorityhacker, Ahrefs, Payoneer and a few others, I decided to attend the summit.
DMSS is an event for marketing professionals, digital nomads and entrepreneurs to share the knowledge and skills to excel and grow in the career.
Don't mistake this as one of those typical events. I am blown away by the kind of content and learnings. It's real people sharing real experience and knowledge about things they do. I have shared some of the takeaways in the latter half of this article.
There were workshops on topics such as SEO, social media, marketing funnels along with keynote speech by speakers from companies like Google, Hootsuite, WWF International, to name a few.
There were also workshops on things that we need in our day to day life for higher productivity and a better physical and mental state.
You can check the complete agenda of the event here.
The event was held in Bali, one of the world's most beautiful destination, and loved by the digital nomads, entrepreneurs and travel enthusiasts.
The event kicked off on October 6, 2018, and lasted two days. The third day, October 8, was for Mastermind, a limited entry event.
There is an optional upgrade of networking and holiday event called Networkation where one can opt for and stay in a villa for three days with the like-minded digital marketers and entrepreneur to share their learning and skills.
I will be attending Networkation from October 10-13, 2018, and will share my experience on my Instagram handle @denharsh. Follow me for regular updates.
I attended about multiple workshops and here are some takeaways from the same. Please note that these takeaways are my version of understanding and may not be 100% of the speaker.
Start using videos on YouTube. It's the world's second largest search engine and #1 search engine for videos. The conversion and engagement are quite high with YouTube.
Ahrefs is launching a keyword tool for YouTube soon.
In his session, Greg took an interesting approach to content marketing.
He mentioned the Empireflippers valuation tool to evaluate the price of your website/blog/saas product if you decide to sell it. In case you're unaware, Empireflippers is a popular platform for flipping websites. This free valuation tool helped them to earn a lot of free mentions from PR companies and journalists all across the globe.
Share Insider knowledge content – These are not for SEO, but it earns loyalty. For example, case studies, personal experience. This article is an example of Insider knowledge content.
Buyer intent keyword – These are the keywords which a buyer is searching for.
Shoulder niche keyword – The intent isn't close to buying, but they are in the same sphere as your customers who are looking for information.
Buying an affiliate website is an option. (Personal note: These could be good as an investment which will continue adding to your residual income. If you know SEO or marketing, you can buy a good website generating a decent income every month, and add your magic to grow traffic and revenue). You can use Empireflippers to look for such opportunities.
Redirect free wifi to Instagram or other important landing pages. (You can use this for your office, home or even ask your clients to do that with their wifi connection).
Work with brand advocates that influence consumers.
Brand collaboration – Branded video would be pretty awesome.
He mentioned about one of his clients, Accorhotels, that used Hootsuite to set up The Social Desk using the Hootsuite Enterprise. If you are in the hotel business, this could be interesting for you. You can find their case study here.
Offline business or offices should be optimized for social media. For example, a selfie booth. This was the most common suggestion by experts to make your restaurant, bars, cafes, co-working space, office or businesses to be Instagram friendly. I am excited to share this with my friends who are into the restaurant and bar business.
He is the friend who told me about the DMSS event. He spoke on a fascinating topic, and this turned out to be one of my favourite session of the event.
Andrea explained to us how he is managing and helping a lot of Instagram profiles grow, and most of his tips were actionable.
Buy profile with followers if you are working for a client. You can always change the username as long as it's available.
Use Hyperauditor to analyze the Instagram profile before buying it.
Post link in stories (this is good for driving traffic and something I also do for ShoutMeLoud).
Add your own hashtag. For example, I use #ShoutMeLoud as the hashtag.
Add up to 30 hashtags.
Target followers based on locations.
Engage with comments or likes.
Use stories highlights (You can see an example of this on my Instagram profile).
Use shoppable posts if you are selling products. You can find more information about here.
Use linktree to post multiple links on your Instagram bio.
This part of his session was mind-blowing. He explained the use of Instagram bots with real examples.
Instazood: They offer a 3-day free trial. Test it with a dummy IG account as it automatically starts following, liking and commenting.
Stimsocial: They offer a 5-day free trial.
Jarvee: This is perfect for agencies or freelancers who are managing multiple Instagram profiles. It is feature-rich, and unlike the two mentioned above which are cloud-based, this one needs to be installed on a Windows system.
If you are using a Mac, you can buy a Windows VPS and use it. This one is for advanced users and if you have never used a bot before, you can start with the cloud-based tools like Instazood or Stimsocial.
Follow new profile and automatically unfollow them after x number of days.
However, you need to be careful with the automation you use. If you don't know anything about it, spend time reading and learning before you even touch an Instagram bot.
Gifts like candies (which is not expensive) in the packages can bring the smile on the face of your customers and they might talk about your brand on social media.
I was pretty excited about listening to Gael. This guy always talks sense. He spoke about "Building automated high converting sales funnels".
Reverse discount – increase the price by 50% (anchor high value) and then offer a discount.
Transfer rational buying into emotional buying. They are doing this with a webinar where they offer bonuses if viewer purchases their course within 45 minutes.
Personally, I have witnessed that this works great. Anyone who runs webinars and sells products can take advantage of it. You can think of bonuses like templates, blueprints or adding some other value stuff which is exclusive.
Enforce real deadlines for your courses. If you promise to open only twice a year, it should be twice only. I have made a mistake with ShoutUniversity where I opened it 3-4 times in a year which is not ideal.
He recommended using Deadlinefunnel for enforcing the real deadlines. He uses Activecampaign which also integrates with Facebook audiences and helps them run targeted ads on Facebook to their email list only. Here, the segmentation has helped them get maximum ROI from the ads. I currently use Convertkit for ShoutMeLoud but I will evaluate Activecampaign in the days to come. I will share my findings with you soon.
Replica webinar – This is an interesting concept where you record webinar once and then you keep reusing it in an automated manner. You can see an example of this on Mobilemonkey.com. They offer you to watch their webinar with a countdown timer.
Go above and beyond when offering free stuff.
Mehedihasan404 – He recommended this Fiverr guy for graphics related stuff.
Use Pixel caffeine WordPress plugin for segmenting FB audience based on category. I have shared a detailed write-up about this plugin here.
Create a lookalike audience on Facebook from your existing email list or segmented category users. Use it to promote your blog posts and drive new traffic.
Hanna is the CMO of Thrivethemes. She shared a lot of knowledge on A/B testing and user testing.
Focus on percentage rather than numbers when looking at conversions or A/B testing.
Start with testing things that matters the most. For example, CTA text matters more than what colour your CTA button is.
You can also ask your readers, customers to give feedback of your website. You can use Loom which makes it easier for them to record the screen and give you a video feedback.
Remove friction. – useless stuff like phone number if you don't really need it.
You should pick stuff which will have the maximum possible impact to your end goal. Do consider the speed of implementation. Document all the A/B test at one place such as Google docs so one can easily refer to it in the future.
If you don't have much traffic, listen to your customers and optimize.
This was another workshop that has a great impact on me. I had no idea about Mott Totten before his talk, but I got great insights from his talk.
He talked about how we should work in this digital age and made a strong case on what will happen if we don't take care of our body. His talk was inspired from his work on this blog called Wild workstation.
Work for 90 minutes straight and then take a 30-minute movement break. Make sure to move your body by exercising or just take a walk.
Do acro yoga or other forms of exercise in the morning.
Set a digital sunset time. For him its 6.30 pm. He recommends not using any form of digital stuff including Kindle post that time. I like this idea, but I also know it would take a great deal of self-control to make this a part of life.
Use flux or similar app for your computer or mobile in the night.
I recommend you to read his blog. He has shared many interesting ideas which you can implement to improve your day to day life.
He was the highlight of the event. Probably the craziest guy in the whole event who is also a world record holder for many stunts. He also gave a speech on how he achieved things which seemed impossible.
If one person can do it, another person can do it too.
Sometimes its ok to take a step back and then start. This is exactly something I'm doing with my life right now.
Persistence and conviction are two tools that could let you achieve anything in life.
