If you've been using my books since way back (like early days with The Everyday Vegan and Vive le Vegan), you'll know I haven't always loved all my veggies. In fact, I once declared that you would not find cauliflower in my cookbooks!
Times have changed and now I'm eating my words (and the cruciferous)… because Let Them Eat Vegan has a selection of recipes with cauliflower, including this Almond Roasted Cauliflower.
When I created this recipe I had no idea how much of it I could eat.. or our girls. Normally our girls won't dig into cauliflower, but when I make this roasted cauliflower I double the batch so we all get some!
And, we're not the only cauliflower-converts. I've heard from dozens of people that have tried this recipe and then e-mail saying "I now like cauliflower"!
While I'm still not a fan of raw cauliflower (or raw broccoli… or cabbage), I never thought I'd love eating raw greens like kale and chopping copious amounts of parsley for my lunch salads! It is so true that over time our palates adjust. Our taste buds evolve and we become "open" to more diverse flavors and nuances in foods.
Eating vegan did just that for me. Before becoming vegan I relied on cheese to make foods taste good. I learned there are far more options that taste better – and feel better.
Do you feel this way about eating vegan? What foods do you now love that you didn't before?
Roasting cauliflower is not a new idea, but the addition of almond meal and nutritional yeast makes this side dish something special. Easy . . . and addictive (even if you aren't a huge cauliflower fan)!
Preheat the oven to 425°F. Line a rimmed baking sheet or 8 by 12-inch baking pan with parchment paper. Toss the cauliflower with the olive oil and sea salt (and pepper, if using). Transfer to the prepared pan. Bake for 20 minutes, tossing once or twice. At the 20-minute mark, check the doneness and color of the cauliflower. If it has started to soften, turning a golden color, add the almond meal and nutritional yeast and toss again. If, at 20 minutes, it isn't at this stage, let it bake for another 10 minutes and then add the almond meal and nutritional yeast. Bake for another 10 to 15 minutes or more, tossing again once, until the cauliflower is golden brown and fully softened. Remove from the oven and season with additional salt and pepper, if desired. Serve warm! Serves 2 to 3... or maybe just 1!
Oil-free note: You can reduce or omit the oil. Without oil, the cauliflower will not be as moist and caramelized. Be sure to use parchment paper.
I just made this, and it was delightful. I used no oil at all, AND forgot to toss during the first 20 minutes, and it still turned out great. I took a handful of raw almonds and threw them in my Vitamix. Within one minute, I had perfect almond meal. The combination of the nutritional yeast and almond meal is just really perfect. Finally, I added some garlic powder to the almond meal and nutritional yeast mixture. I'll definitely be making this again.
I used 2 T whole raw almonds, ground it in my spice grinder. Put the cauliflower in a zip top bag with a tsp of grape seed oil and roasted as directed. Wow, it really is amazing! Thank you so much, it's delicious!
I've always been a cauliflower fan, and roasting them is the best way to love them. This recipe is really good, thank you!
Is the nutritional yeast a must for this almond crusted cauliflower recipe?
I think you need to edit your recipage link to https://dreenaburton.com/recipe-page/?recipe_id=6030634.
It currently points to this page itself, rather than to the recipage.
whoops, thanks Shahar – will fix up!
I LOVE LOVE LOVE this recipe. Have made several times, it is YUM!!!!!!
Looks so good! But daughter is allergic to some tree nuts… Could I use coconut flour? Or is almond what makes the dish?
Coconut flour a great idea, and you could also use ground sunflower seeds/pumpkin seeds. Enjoy!
Since we have been heading towards vegan, I too, the cauliflower hater, have begun to love it. I keep making big batches of buffalo cauliflower wings (the fat free version) and my kids and I devour them. Likewise, kale chips go in a flash, as well as many veggies that my kids graze on while I'm chopping/ food prepping. It's too awesome for words! We haven't had cheese in a long while, and my kids love nooch! Amazing.
So terrific, Imaan, keep up the great food prep!!
This sounds really good, but someone in my household is allergic to nuts ( all tree nuts ). Is there an acceptable substitute for almonds?
For sure, you could try ground sunflower seeds or pumpkin seeds or combo of both. Good luck!
My 15 year old daughter not only LOVES this recipe but I find that she raids the refrigerator at night to eat the leftovers. This behavior is unheard of because she often likes to eat junk. I have learned to double the recipe because we easily devour a whole head of cauliflower in one setting and need another for later. Who am I kidding? Even at the first setting we need more than one cauliflower. Of course, I love it too and your recipe is going viral in my family and with my colleagues at work. Thanks so much Dreena!
I found this recipe while searching for sides for Thanksgiving. I've been vegetarian for a couple of years but have struggled to find new ways of making the same ol' vegetables. I've never been a fan of cauliflower, but have recently decided to cook more with it. I am so glad I found this recipe. It is amazing. I have graduated this recipe to main course. I have a lot of non-vegetarian friends and they loved it too.
This was a great treat! Thank you for so many wonderful recipes. I'm fairly new to being (almost) vegan and I love to cook, so I'm sure I'll be trying many of your recipes. I also wanted to share a tip for anyone else who would like to limit their oil/fat intake. I found this great little oil mister at Bed Bath & Beyond. I think it may only be available online, but I asked in the store, and they will ship for free to your home if it's something they don't carry in stock.