Whenever I travel, I often meet Shouters. This time I met a Shouter from China who is also a fellow blogger. His name is J.P. and he also blogs in the Chinese language about SEO.
He also showed how he is using Wechat for blogging. He has a blog on WordPress and also publishes his blog on Wechat. It was interesting to see that people can donate money on Wechat to him for his content.
I hope something like this comes to other parts of the world. If you know of the similar platform, do let us know in the comment section below.
One thing is for sure, if you ever feel that your work is becoming monotonous you should visit Bali and attend DMSS for fresh dose of inspiration. The people here will show you how to live a free life, something which is not so common in this digital age.
Bali as an Island is full of charismatic people who are not too different from you. They follow the mantra of "Live a boss-free life" and "Do what your heart says". These will remain only words for you until you experience it yourself.
If you are a marketer or a blogger or anyone who lives a laptop lifestyle, you can stay in Changgu (book via AirB&B) or you can also take advantage of DojoBali which is a co-working space that also offers co-living. Make sure to rent a bike and experience the streets of Bali like a local.
From the pricing point of view, the event is not cheap. I spent $397 for the conference, $250 for the mastermind and $797 for the networkation. However, this will be compensated by the kind of personal and business growth that you will get here at the event.
However, Bali is quite cheap in terms of renting a space and food. You can literally spend your day and night in shorts and T-shirts. Those who live in corporate cities can understand the freedom of this.
You should make a plan for 10-15 days as it will give you enough time to reflect upon your learning and also strengthening your bond with the new connections that you will make here. If you are an adrenaline junkie like me, you can go scuba diving, cliff jumping or learn surfing.
Phew! I had so much to share that I didn't even realize it's been 4 hours and have written more than 2700 words. I have a lot of other stuff to share about DMSS but I think it would be better if I stop here and you could probably explore this amazing event yourself the next year.
You can join DMSS on various channels to keep yourself updated about the next chapter.
Also, on November 1st and 2nd 2018, there is an SEO event happening in Chiang Mai, Thailand, which is one event everyone here is talking about. You can find information about the event here.
Well, stay tuned for more similar updates from some of the best events and conferences around the world. For now, I'm off to Networkation and will share my experience on my Instagram handle @denharsh after the event.
Wow! This is an awesome experience and a great event. Thanks for sharing your experiences with the #Shouters.
Nice blog. Loved the info about Bali.. Spl. Details on cost food etc.
Great tools and websites you shared. Each of the attendees is a source of inspiration and someone to gather knowledge from.
Such an energetic article but can't explore such line by myself.
But sad to note that you haven't posted a single pic of the Bali landscape or the nature photographs from this lovely land called Bali.
Hope you will post in some other posts or include in this at a later stage.
Anyways thanks a lot for sharing this amazing information with the shouters.
PS: Unable to login on website, several time tried but getting a message: "Session expired"please fix it.
Thanks for sharing this Bali event. I will join DMSS on you tube for updating my skill.
Hi Harsh, It sounds like it was an awesome event with lots to learn. I can't believe how many tools there are for social media like the ones you shared for Instagram. Do you think these tools are like gaming the system? That one really got me thinking, the Linktree tool. Thanks for sharing all of this with us and I look forward to reading more from this experience.
Great experience to learn new concepts. Congrats you attended and thanks you shared to the world.
Nice blog! DMSS as well as Bali shall be the amazing experience to explore on and worth it to spend on.
Mott sounds like such an inspiring guy Harsh. Plus Bali is the ultimate background for any conference. I keep going back because the place is so beautiful.
Thanks sharing the pics of the event. All are fabulous. I am also love to read and hear Gael. He is very much informative and have great content on his blog. Thanks for sharing this.
i m glad to find your blog and this post. I already try facebook but just the traffic and conversion option. I ve got the pixel set up then i m gonna try this plug in.


The Internet isn't a place where everyone shouts at each other. It's a collection of lots of small places where people are chatting among themselves.
In case you didn't know, muscle-car lovers have a thriving Internet community. Twitter users like @HookupMyRide and @CorvetteBlogger are among the chattiest sports-car enthusiasts, tweeting links and striking up conversations with other fans of fast cars. The influential drivers of the muscle-car blogosphere stick to what they like; they mostly share links and thoughts about cars. For that reason, it's unlikely that they'd ever interact with Twitter users who focus on environmental issues – in fact, the two groups live in entirely separate neighborhoods of the Internet.
That may seem like a strange metaphor for the non-physical space of the Internet, but to John Kelly, the chief scientist at Morningside Analytics, it's quite apt. He spends his days mapping the "cyber-social geography" of the Internet, anlayzing who is talking to whom and what they're talking about. While many web analytics companies focus on the users who are most influential across the entire Internet, Kelly said, his data show who's influential in small, specific communities. This helps uncover a few interesting trends about who really gets heard in the public sphere of the Internet.
First, like the muscle-car lovers, people with shared interests often create isolated communities, talking among themselves about a limited set of topics. That means that people who share certain interests or viewpoints are less likely to interact with people who have different and possibly opposing priorities – for example, car lovers and environmental activists.
But Kelly's maps also suggest two different models for becoming influential in the digital public sphere: Be like Oprah, who reaches lots of different people on many subjects, or be like the president of a very committed bowling club, who reaches a limited audience that probably cares a lot about that specific topic. The question is, are the "bowling club presidents" of the Internet really regular people who happen to love a certain topic? Data suggest that "traditional" influencers like companies and news organizations still have a lot of power, even in niche digital spheres.
More on that in a minute. First, check out the most visually striking aspect of Kelly's work: The rainbow balls he uses to map the Internet. In this particular case, each dot represents a Twitter account, and the size of the dot represents how many people are following that account. The closeness of the dots indicates how much those Twitter users pay attention to the same stuff, and people who have statistically similar web surfing habits are grouped by color.
What this tells us is that Twitter's most eco-conscious users aren't reaching one of the audiences that probably needs to hear from them most: people who love cars. The two groups have different values and priorities, but they're still connected – gas consumption, car exhaust pollution, and road and highway development are among the important environmental issues related to cars. Instead of putting their perspectives into dialogue, though, these groups stick to their respective corners of the Internet.
Of course, this isn't some vast conspiracy by car lovers who want to remain blissfully ignorant of environmental issues or by environmentalists who pretend cars don't exist – people find stuff they like on the Internet, and understandably, that's the stuff they read and share. But this also means that the digital public sphere is fractured, made up of lots of different nodes that don't quite connect.
This can be good. The Internet has meant that communications can now take place in no other setting but the digital one. "People who are all interested in saving sea turtles," Kelly says, "or voting for some upstart candidate for Congress – all those people can pretty costlessly find each other and affiliate now and find some plan for action."
In other words, anyone can find other people who share her interests, no matter how obscure those interests are. These communities might provide entertainment, but they also provide a place for groups to coordinate and rally offline action. This is especially important because of the low cost of entry – people no longer have to have a printing press and/or a powerful company on their side to find allies and make their voices heard in a public sphere.
On a deeper dive, Twitter users like @Toyota, @MazdaUSA, and @Hyundai show up as top influencers on all things auto; Ford-related websites and Twitter handles have their own category. With followers in the hundreds of thousands, major companies and news outlets can reach bigger audiences, offering authoritative information to people outside of the tightly woven community of car lovers. At the same time, these organizations have also been able to infiltrate the micro community of people who really care about their products.
This mix of everyday Twitter users with traditional influencers is interesting for a few reasons. First, it suggests that big companies and traditional news organizations are actively seeking out niche digital audiences – they're sharing, engaging with, and re-tweeting information created by regular people. As a result, traditional influencers have become embedded in tight-knit, interactive communities. Marketers and magazines are no longer just trying to blast target audiences with a message; they're trying to engage with and actually become part of their audiences. This allows commercial messages and information to be woven even more seamlessly into the daily lives of regular people.
Second, the lack of overlap between different but connected communities, like car lovers and environmentalists, seems even more problematic when those communities include companies and news outlets that have a lot of power to create change in the real world. It's one thing for @CorvetteBlogger to come into contact with environmentalists like @ElectricDrive, a Washington organization that advocates electric car use, but what if @ElectricDrive started sharing lots of links with @Toyota? With a broader reach, communities can put their perspectives into dialogue; for example, car lovers might start to understand the environmental effects of their hobby, and environmentalists might start to understand the heart-stopping beauty of a blood red sports car.
Of course, Twitter doesn't make up the entire public sphere of the Internet – plenty of conversations take place on blogs and other social media platforms, although these trends happen there, too. And the traditional public sphere, meaning live debates, printed publications, coffee shop conversations, etc., isn't dead – yet. But if these trends continue, it seems inevitable that they will affect the public sphere, shaping it into lots of self-contained nodes and fragmented spheres where anyone can be an expert but few perspectives are heard.


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Saccharomyces cerevisiae senses hyperosmotic conditions via the HOG signaling network that activates the stress-activated protein kinase, Hog1, and modulates metabolic fluxes and gene expression to generate appropriate adaptive responses. The integral control mechanism by which Hog1 modulates glycerol production remains uncharacterized. An additional Hog1-independent mechanism retains intracellular glycerol for adaptation. Candida albicans also adapts to hyperosmolarity via a HOG signaling network. However, it remains unknown whether Hog1 exerts integral or proportional control over glycerol production in C. albicans.
We combined modeling and experimental approaches to study osmotic stress responses in S. cerevisiae and C. albicans. We propose a simple ordinary differential equation (ODE) model that highlights the integral control that Hog1 exerts over glycerol biosynthesis in these species. If integral control arises from a separation of time scales (i.e. rapid HOG activation of glycerol production capacity which decays slowly under hyperosmotic conditions), then the model predicts that glycerol production rates elevate upon adaptation to a first stress and this makes the cell adapts faster to a second hyperosmotic stress. It appears as if the cell is able to remember the stress history that is longer than the timescale of signal transduction. This is termed the long-term stress memory. Our experimental data verify this. Like S. cerevisiae, C. albicans mimimizes glycerol efflux during adaptation to hyperosmolarity. Also, transient activation of intermediate kinases in the HOG pathway results in a short-term memory in the signaling pathway. This determines the amplitude of Hog1 phosphorylation under a periodic sequence of stress and non-stressed intervals. Our model suggests that the long-term memory also affects the way a cell responds to periodic stress conditions. Hence, during osmohomeostasis, short-term memory is dependent upon long-term memory. This is relevant in the context of fungal responses to dynamic and changing environments.
Our experiments and modeling have provided an example of identifying integral control that arises from time-scale separation in different processes, which is an important functional module in various contexts.
Adaptation to dynamically changing environments is required for any life form to survive. Unicellular microorganisms often adapt to environmental changes by modulating their metabolism and reprogramming their gene expression patterns. Generally, microbes are constantly monitoring their environment via specific receptors, and then adapting their cellular physiology accordingly via changes in gene expression and metabolism that are driven by specific signal transduction networks.
The yeast Saccharomyces cerevisiae is able to adapt to acute changes in extracellular osmolarity. The hyperosmotic signal is amplified and transmitted via the High Osmolarity Glycerol (HOG) signaling network, and this leads to the intracellular accumulation of the osmolyte, glycerol. Increasing intracellular glycerol concentrations decrease the intracellular water potential, restore water influx and consequently restore cell volume and turgor pressure.
In S. cerevisiae, the HOG network has two main upstream branches, namely the Sln1 branch [1, 2] and Sho1 branch [3, 4] (Figure 1). These two branches converge at Pbs2, which becomes phosphorylated in response to hyperosmotic stress, eventually culminating in Hog1 activation . The Sln1 branch is thought to have a linear topology (i.e. no feed-forward or feedback loops). In contrast, the Sho1 branch has at least two negative feedback control loops (Figure 1), in which activated Hog1 inhibits the activity of upstream signaling components including Sho1  and Ste50  via phosphorylation. In principle, such negative feedback amplifier can ensure Hog1 phosphorylation levels be kept within a narrow range upon adaptation to hyperosmotic shocks . Consistent with this idea, the Sho1 branch does not respond to low hyperosmotic signals (less than 0.1 M NaCl), and displays lower maximum responses compared with the Sln1 branch . In contrast, Sln1 branch operates at a high basal level in the absence of hyperosmotic signal, although the components generating such basal activation remain unidentified . This basal signaling activity enables the Sln1 branch to respond faster than the Sho1 branch. Previous studies also suggest that, following osmoadaptation, Sln1 signaling is down-regulated via ubiquitin-proteosome mediated degradation of unphosphorylated Ssk1 .
Osmosensing networks. The osmosensing signaling network in S. cerevisiae includes the Sln1 and Sho1 branches which converge at Pbs2 and eventually activate Hog1 by dual phosphorylation . Under normal turgor pressure (i.e. in the absence of hyperosmotic condition), Sln1, a transmembrane protein upstream of the Sln1 branch, is autophosphorylated. This leads to phosphorylation of Ypd1, which subsequently transfers the phosphate group to Ssk1. The phosphorylated form of Ssk1 is unable to activate Ssk2 or Ssk22 via phosphorylation. Under hyperosmotic conditions, autophosphorylation of Sln1 is inhibited. This inactivates Ypd1 and consequently abrogates the inhibition of Ssk1. This is followed by the subsequent activation of the MAPKKK Ssk2 and ultimately of Hog1. Putative osmosensors Hkr1 and Msb2 that lie upstream of the Sho1 branch are postulated to directly sense the extracellular osmolarity . Cdc42 interacts with and activates membrane associated Ste20 or Cla4 . In addition, Cdc42 is able to bind the Ste11-Ste50-Opy2 complex (targeted to the membrane by Opy2) to bring activated Ste20 or Cla4 to their substrate Ste11 . Docked with membrane-bound Sho1, activated Ste11 phosphorylates Pbs2 and eventually activates Hog1. The components of this network that are currently understood in C. albicans are depicted in the dotted box .
In contrast to the benign model yeast S. cerevisiae Candida albicans is a major fungal pathogen of humans that causes frequent mucosal infections in otherwise healthy individuals and potentially lethal infections in immunocompromised intensive care patients . HOG signaling is essential for the normal virulence of C. albicans, although osmosensing in C. albicans is not well characterised (Figure 1). Similar to S. cerevisiae, in C. albicans osmotic stress signals are relayed to Hog1 via Pbs2 . However, in C. albicans, osmotic stresses activate Hog1 only through Ssk2, and the Sho1 branch does not contribute significantly to osmosensing . Therefore, Ssk2 appears to be the only MAPKKK that activates the HOG MAPK module under the stress conditions examined so far . It is not yet clear whether the stress signal is relayed via Sln1. A novel osmotic stress signaling pathway might work in parallel with Sln1 to relay osmotic signals to Pbs2 . In contrast, bioinformatic surveys of osmotic signaling components have suggested that key components of the Sho1 branch might be absent in C. albicans (Additional file 1: Figure S1; ). In summary, uncertainties remain regarding the upstream and downstream components of the HOG signaling network in C. albicans.
Given the importance of HOG signaling components for the virulence of C. albicans, it is important to study how this pathogen responds to osmotic shocks. In this study, we have investigated how the HOG signaling network operates in C. albicans using a model that encompasses the HOG signaling network and downstream adaptive processes.
Some signal transduction pathways returns to basal activity levels once a cell has adapted to environmental change. For instance, chemotaxis in E. coli is achieved through a sensing network whose activity always returns to the basal levels once the cell moves towards the attractant or away from the repellent . Also, the phosphorylation status of the heat shock transcription factor returns to basal levels once C. albicans cells have adapted to elevated ambient temperatures . This type of "perfect adaptation" may be significant in minimizing the potential impact of signaling crosstalk. In particular, the HOG pathway shares common components with the pheromone sensing pathway and the filamentous growth pathway. Perpetual HOG signaling activity might inappropriately activate other pathways.