Anyway, it was perfect for something like this where you just need a touch of oil for roasting or baking, and this way, you don't have to pay for those expensive baking sprays, which often contain other stuff besides just the oil!
This is so awesome – thanks Dreena! I began making this a while ago and absolutely love it. I also enjoy proselytising its goodness to my friends and then hearing how successful it has been in their families. I've even taking to adding some paprika to the mix – super yum!
Is almond meal made by grinding raw or toasted almonds?
Jackie, yes, usually it is raw almonds ground into a fine powder/flour.
Dreena, this was fabulous! It passed both the "hubby who hates cauliflower" and the 5-year old who "hates all our food" test. Both had thirds and proclaimed it delicious. I did it without oil and it was still terrific. Next time I need to double it. Thanks!
I haven't made this one yet, but just by reviewing it, I'm thinking it might taste good pureed with mashed potatoes? Or even on top of some greens and rice? Sounds good! It's next on my list.
oooh, that sounds like an amazing idea, Anita, with the mashed potatoes – wow!
I never came back to tell you how much I *love* this. I make it all the time. CRAVE it, even. So easy, and so delicious.
This is the Bomb! So good, planning to serve as an app at Superbowl.
I made this tonight with broccoli stems instead of cauliflower. Also good!
In the oven now – can't wait!
awesome! Hope you loved it Gail!
oh my gosh I am reading this as I am eating curry roasted cauliflower! If I had seen these before cooking it up, I would have tried it! Will be making this one soon, sounds most tasty!
I made this–super yummy! Probably the best cauliflower-side dish I've ever had.
Absolutely delicious. I love how you combined such healthy ingredients to make an outstanding dish. We're trying to cut down on salt, so I followed your first addition of salt, slightly increased the almond meal and nutritional yeast amounts, and omitted the salt and pepper at the end. Full of flavor!!!!!
This recipe turned my husband around on cauliflower! I've always enjoyed it, but he's been a cauli-skeptic. 🙂 Now he's fully on board! Thanks for the fab/simple recipe!!
hurrah, hurrah!!! Awesome, Chez… it did the same for our kiddos. Great stuff, thanks for the note!
I love this recipe! I have had roasted cauliflower before, but the addition of almond meal and nutritional yeast makes these unbelieveably good.
Wonderful!! Thank you Gretchen… and what a good point – vegetables have much less fear factor!
YUM! Do you think I could sub almond butter in place of the almond meal and oil?
Erica, if you do, I'd use a raw almond butter, b/c the roasted has a different flavor (most almond butters are roasted unless specifically stated as 'raw'). It might be tricky to coat the cauli tho, b/c the equivalent compared to almond meal will be just a tsp or two… so might take a little time to work it through… but worth a try!
Hi, love your sight. This recipe sounds delicious! Can't wait to try it.
there is nothing like a pan of caramelized roasted cauliflower! it's too hot for me to get roasting veggies just yet, but it's one thing about fall i look forward to. especially brussel sprouts – talk about taste bud evolution on my part once i had them roasted!!
This is actually one of the best recipes in LTEV, in my humble opinion. Sadly, it's been too hot in my 5th floor apartment to make it in the last few months… and I can't wait til it cools down so I can make it again!
I'm willing to believe in you enough to try this.. and because it looks so darn good! Cauliflower isn't always my thing, but if this is anything like the deliciousness that is roasted broccoli..
Mmm, this looks delish. I actually don't think there's a veggie I don't like but roasting cauliflower certainly improves it for me. I really like the herb breadcrumb roasted cauli in appetite for reduction but can't wait to try your variation.
My tastes have completely changed since going vegan. I wouldn't touch ANY fruit and now am an utter fruit bat. Also hated creamy sauces and now am a little obsessed with nut or tofu based creamy things…oh and salad. 5 years ago you would not have seen it pass my lips! Very strange how our tastebuds evolve.
Do you have specific instructions for making almond meal?
It's super easy to do, Vanessa… pop some raw almonds into your food processor and whiz until really fine and crumbly – and watch, b/c it can turn pasty fairly quick. You can also use a blender, but unless it's a high-speed blender I find the processor does better job.
The almond meal and nooch have no problem staying adhere to the cauliflower?
Stays on well Katie! If you didn't add oil it would mostly fall off, but it coats the cauli well and gets right into some of the florets… super tasty!
Boy do I love my cauliflower. Another great Dreena recipe I'm dying to try.
Yes, I do remember in Vive le Vegan (or maybe it was one of your others), where you mention your lack of love for things like eggplant, cabbage, cauliflower. Always thought it was a shame b/c they are such tasty things. Taste buds do change, don't they?
So true, Janae, and eggplant is another that I know really like – when prepared well. If it's just poached/steamed, that doesn't appeal to me, but grilled nicely or roasted, can be so tasty! We all evolve, huh?
I never would have thought about using almond meal with roasted cauliflower. Great and easy tip! Can't wait to try!
Thanks Debby, it makes the cauliflower taste just a little nutty, and with the nooch it's really rich tasting!
Since becoming vegan eighteen months ago, I've discovered vegetables that I would never have tried beforehand. I am addicted to ratatouille, when before it just seemed like lots of lumpy veg.
Oh gosh, Kate – yes, ratatouille!!! I love it as well and haven't made it in a long time.


In the Guriners' world, with snow shoes, you can experience unforgettable moments in unspoilt natural beauty while discovering the Walser culture. You will be amazed by the hospitality you will find in Bosco Gurin, the highest village in Ticino situated in the upper Vallemaggia (Maggia valley).
In winter, Bosco Gurin is synonymous with winter sports. Leave your car and, with snow shoes, venture out to explore an alpine area which has been shaped by the Walser people through the centuries.
As you walk up among majestic larches, you will discover the "Gadumschi" as well as other typical buildings that escape the fleeting glimpse of the skiers shooting down the snow-covered slope.
A picture-postcard landscape surrounded by high peaks and the sunshine that bathes the wide valley of Bosco Gurin will accompany you along the climb. Once you get to Grossalp, a small settlement where you will find the hut of the same name, which shelters and delights mountain lovers, you may decide to continue up to the mid-line station of the chairlift or to turn back.


You'll see the terms REALTOR® and MLS® system used frequently in this column, as well as out in the world of real estate advertising. The terms are now ubiquitous enough that most people have at least a basic idea of what they think those terms represent. But you might be surprised to know that both of them are registered trademarks owned by the Canadian Real Estate Association (CREA), and used under license by real estate boards and associations across Canada.
To meet their obligations, REALTORS® pledge to observe the spirit of the Code in all of their activities and conduct their business in accordance with the Standards of Business Practice and the Golden Rule – do unto others as you would have them do unto you.
Now let's talk about the term MLS®. It's not a noun, or a thing, but an adjective that refers to a standard of service – the MLS® Services – that are provided by CREA members. Local real estate boards or associations license the term MLS® from CREA to use to describe their co-operative selling systems, referred to as MLS® systems. An MLS® system includes an inventory of listings of participating REALTORS® and ensures a certain level of accuracy of information, professionalism and co-operating amongst REALTORS® to effect the purchase and sale of real estate. The Board ensures that level of accuracy and professionalism by enforcing a set of Board-specific MLS® Rules and Regulations that apply to all members' listings.
Only a real estate professional who is also a REALTOR® can list properties on his or her Board's local MLS® system. When your home is listed on the MLS® system, all REALTORS® can view it, creating a much wider pool of potential buyers than a sign on your lawn would offer. If you're looking for a new home, working with a REALTOR® gains you access to all the properties listed on the MLS® system. He or she can set up a custom search that e-mails you details of properties that meet your criteria. It's a service that only a REALTOR® can offer you.
REALTORS® are proud of the professional real estate services they provide and the Code of Ethics they adhere to.