A recent in silico study reveals that only two network topologies ensure perfect adaptation, incoherent feed-forward loop and negative feedback loop (; see Figure 2 for detailed discussions). In incoherent feed-forward loop, the response element is subject to a positive regulation that is proportional to a negative regulation simultaneously. The overall outcome is that the final output is insensitive to the signal. The negative feedback loop involves integral control, a regulatory mechanism whereby the controller output is proportional to the amount and duration of the error signal (the "error signal" being defined as the difference between a signaling network's current state and its final adapted state) (Figure 3). Integral control enables the cell to convert an error signal into the temporal integral of the activity of the signaling pathway. In other words, the output of the signaling network (i.e. changes in the downstream adaptive processes) will be proportional to the temporal integral of the signaling pathway. Since the information is encoded as the temporal integral of the signaling pathway, the signal transduction pathway is able to "integrate out" the error signal, returning to basal levels once the cell has adapted to its new state. Hence, integral control provides a means of achieving the perfect adaptation of a signal transduction pathway.
Networks that enable response ( R ) to perfectly adapt to signal ( S ). (A) Incoherent feedforward loop: on one hand, S directly phsophorylates and hence activates R; on the other hand, S inactivates R proportionally via stimulating the expression of proportioner (P) that dephosphorylates R. The activation and inactivation effects cancel out for R in such a loop. As a result, R always resumes to the original state upon adaptation. In the mathematical model, R refers to the phosphorylated form of R (i.e. Ra in the diagram). The first equation dictates that the steady state expression level of P is proportional to S (this is why it is called "proportioner"). Plug this relationship into the second equation and take the steady state: S in the first term will cancel with P in the second term. This makes the steady state of R independent from S. (B) Incoherent feedforward loop. This slightly more complex example also helps demonstrate perfect adaptation. In this case, S phosphorylates and thereby activates both R and P. If S operates in the saturated regime (i.e. K 1 < <(1-P)) and the dephosphorylation of P operates in the unsaturated regime (i.e. K 2 > > P), then the first equation reduces to the same form as that in (A). By the same reasoning, Ra in this incoherent feedforward loop perfects adapts. (C) Negative feedback loop involving time-scale separation: S phosphorylates and activates R that subsequently simulates the expression of its own inhibitor E. In the model, R refers to the phosphorylated form of R (i.e. Ra in the diagram). When E disappears at a constant rate v 4 , the second equation ensures that the steady state R is independent of S, and is only determined by k 3 and v 4 . In this case, E integrates over R, and this negative feedback loop constitutes an integral controller. As a special case, when the half life of E is much longer than the time scale of other reactions, v 4 is approximated to 0. Consequently, R always resumes 0 upon adaptation. (D) Negative feedback loop involving saturated enzyme kinetics: in this slightly more complex scenario, element (E) is the phosphatase of R and is activated by R via phosphorylation. If Ra and E's phosphatases both operate in their saturated regimes, then the second equation reduces to the same form as that in (C). By the same reasoning, such a negative feedback loop is capable of perfect adaptation.
Block diagram of integral control. For a system, the input signal is u(t), and the output signal is y(t). The difference between u(t) and y(t) is defined as the error signal e(t).
The integral controller employs the time integral of the error signal K ∫ 0 t e(τ)dτ as the feedback mechanism.
Interestingly, integral control mechanisms have arisen frequently in evolution, presumably because they provide robust means by which systems can adapt effectively to constant environmental stimuli despite stochasticity. Indeed, systems biology studies have revealed a variety of biological processes that employ integral control mechanisms including bacterial chemotaxis , calcium homeostasis  and energy metabolism .
Elegant single cell analyses of nuclear Hog1 enrichment in S. cerevisiae following hyperosmotic shock have revealed that nuclear Hog1 levels return to basal levels once the cell has adapted to hyperosmotic conditions, and therefore that the HOG system displays perfect adaptation . These authors showed that upon exposure to osmotic stress, the time integral of Hog1 activity is linearly related to the increase in extracellular osmotic pressure within a certain range . This verifies that Hog1 exercises integral control over glycerol production in response to a persistent hyperosmolarity. This key discovery offers a starting point for developing simple mathematical models of osmotic stress responses in S. cerevisiae and C. albicans.
Using modeling and experimentation, we demonstrated that such integral control arise through a separation of the time scales between rapid signaling events and the relatively slower downstream adaptive processes. In addition, a hyperosmotic shock triggers long-term changes in the physiology of yeast cells that prepares them for subsequent hyperosmotic shocks. It appears as if a yeast cell can "remember" a previous hyperosmotic shock over a period that is longer than the time scale of signal transduction, and therefore adapts quickly to subsequent hyperosmotic shocks. We term this phenomenon a long-term stress memory. Our model suggests the HOG system also has a short-term memory that is engendered in the activation and inactivation of the intermediate kinases during the signal relay. The short-term memory might be affected by the regulation of glycerol channels. Our work highlights the need to study the properties of a signal transduction network in an appropriate biological context.
Several possible mechanisms enable integral control (Figure 2C-D, Figure 4). Our aim was to test which of these mechanisms operates during osmoadaptation. Consider a signaling molecule that exists in either a phosphorylated or unphosphorylated state (Additional file 1: Figure S2). Its kinase activity is modulated by a signal, while its phosphatase has a constant activity. Given a constant signal, if the kinase and phosphatase both operate in the saturation regimes (i.e. the concentrations of the kinase and the phosphatase far exceed their respective Km values), using a total quasi-steady-state approximation to describe the phosphorylation and dephosphorylation processes, it can be demonstrated that the activity of this signaling molecule is mainly determined by the activities of its kinase and phosphatase ([27, 28], for details see Figure 4). Thus, the activity of this signaling molecule effectively integrates the difference between its kinase and phosphatase activities. In addition, this mechanism involving saturated enzyme kinetics would result in a memory whose duration is determined by the rates at which the kinase and the phosphatase activities change. This is predicted to endow a short-term memory that lasts seconds because changes in the kinase and phosphatase activities typically are rapid . However, it is unlikely that any component in the HOG pathway would operate under both saturating phosphorylation and dephosphorylation conditions because of the low concentrations of MAPK pathway components in S. cerevisiae (see supplementary material section 2.1 for details). An alternative mechanism of saturated enzyme kinetics can give rise to perfect adaptation is discussed in Figure 2D. For the same reason as the previous case, it would leave only a short-term memory.
Integral control could result from saturation enzyme kinetics. Here, both kinase and phosphatase operate in the saturated region, the equation governing R reduces to d R d t = k 1 S − k 2 E . Therefore, R integrates the difference between S and E.
An alternative mechanism by which integral control can arise is via differential time scales in biological processes (see Figure 2C for details). Phosphorylated Hog1 activates several parallel mechanisms to increase the intracellular levels of glycerol in S. cerevisiae. Active Hog1 up-regulates the expression of genes encoding glycerol biosynthetic enzymes (GPD1 GPD2 and GPP2). Hog1 also increases the activity of a key enzyme (Pfk26) that diverts metabolic flux towards glycerol production . Furthermore, Hog1 stimulates the production of Stl1, a component of the glycerol/H+ symport system that assimilates glycerol from the growth medium [11, 30]. In principle, if the timescale for the inactivation any of these mechanisms is much longer than the timescale for achieving adaptation to higher osmolarity, then we can safely ignore the inactivation of the adaptive processes during the adaptation process. Since the glycerol channel activities change rapidly in response to external osmotic pressure , the adaptive processes we consider here are only related to glycerol production. Hence, if inactivation of glycerol production is a much slower process than adaptation itself, then the change in glycerol production rate (i.e. the output of the HOG signaling network) is determined by the time integral of phosphorylated Hog1. Indeed, in S. cerevisiae the rate of increase in glycerol biosynthetic enzyme levels is proportional to the time integral of Hog1 phosphorylation . This change in physiological status would be likely to generate a molecular memory whose duration is determined by the rate at which the glycerol production rate reduces to basal levels following a return to hypo-osmotic conditions. Therefore, a significant memory was predicted because the degradation of stable enzymes is relatively slow. A descriptive model detailing Hog1 integral control was experimentally validated . However, the idea that this integral control arises in S. cerevisiae through a separation of time scales between signaling and glycerol production rate changes was not fully recognized. The connection between Hog1 adaptation and integral control was not reported till later .