Reds coach Brad Thorn is not disheartened by his side's showing in their Super Rugby opener, preaching positivity after his team fought on after being reduced to 14 men for 70 minutes.
The Reds were well beaten by an impressive, rejuvenated Rebels but the night was marred by Scott Higginbotham's red card for a shoulder charge that made contact with Matt Philip's head.
Higginbotham will face a sanction in the coming days and neither the Reds captain or coach wanted to add too much fuel to the fire.
"It's a physical game... it's a tricky one," Thorn said.
"They're trying their best and with 70 minutes to go, she's a big call.
"It's tightened up more and more every year.
"Go down to Marathon Stadium in the mid 90s and it was game on.
"They're very conscious about where it has got to now - protecting players - and it's a fine line in a contact sport.
"We want to play physical so it's a tough one."
Outside of the red card, Thorn was relatively positive about the 45-19 loss."I took a lot from it," he said.
"I loved the fight of the guys, I loved how they kept competing.
"There are still a lot of young guys out there and it was a lot to take on for a young group.
"Unfortunately a few things happened tonight that weren't great but sometimes that affords you the opportunity to test your character, show what you're about and I think there were some good signs in there as well."
Once they learn Higginbotham's fate attention will turn to the Brumbies, who will present an even greater challenge for Thorn's side.
"I was pleased with what they showed me about who they are but we have got to get smarter and continue to build our game," Thorn said.
"The Brumbies are good at their set piece, at the breakdown and they've been together for a long time.
"They're used to playing with each other, they've got their game so we have just got to work hard in all areas."
The Reds take on the Brumbies at Suncorp Stadium on Friday March 2, kicking off at 7pm local, 8pm AEDT, LIVE on FOX SPORTS. Buy tickets here.


BCA's minimalist model for high performance riding, designed specifically for snowmobilers.
Panel access, zippered tool compartment, hip belt pocket, removable leg strap, and compatible with snowboard carry attachment. Trigger is in right shoulder strap for left-handed deployment (so you can keep your right hand on the throttle). Cylinder sold separately.
Features: Panel access, zippered tool compartment, hip belt pocket, removable leg strap, compatible with snowboard carry attachment.


VEC Creative is a results-driven print, web and multimedia design agency, providing innovative and effective visual communications for a diverse range of clients. We are uniquely qualified to meet your needs creating fresh, cutting-edge collateral seamlessly across multiple design formats that ultimately boosting your bottom line.
VEC Creative was established specifically to meet the need for expert graphic and web design and development for our clients.
We provide a wide range of design services to help our clients create and build successful marketing communications.
My design career started in 1996 working for a finance company. In those days, everyone wore multiple hats, and mine was just a bit more creative than the rest. It was a perfect fit and I have been wearing that hat ever since.
Since those early days, my talents have been sought by companies in several industries to create the visuals for many types of projects including corporate branding, multimedia, photography, and animation, alongside traditional print and web design.
With visual design being my fortay, I have also proven herself to be a great illustrator, fine artist, and writer. Some of my off-the-clock projects include being the past editor of the Merrimack Valley Camera Club monthly newsletter, Focal Points; moderator of The Digital Darkroom, a Yahoo group with over 2,000 members; and an avid product, nature, and landscape photographer, watercolorist and sketch artist. My photography work has been published in the Boston Business Journal, The Boston Globe, has won local, national, and international awards, and has been acquired by many commercial corporations.


Take the Toltec apprenticeship journey don Miguel Ruiz Jr. learned from his father, don Miguel Ruiz Sr., and his grandmother, Madre Sarita.
The Mastery of Self uses the wisdom of Toltec philosophy to explain how a person can liberate themselves from illusory beliefs and live with authenticity. The Toltec tradition is an instrument by which life teaches us how to be free and enjoy every moment that life has to give. This is the path that don Miguel Ruiz Jr. took throughout his apprenticeship with his father, don Miguel Ruiz Sr., and his grandmother, Madre Sarita.
Save $100 on this course when you also attend The Four Agreements for a Better Life. To take advantage of this offer, please call Omega registration at 877.944.2002. This offer cannot be combined with other discounts.
The Mastery of Self: A Toltec Guide to Personal Freedom by Don Miguel Ruiz, Jr.
The Five Levels of Attachment: Toltec Wisdom for the Modern World by Don Miguel Ruiz, Jr.


text:
Jaminton Leandro Campaz (born 24 May 2000) is a Colombian professional footballer who plays as an attacking midfielder for Brazilian club Grêmio. He has made one appearance for the Colombia national team.