Whilst upstream components of HOG signaling have diverged significantly in the evolutionarily divergent yeast, C. albicans[19, 20], Hog1 integral control of osmotic stress adaptation might be conserved. Therefore our first aim was to build a simple mathematical model that highlights Hog1 integral control for both S. cerevisiae and C. albicans, and then use it to test alternative mechanisms by which a long-term memory can arise.
In our model, a pathway or module describing a certain biological function is represented by a single reaction, encapsulating the main dynamical features of several molecular events. Our model encompasses the HOG signaling network that transmits osmotic stress signal and modulates Hog1 activity (v1 to v4), Hog1-dependent intracellular glycerol accumulation (v5 and v7) and an osmolarity-regulated A quaG lyceroP orin activity (v6) (AGP, i.e. Fps1 in S. cerevisiae; unidentified in C. albicans) (Figure 5). An acute environmental hyperosmotic shift is proposed to cause rapid closure of this aquaglyceroporin to reduce glycerol efflux . It is generally believed that this is a fast change mediated by a rapid conformational change of the aquaglyceroporin under hyperosmotic conditions, and that the aquaglyceroporin will reopen once the cell has adapted [11, 32].
Overview of the model. The hyperosmotic stress signal is represented as the change in the difference between intracellular and extracellular osmotic pressures (i.e.S(t) = (Π i 0 − Π e 0) − [Π i (t) − Π e (t)]; Π i 0: initial intracellular osmolarity, Π e 0: initial extracellular osmolarity, Π i (t): current intracellular osmolarity, Π e (t) current extracellular osmolarity). Thus, the initial signal is equivalent to the increase in osmolarity caused by the extracellular NaCl. Upon an increase in extracellular osmolarity, the signal becomes positive and activates an intermediate kinase (v1) and then Hog1 (v3), both of which are balanced by dephosphorylation activities (v2, and v4 respectively, associated kinetic parameters are constant). Once activated, Hog1 induces the activity of glycerol production machinery (GPM) (v5) which produces glycerol. Intracellular glycerol passively diffuses out of the cell through an aquaglyceroporin (AGP), driven by the concentration gradient across cell membrane (v6). Hyperosmotic shock triggers rapid closure of the aquaglyceroporin to retain glycerol, while a hypoosmotic condition causes the aquaglyceroporin to open to a higher degree than that of the steady-state (v6) and triggers a rapid decrease in the glycerol biosynthesis rate (v7). In both C. albicans and S. cerevisiae, increased intracellular glycerol concentration elevates the intracellular osmotic pressure and eventually attenuates the signal, indicating adaptation to the new condition.
In our model we also assume that glycerol productivity does not decrease under hyperosmotic conditions (v7 = 0). Thus, the increase in the activity of G lycerol P roduction M achinery (GPM) will be proportional to the time integral of phosphorylation levels of Hog1. We also note that in the long term in S. cerevisiae, active Hog1 is reported to phosphorylate the aquaglyceroporin to target it for subsequent degradation [11, 32]. However, this regulation has yet to be quantified in S. cerevisiae, and it is not known whether the aquaglyceroporin in C. albicans is regulated in the same way. Hence, the degradation of aquaglyceroporin, despite its potential interest, is not included in our model.
To construct our model for both S. cerevisiae and C. albicans, we investigated the dynamics of different physiological variables for various doses of NaCl. These included Hog1 activity, and intracellular and extracellular glycerol concentrations. S. cerevisiae data were taken from several publications [31, 33, 34], and we systematically measured these values in C. albicans (Figure 6). As discussed in supplemental section 2 in details, most kinetic parameters were set to reproduce the dose–response in Hog1 activation. The rest were manually tuned with respect to the single shock experiment.
Experimental measurements and model construction. Wild-type S. cerevisiae (A, B) and C. albicans (C-D) cells were exposed to hyperosmotic condtions. (A) S. cerevisiae: 0.2 and 0.5 M NaCl; (B) S. cerevisiae: 1 M NaCl; (C) C. albicans: 0.5 and 1 M NaCl. (D) C. albicans: 1 M NaCl. Hog1 activity, intracellular glycerol and total glycerol were measured in time courses of up to 1 hour. Experimental data for S. cerevisiae in A and B are published results . C. albicans data are from this study. Model predictions were plotted separately from experimental measurements.
where F nuc is nuclear fluorescence signal, F cell is whole cell fluorescence.
Our model is consistent with this. First, following adaptation to the higher osmotic pressure, the rate of production of intracellular glycerol is then balanced by glycerol efflux so as to maintain constant intracellular glycerol levels. In principle, three factors contribute to glycerol efflux rate: [i] intracellular glycerol levels, [ii] extracellular glycerol levels, and [iii] aquaglyceroporin activity.
This signal reduces to a small value following cellular adaptation. This suggests that the activity of aquaglyceroporin will return to its resting value b AGP after adaptation. Taken together, the rate of glycerol efflux is determined by and is proportional to the intracellular glycerol concentration G i alone. Because glycerol production P G balances glycerol efflux v 6 , the former is also proportional to intracellular glycerol concentration G i .
The increase in intracellular osmolarity caused by the rise in the intracellular glycerol concentration G i eventually matches the new extracellular osmolarity ∏ NaCl to reduce the signal upon adaptation. Thus, increase in the extracellular osmolarity that triggered the response ∏ NaCl is linearly proportional to the increase in glycerol production rate P G , which is determined by ∫ 0 t Hog 1P(t)dt due to the integral control. Hence, the time integral of the nuclear enrichment of Hog1, which is highly correlated with the phosphorylation of Hog1, has a linear relationship with ∏ NaCl .
In response to hyperosmotic conditions, S. cerevisiae closes the aquaglyceroporin channel, Fps1, to prevent glycerol leakage and help to maintain a high intracellular glycerol concentration [27, 31]. Similarly, C. albicans appears to have a high restriction over glycerol efflux by an aquaglyceroporin. Our experimental data show that, in the presence of 1 M NaCl, the increase in total glycerol (i.e. the sum of intra- and extra-cellular glycerol) is mainly due to the induction of intracellular glycerol, and extracellular glycerol (i.e. the difference between total and intracellular glycerol) does not change significantly (Figure 6D). This is consistent with the idea that the aquaglyceroporin closes quickly in response to hyperosmotic stress thereby inhibiting glycerol leakage. This would maximize the efficiency with which cells could accumulate glycerol. However, we note that the experimental data suggest that intracellular glycerol does not plateau upon Hog1 adaptation (Figure 6B6D).
Our measurements of intracellular and total glycerol concentrations revealed relatively high initial intracellular glycerol concentrations in unstressed cells, which were induced about four-fold following a hyperosmotic shock. Our experimental procedures, which examined exponential cells grown in rich media at 30°C, were designed to minimize environmental stress. We would point out that the glycerol assay does not have the sensitivity to measure low concentrations of glycerol accurately . Nevertheless, our data indicate that under our experimental conditions unstressed C. albicans cells contain intracellular glycerol (Figure 6D). In our model we assume that the intracellular glycerol concentration is in equilibrium with the extracellular glycerol concentration pre-stress.
Our experimental data revealed two significant differences between the responses of C. albicans and S. cerevisiae. Firstly, in S. cerevisiae the proportion of phosphorylated Hog1 reaches its maximum value when concentrations of NaCl are greater than or equal to about 0.2 M (Figure 6A), whereas in C. albicans the percentage of phosphorylated Hog1 continues to increase, even in the presence of 0.5 M NaCl (data not shown). The NaCl concentration at which Hog1 phosphorylation amplitude becomes saturated was used to constrain parameters of the HOG signaling pathway (for details see supplemental information, section 2.1). Secondly, in S. cerevisiae GPD1 expression was strongly induced at the protein level and this regulation was mediated by Hog1 . However, in C. albicans GPD1 is expressed at high levels even in the absence of hyperosmotic stress, and Gpd1 is not highly induced under hyperosmotic conditions . However, expression of GPD2 was found to be induced at the mRNA level . This indicates differential regulation of the Gpd isoenzymes by Hog1 in C. albicans.