Club career
Campaz joined Campeonato Brasileiro Série A club Grêmio from Deportes Tolima in August 2021, having agreed a contract until December 2025.

International career
Campaz was selected for the Colombia national team for 2021 Copa América and made his debut on 17 June 2021 in a match against Venezuela.

Career statistics

Club

International

Honours
Grêmio
Campeonato Gaúcho: 2022
Recopa Gaúcha: 2022

References

2000 births
Living people
People from Ibagué
Colombian footballers
Association football midfielders
Colombia youth international footballers
Colombia international footballers
2021 Copa América players
Categoría Primera A players
Deportes Tolima footballers
Campeonato Brasileiro Série A players
Campeonato Brasileiro Série B players
Grêmio Foot-Ball Porto Alegrense players
Colombian expatriate footballers
Colombian expatriate sportspeople in Brazil
Expatriate footballers in Brazil

redpajama_set_name: RedPajamaWikipedia


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You are here: Home › Category Archives › women in technology
Dorothy Hodgkin and the Structure of Penicilin
29. July 2014 Tabea Tietz
Dorothy Hodgkin (1910 – 1994) On July 29, 1994, British chemist and Nobel Laureate Dorothy Mary Hodgkin passed away. She advanced the technique of X-ray crystallography, a method used to determine the three-dimensional structures of biomolecules. Among her most influential discoveries are the confirmation of the structure of penicillin. Dorothy Crowfoot's (late Hodgkin's) interest in chemistry started around the age of only 10. Her parents were involved in education projects in Egypt and Sudan…
Rosalind Franklin and the Beauty of the DNA Structure
27. July 2014 Harald Sack
Rosalind Franklin (1920–1958) On July 25, 1920, British biophysicist and X-ray crystallographer Rosalind Elsie Franklin was born. She made the first clear X-ray images of DNA's structure. Her work was described as the most beautiful X-ray photographs ever taken. Franklin's 'Photo 51' informed Crick and Watson of DNA's double helix structure for which they were awarded a Nobel Prize. Rosalind Franklin was born in Notting Hill, London, as the second of five children into…
Maria Goeppert Mayer and the Nuclear Shell Model
28. June 2014 Harald Sack
Maria Goeppert Mayer (1906-1972) On June 28, 1906, German-born Physicist Maria Goeppert Mayer was born. She was awarded the Nobel Prize in Physics for proposing the nuclear shell model of the atomic nucleus. She was the second female Nobel laureate in physics, after Marie Curie. Maria Goeppert was born in Kattowitz, a city in Prussia, the only child of Friedrich Goeppert and his wife Maria. At age 4, she moved with her…
Florence Nightingale – The Lady with the Lamp
12. May 2014 Tabea Tietz
On May 12, 1820, celebrated British social reformer and statistician Florence Nightingale was born. She is best known for being the founder of modern nursing. She came to prominence while serving as a nurse during the Crimean War, where she tended to wounded soldiers. She was known as "The Lady with the Lamp" after her habit of making rounds at night. Youth and Education It is known that Florence Nightingale was a…
Mary the Jewess and the Origins of Chemistry
8. May 2014 Harald Sack
Mary the Jewess (also known as Maria Prophetissima or Miriam the Prophetess) is a figure who first appeared in the works of the Gnostic Christian writer Zosimos of Panopolis, whose sources for this are not clear. On the basis of Zosimos's comments, she lived between the first and third centuries A.D. She is credited with the invention of several kinds of chemical apparatus and is considered to be the first true alchemist of the…
Harriet Quimby – the First Woman to Fly Across the English Channel
16. April 2014 Tabea Tietz
On April 16, 1912, Harriet Quimby became the first woman to fly across the English Channel. She was the the first woman to gain a pilot's license in the United States. Although Quimby lived only to the age of thirty-seven, she had a major influence upon the role of women in aviation. Harriet Quimby was born into a farmer's family in Michigan and moved to San Francisco in order to become an…
A great man whose only fault was being a woman – Émilie du Châtelet
17. December 2013 Harald Sack
Émilie du Châtelet (1706-1749) On December 17, 1706, French mathematician, physicist, and author Gabrielle Émilie Le Tonnelier de Breteuil, marquise du Châtelet was born. Her major achievement is considered to be her translation and commentary on Isaac Newton's work Principia Mathematica, which still is the standard French translation of Newton's work today. Philosopher and author Voltaire, one of her lovers, once declared in a letter to his friend King Frederick II of…
Trotula of Salerno and Women's Health in the Middle Ages
Trotula of Salerno from a manuscript c. the late 12th or early 13th century Although neither her birthday nor her date of death is known to us, today we want to point out a rather prominent woman in science of which you might never have heard of unless you know your way around in the history of medicine. Trotula of Salerno lived in the 11th or 12th century AD and was a…
Hypatia – the first Woman in Mathematics
10. December 2013 Tabea Tietz
Hypatia of Alexandria The Neoplatonian philosopher Hypatia of Alexandria, Egypt, was the first well-documented woman in mathematics. Her actual date of birth is unknown, although considered somewhen between 350 and 370 AD. She was the head of the Platonist school at Alexandria and additionally taught philosophy and astronomy. Hypatia was taught in mathematics and astronomy by her father, who was well known for his studies at the Alexandrian School. It is unknown,…
Freedom within Limits – the Education Principles of Maria Montessori
31. August 2013 Tabea Tietz
Maria Montessori(1870 – 1952) On August 31, 1870, Italian physician and educator Maria Tecla Artemesia Montessori was born. She is probably best known for the philosophy of education that bears her name, and her writing on scientific pedagogy. Her educational method is in use today in public and private schools throughout the world. Maria Montessori was pretty well educated herself and mostly supported by her mother to continue school. She entered a…