As mentioned previously, the existence of a long term memory is the key to distinguishing the mode of control that Hog1 exerts upon glycerol production (i.e. proportional, derivative or integral) and to explain its underpinning mechanism (i.e. saturated enzymatic kinetics or the separation of time scales). The existence of a long-term cellular memory would imply a mechanism of Hog1 integral control that arises through the separation of time scales between Hog1 signaling events and glycerol production rate changes.
To test this, we developed an experimental assay whereby C. albicans cells were exposed to an initial hyperosmotic shock (1 M NaCl) until they fully adapted. These cells were then removed from the hyperosmotic condition for about 10 min, and were then exposed to an identical, second hyperosmotic shock. We found that the duration of Hog1 phosphorylation in the second response was much shorter than that for the first stress (Figure 7A). This provided direct experimental evidence that adaptation to 1 M NaCl results in a memory that lasts for at least 10 min. Our model, manually turned to reproduce single-shock data, reproduces these results well quantitatively. We also assayed the time course of Hog1 phosphorylation during sequential hyperosmotic shocks of 0.5 M NaCl. Once again the model predictions were in good agreement with experimental results (Figure 7B).
Responses of C. albicans to repeated hyperosmotic stress. C. albicans cells were exposed to two identical hyperosmotic shocks (A: 1 M NaCl; B: 0.5 M NaCl). After adaptation to the first shock (A: 60 min; B: 30 min), the cells were shifted to medium lacking NaCl for 10 min. Subsequently, the cells were subjected to an identical second shock (A: 1 M NaCl, 60 min; B: 0.5 M NaCl, 30 min). Hog1 phosphorylation was measured at various time points over a 1 or 2 h time course in duplicate (A) or triplicate (B). Experimental and simulated Hog1-phosphorylation levels are normalized against the first Hog1 phosphorylation peak. (C) Relative total and intracellular glycerol concentrations (0.5 M NaCl) were measured at various time points over a 2 h time course (2 to 6 replicates were measured up to 60 min, and in duplicate after 60 min). Both experimental and simulation results are normalized to the total glycerol concentration at 60 min.
We then tested whether this molecular memory was due to the retention of a relatively high glycerol synthetic capacity after adaptation to the first hyperosmotic stress. This was achieved by monitoring the intracellular glycerol levels generated by C. albicans cells after repeated exposure to hyperosmotic conditions (Figure 7C). The data showed that intracellular glycerol levels plateau within the first 45 min, which was coincident with the disappearance of Hog1 phosphorylation during the first hyperosmotic shock. Intracellular glycerol levels were then restored within 20 min of the second shock, also coincident with the disappearance of Hog1 phosphorylation. This provided further evidence that C. albicans cells retain high glycerol productivity for some time after the first adaptation. It also strongly supports the idea that the integral control in the HOG system is endowed by the separation of time scales. We note that the total glycerol was induced about 2-fold while it is simulated to increase 4-fold. However this minor discrepancy does not change the main conclusions drawn above.
Having shown that C. albicans displays an osmotic stress response memory and discussed its relevance to integral control, we used our model to make predictions about the behaviour of this memory. Our model predicted that during the hypoosmotic period between the first and second hyperosmotic shocks, cells would rapidly release the intracellular glycerol that was accumulated during the first hyperosmotic shock. We also predicted that the proteolytic degradation of the glycerol production enzymes synthesized during first hyperosmotic shock might take a relatively long time. These factors influence how long the memory lasts. By changing the duration of the interval between two consecutive hyperosmotic shocks, our model predicted that a short interval, such as 2 min, would not result in significant reduction in the glycerol production rate (Figure 8E). We therefore inferred that the rapid closure of the aquaglyceroporin would be sufficient to maintain the intracellular glycerol level when the second hyperosmotic shock is applied. Interestingly, the model also predicted that even though the intracellular glycerol concentration is fully restored during the second adaption, the glycerol production rate might not (dashed line in Figure 8E). During a longer interval between hyperosmotic shocks the glycerol production machinery is predicted to decrease significantly. In this case the second hyperosmotic adaptation would require a higher glycerol production rate and hence more sustained Hog1 activation. For example, after a gap of 30 min between shocks, the C. albicans cell is predicted to return to its pre-shock physiology and respond to the second shock in nearly the same way as it did to the first stress (dotted line in Figure 8A, E).
Simulations of the duration of cellular memory following exposure of C. albicans to 1 M NaCl. Cells are stressed for 60 min, undergo an interval without stress before a second identical stress is imposed. The interval varies between 2 to 30 min, as indicated in the lower left inset. (A) Hog1 is plotted in relative values. (B) Internal glycerol concentration is in M. (C-D) Extracellular and total glycerol concentration are in mM. (E) Glycerol production rate is in M/min. (F) Stress signal has a dimension of Osm.
The HOG signaling networks in S. cerevisiae and C. albicans also possesses a "short-term memory" of hyperosmolarity. This results from the time it takes for the signaling components to be inactivated via dephosphorylation/phosphorylation. In response to a fluctuating osmotic signal, if the duration of the "off" phase of the signal is longer than the time required to inactivate the signaling components on HOG pathway, the phosphorylation levels of Hog1 would be predicted to follow the fluctuating signal. However, if the duration of the "off" phase is shorter than the inactivation time of the HOG pathway, the HOG network would remain active into the next cycle. The short-term memory of HOG pathway (i.e. the inactivation time for HOG pathway) typically lasts several minutes [37, 38].
To better understand this phenomenon, we developed a theoretical framework for the basic HOG signaling module, which is represented by a protein that is phosphorylated and dephosphorylated by its kinase and phosphatase, respectively. Employing Michaelis-Menten kinetics, we show that this module is essentially a low-pass filter (supplemental section 2.2). In other words, given a constant phosphatase level, the phosphorylation level of the protein faithfully follows a low-frequency activation signal while integrating a high-frequency signal, as reported previously [28, 37, 38]. We also derived analytically how the frequency of an activation signal would impact upon the phosphorylation level of an enzyme (see supplemental section 2.2 for details of the solution). In this way, our analytic solution of the frequency response has furthered our understanding of the behaviour of this simple module. In addition, we showed that in response to an alternating signal, the amplitude of the output of a network decreases with the number of cascades it contains (supplemental section 2.2). This ability to attenuate high frequency signals would allow cells to filter out random fluctuations (white noise) in environmental osmolarities, whilst maintaining its ability to sense significant environmental changes over longer time scales.
These studies were carried out using theoretical frameworks that only modeled the signal transduction pathway itself. We then extended our analyses to include downstream adaptive processes by simulating how the entire system responds to a fluctuating signal. As previously mentioned, the HOG signaling network faithfully monitors low frequency signals. As expected, our simulation results suggest that Hog1 phosphorylation levels follow the sinusoidal signal when its frequency is 0.1 rad/min (Figure 9A). However, the average of Hog1 phosphorylation initially decreases to a constant value. This is due to the sequential accumulation of intracellular glycerol during each period. Cells that have acquired relatively high intracellular glycerol concentrations are essentially pre-adapted to a hyperosmotic shock posed by 1 M NaCl.
Predictions of frequency responses in C. albicans . Responses of a C. albicans cell to a sinusoidal osmotic signal with peak-to-peak amplitude of 1 M NaCl (centered at 0.5 M NaCl) at different frequencies are simulated (dotted line: 0.1 rad/min; dashed line: 1 rad/min; real line: constant stress).
Meanwhile, the HOG signaling network integrates high frequency signals. It is expected that a cell will respond to a high frequency sinusoidal signal in a similar manner as to a constant hyperosmotic stress with the time-average amplitude of the sine signal. In addition, due to the integral control, Hog1 phosphorylation levels might be expected to return to basal levels once the cell has adapted. However, our simulations predict that Hog1 phosphorylation does not return to the initial condition. Instead the model predicts that, due to the quick release of glycerol in the "off" phase of the signal, the cell does not accumulate intracellular glycerol to the same level as it does under a constant signal (Figure 9B), and the glycerol production rate does not reach the same level as that under a constant stress (Figure 9E). This would be similar to the molecular response of mutants that are unable to close the aquaglyceroporin channel, which must constantly activate Hog1 to maintain a high intracellular glycerol concentration. Based on this consideration, we designed an asymmetric square wave signal with the same frequency of 1 rad/min, but where each "on" phase is longer than each "off" phase. The simulations predicted that under these conditions, Hog1 phosphorylation levels will recover when the "off" phase is sufficiently short (see supplement section 2.6 for details). These results suggest that the frequency of the cellular response is dependent upon both the short-term memory in the signaling pathway (i.e. the low-pass filter) and the property of glycerol channels. The results highlight the need to place a model of the signal transduction network into an appropriate context when studying its properties.
We also investigated whether the long-term memory, a property of the adaptive process itself, affects the short-term memory of the signaling pathway. We performed simulations of a cell pre-stressed in 1 M NaCl for 60 min and observed how it then reacted to a 1 rad/min sinusoidal osmotic signal of a peak-to-peak amplitude of 1 M NaCl centred at 0.5 M NaCl (Figure 10). The model predicted that it takes much shorter for the Hog1 activity to adapt to similar levels compared with those cells excited by the same signal but without a preconditioning history (compare Figure 10 with the dashed lines in Figure 9). This indicates that, although HOG signaling behaviour is typically conceived to be determined by the short-term memory alone, long-term memory also contributes to signaling behaviour. Our computational study suggests that a pre-stressed cell possesses relatively high levels of intracellular glycerol that offset the environmental osmotic shock. Hence, as a result of this long-term memory, a stronger osmotic shock is required to achieve an equivalent signaling amplitude to non-pre-stressed cells. Also, this effect partially overrides the short-term memory, at least in over short time scales. This insight again emphasises the importance of a systems approach to study the properties of signal transduction pathways in vivo.
Long-and short-term memories in C. albicans . A cell initially undergoes a constant hyperosmotic shock of 1 M NaCl within the first 60 min. This is followed by the treatment of a 1 rad/min sinusoidal signal with a peak-to-peak amplitude of 1 M NaCl centered at 0.5 M NaCl.
Recently, Gennemark and coworkers reported a simple mathematical model of hyperosmotic responses in S. cerevisiae. Their model concisely described the biophysical changes of a hyperosmotically stressed yeast cell, and related those changes to glycerol production. This model is able to reproduce some published data on the changes in intracellular and extracellular glycerol concentrations in response to different physiological perturbations. Instead of integral control, their model assumes a time-delayed proportional control of glycerol production, i.e. glycerol productivity at a particular time is assumed to be proportional to the change in turgor pressure (relative to a constant reference turgor pressure). A consequence of this assumption is that there should be no memory effects in the stress response dynamics. This motivated us to investigate whether a model including integral control would be more appropriate.
Also inspired by the recent finding of Hog1 integral control in S. cerevisiae, we investigated osmotic stress responses in C. albicans by constructing a low granularity mathematical model assuming Hog1 integral control. This model integrates the HOG signal transduction pathway with downstream adaptive processes, and encompasses both hyper- and hypo-osmotic conditions. In this model, a signaling or biochemical pathway was concisely represented by an overall reaction (Figure 5). Hence, the property of the pathway was defined by the associated kinetic parameters. The model was calibrated using in-house generated time-course data of Hog1 phosphorylation plus intracellular and total glycerol levels following exposure to two doses of NaCl. Subsequently, Hog1 integral control was experimentally verified in C. albicans using experiments in which cells were subjected to repeated NaCl insults. The data showed that pre-stressed cells adapted to a second hyperosmotic shock more quickly, as if they remembered the hyperosmotic history. This phenomenon is known as the "long-term stress memory", because its duration was longer than the time required for signal transduction to take place. Using this model, we reasoned that the cellular memory observed under hyperosmotic conditions is a hallmark of the separation of time scales between HOG signaling and reduction of glycerol production rates. In this case this mechanism enables Hog1 integral control.
The separation of time scales in different biological processes is a universal phenomenon. Often, signaling networks that perceive environmental conditions such as nutrient availability, chemical insults, and mating pheromones are required to function at much faster rates (i.e. seconds) than the ensuing regulatory networks which encompass transcriptional and translational controls (i.e. tens of minutes). It is also common for signals to be converted, via modulation of transcriptional regulators, into the expression of a stable product (i.e. a stable mRNA or protein). Such a separation of time scales could result in an integral control mechanism that would generate an experimentally testable long-term memory. Therefore our experimental approach could be further applied to other signaling networks to examine such a property. In addition, the identification of such a phenomenon allows mathematical simplifications of the regulatory network under study, an important step towards a thorough understanding of signaling networks which may be obscured in exhaustive descriptive models.
The teleological question as to why the yeast cell employs an integral control mechanism remains to be answered. Among the various types of feedback mechanism, proportional control and derivative control mechanisms would allow a system to adapt to a new status that is different from the original condition. However, integral control ensures perfect adaptation of the system, whereby signaling returns to basal levels once adaptation is achieved. This would reduce the potential for cross-talk between signaling pathways. The ability of the cell to restore turgor pressure in the face of an osmotic challenge is crucial for the restoration of growth. Should Hog1 signaling regulate glycerol production via proportional control, a change in osmotic pressure would be reflected by a proportional change in Hog1 activity. In other words, the ability to sense diverse amplitudes of osmotic signal would require high concentrations of HOG signaling proteins, the production of which would demand considerable cellular resources. In contrast, the integral control mechanism converts the error signal into the temporal integral of HOG activity. This avoids the need to express HOG pathway components at high levels. In fact in S. cerevisiae, Hog1 phosphorylation levels become saturated in response to relatively low hyperosmotic signals. In addition, derivative control offers gradual changes in a system, which might be too slow to generate the necessary adaptation to external osmotic challenges. Indeed, derivative control is often found to provide a buffering capacity in cellular systems. For instance, in energy metabolism, phosphorylated molecules, such as phosphocreatine, act as a buffer during high energy demand periods. Phosphocreatine implements a biological derivative control over ATP concentration .
Our modeling further suggests that the frequency response of the HOG signaling pathway can be affected by the regulation over the glycerol channels. This prediction is significant because this frequency response is generally thought to be a property of the short-term memory mediated by the regulation of intermediate protein kinases alone. In addition, our simulations show that the long-term memory may also affect the way a cell responds to a high frequency signal. Our simulations suggest that a cell that has previously adapted to hyperosmolarity retains relatively high intracellular glycerol levels for a period. Consequently, the high intracellular osmolarity counterbalances the hyperosmotic signal that the cell perceives. These results highlight the importance of a systems approach to study the signaling networks.
Our measurements of Hog1 phosphorylation dynamics in C. albicans suggest that, in this pathogen, Hog1 achieves perfect adaptation to a constant hyperosmotic shock through an integral control mechanism that is dependent on separation in time scales between signalling and downstream adaptation. We also predict that Hog1 signalling exhibits a short-term memory that can be revealed by tracking responses to an alternating signal. Furthermore, we predict that this short-term memory depends on the long-term memory. For example, Hog1 phosphorylation levels are predicted to adapt relatively quickly to high frequency signals in cells that have pre-adapted to a constant hyperosmotic stress.
C. albicans strain CA1655 (ura3::λimm434/ura3::λimm434 RPS1/rps1::pACT1-FLAG-GFP) was used for the Hog1-phosphorylation assays. This strain is CAI-4  containing pACT1-FLAG-GFP  integrated at the RPS1 locus. C. albicans CA1655 expresses a FLAG-tagged version of GFP from the ACT1 promoter and functions as an internal loading control for Western blots. C. albicans NGY152 , which is CAI4 transformed with CIp10 , was used for the glycerol assays. Strains were routinely maintained on YPD-T medium (2 % (w/v) glucose, 2 % (w/v) mycological peptone (Oxoid), 1 % (w/v) yeast extract (Oxoid), 100 mM Tris–HCl, pH 7.4) .
Cells were grown at 30°C with shaking (200 rpm). To ensure consistency in the starting physiology of the cultures used in our experiments, cells were pre-cultured twice overnight in YPD-T, diluted to an OD600 of 0.2 in fresh medium and then grown to mid-log phase (OD600 0.8) before any stress was applied . A single hyperosmotic stress was applied by splitting one large starting culture and diluting the cells back to an OD600 of 0.2 in fresh YPD-T with NaCl added to achieve concentrations of 0, 0.3, 0.5, 0.75 or 1 M. Cells were harvested by centrifugation at selected time points and the pellets flash frozen in liquid nitrogen.
For the experiments involving the imposition of sequential stresses, cells were initially cultured and stressed as described above. At the end of the first stress period, cells were harvested, resuspended in fresh YPD-T with no NaCl and incubated at 30°C for 10 min. NaCl was then added to the cultures and samples were collected after the second stress period. Three biological replicates were prepared for each condition.
To make protein extracts, flash-frozen cell pellets were resuspended in freshly prepared protein lysis buffer (50 mM Tris–HCl pH 7.5, 150 mM NaCl, 0.5 % NP40) containing inhibitors (2 mg/ml Leupeptin, 2 mg/ml Pepstatin, 1 mM PMSF, 2 mM Na3VO4 and 50 mM NaF) and sheared with acid-washed glass beads (425–600 μm, Sigma-Alrich) using a Fast-Prep FP120 machine (Thermo Scientific) (6 × 15 s bursts, Speed 6.5 with 1 min on ice between bursts). Protein extracts were clarified by centrifugation and protein concentration determined using a Bradford assay .
Proteins were separated by SDS-PAGE on NuPAGE®Novex Bis-Tris 4-12 % pre-cast polyacrylamide gels (Invitrogen, Paisley, UK). 15 μg protein was loaded in each lane. Proteins were transferred to PVDF membranes, rinsed in phosphate-buffered saline (PBS) and then blocked in PBS-T containing 10 % BSA (PBS, 0.1 % Tween20, 10 % (w/v) BSA) for 30 min at room temperature. Blots were incubated overnight at 4°C in PBS-T containing 5%BSA containing a 1:2000 dilution of anti-phospho-p38 MAPK (Thr180/Tyr182) antibody (Cell Signaling Technology) and a 1:20000 dilution of anti-FLAG antibody (Sigma-Aldrich, UK). Blots were washed in PBS-T and then incubated for 1 h at room temperature with Anti-rabbit IgG, HRP-linked antibody (Cell Signaling Technology). The blots were washed in PBS-T and the signal was detected using LumiGLO™ (Cell Signaling Technology) or SuperSignal®WestFemto (Thermo Scientific) according to manufacturer's instructions. Phosphorylated Hog1 and GFP-FLAG levels were visualized and quantified using the FluorChem®FC2 (Alpha Innotech) or the FUSION SL™ (Peqlab) systems and the levels of phosphorylated Hog1 were expressed relative to the internal standard (GFP-FLAG).
Extracellular and total glycerol concentrations were determined in stressed and unstressed cells at various time points. Cultures were grown and the stress applied as described above. The Free Glycerol Determination Kit (Sigma-Aldrich) was used to determine glycerol concentrations according to the manufacturer's instructions. To measure extracellular glycerol concentrations, 1.5 ml samples of culture were collected and the cells harvested by centrifugation. Supernatants were transferred to a fresh tube and heated at 100°C for 10 min before their glycerol content was determined. Total glycerol concentrations were measured using 1.5 ml of culture after heating at 100°C for 10 min without prior removal of cells. Cell debris was spun down and the supernatant assayed for glycerol content. Intracellular glycerol concentrations were calculated by deducting the extracellular glycerol concentration from the total glycerol concentration.
This paper is dedicated to Jaroslav Stark, our source of wisdom and inspiration, who tragically died in 2010. TY would like to thank Wei Pang for the valuable discussions on model development and Christopher Brackley for the help on the analysis of frequency response. All authors would like to thank Laura Selway for undertaking some Gpd1 time course experimental work, and Despoina Kaloriti, Anna Tillman, Melanie Puttnam, Elahe Radmaneshfar, George Coghill, Janet Quinn and Mauricio Barahona for general discussions. All authors gratefully acknowledge the funding support by the CRISP project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative. NARG and AJPB were also funded by the European Marie Curie Initial Training Networks, ARIADNE and FINSysB, respectively (PITN-GA-2008-214004). AJPB was also supported by an ERC Advanced Grant (STRIFE: ERC-2009-AdG_20090506).
Model development and analysis: TY, PI. Development of the repeated hyperosmotic shock experiment: APSM, MT, TY, MCR. Experimental data collection: MDJ, EC, MDL, AM. Data analysis: TY. Bioinformatic analysis of signaling component conservation: TT. Frequency response: TY, MCR, APSM, MT. Drafted the paper: TY. Also participated in paper writing: PI, MDJ, APSM, MCR, MDL, NARG, KH, AJPB. Supervision of modeling: CG, JS. Supervision of experiments: AJPB, KH, NARG. Conceived the research: JS, CG, MS, KH, AJPB. All authors approved the final manuscript.


Samba - rsync - why rsync update large directory so slow?
why rsync update large directory so slow?
I have a large directory with about 0 Milillion files in it to backup by network. Server and client both windows.
start cmd /c rsync -avvu --delete %src_dir%/Files/%%i %dst_dir%/Files --password-file=%pwd_file% --log-file=!log_file! --log-file-format=""
In order to make backup faster, I created many rsync intances with "-avvu" options. It seems worked, and only take about 5 hours to complete backup job.
When I restarted the client bat script, and expect very little time to complete backup, but it still cost about 3 hours.
It seems that concurrence makes no effect, I can not figure out what happend, the file checking is so slow?
Does anybody encounted cases like this? Any help will be thankful.
Re: why rsync update large directory so slow?
> I have a large directory with about 0 Milillion files in it to backup by network. Server and client both windows.
>In order to make backup faster, I created many rsync intances with "-avvu" options. It seems worked, and only take about 5 hours to complete backup job.
>When I restarted the client bat script, and expect very little time to complete backup, but it still cost about 3 hours.
>It seems that concurrence makes no effect, I can not figure out what happend, the file checking is so slow?
>Does anybody encounted cases like this? Any help will be thankful.
>>> I have a large directory with about 0 Milillion files in it to backup by network. Server and client both windows.
>>>In order to make backup faster, I created many rsync intances with "-avvu" options. It seems worked, and only take about 5 hours to complete backup job.
>>>When I restarted the client bat script, and expect very little time to complete backup, but it still cost about 3 hours.
>>>It seems that concurrence makes no effect, I can not figure out what happend, the file checking is so slow?
>>>Does anybody encounted cases like this? Any help will be thankful.
>but comparison should very fast, what is the problem?
rsync options, RAM, CPU etc.
is known to be slower. But even then 5h seems slow.
So over 3 million files in 20 minutes. What are your --stats?


If there is anyone who could bring back the noughties-era exposed thong, it's Jennifer Lopez. Just last night, her stylist Rob Zangardi Instagrammed an image of Lopez on set of a video in Miami with DJ Khaled, wearing a cropped white T-shirt, and a pair of low-slung, baggy gray pants with a hiked-up thong attached. The daring whale tail look was from Natasha Zinko's Fall 2018 collection. Lopez accessorized it with handfuls of blingy jewelry, circular shades, a large portable cup emblazoned with her moniker "JLo," and a perfectly polished middle finger. Clearly the singer had no qualms about making a pointed fashion statement.
The exposed thong trend made various cameos on the runway a little over a year ago at the Spring 2018 shows. Since then, Kim Kardashian West has sported a flashy Tom Ford-era Gucci thong in the comfort of her own home, but Lopez might be the first major celeb to take the attention-grabbing trend out and onto the street. Admittedly, she's never be one to shy away from risk-taking style. Lest we forget, this is the woman whose risqué Versace dress at the 2000 Grammy Awards prompted the creation of Google Images. In other words, a full thong-aissance could be on the horizon, thanks to JLo.