redpajama_set_name: RedPajamaCommonCrawl


This is the last of the Royal Collection and by far it is the nicest.
A really deep plum purple with gold, pink and purple sparkle throughout. I liked it so much that I actually kept this on, unlike the others which I just swatched.
Above is without a topcoat and below is with. I like it both ways.
This is the kind of colour that Barry M should have focussed on in my opinion, a lovely rich jewel, the others where a bit washed out or brassy.


Visit 1,000-year-old megaliths discovered on a cattle ranch in Brazil. The site sheds new light on how indigenous people of the Amazon may have lived.CreditCreditDado Galdieri for The New York Times. Technology by Samsung.
Back in the late 19th century, the Swiss zoologist Emílio Goeldi had spotted megaliths — large monumental stones — on an expedition through Brazil's frontier with French Guiana. Other scholars, including the pioneering American archaeologist Betty Meggers, also came across such sites, but argued that the Amazon was inhospitable to complex human settlements.
"We've seen a lot of similar claims, but it takes more than a circle of standing stones to get to a Stonehenge," said Jarita Holbrook, a scholar of physics and cultural astronomy at the University of the Western Cape in South Africa, citing the need for more findings about Rego Grande's characteristics and how the site was used by the people who built it.
"The stones of Rego Grande are quite extraordinary and in their irregularity may have their own unique meaning, different from other megalithic sites around the world," Mr. Malville said, raising the possibility that Rego Grande reflects the importance in Amazonian cultures of animism, the attribution of a soul to entities in nature and even inanimate objects.
The Calçoene Journal article on Dec. 15, about archaeological discoveries in the Brazilian Amazon that have upended earlier views about the human history of the Amazon Basin, misstated the given name of a scholar at the University of the Western Cape in South Africa who cited the need for more research on an arrangement of megaliths in Calçoene, Brazil, that resembles Stonehenge. She is Jarita Holbrook, not Jovita. The article also misstated, at one point, the surname of a physicist at the University of Colorado who called the stones "quite extraordinary." As noted correctly elsewhere in the article, he is John McKim Malville, not Melville.
Follow Simon Romero on Twitter @viaSimonRomero.


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There is a boy named hiccup who lives with his clan (Viking) in the cold and snowy village named berk in northern regions. This clan has an old pests problem. If most places have mice and mosquitoes, they have dragons. The first scene in the movie featuring scenes The village is attacked by dragons. The dragon steal their food (mostly sheep) and burned their homes. That's why almost every single building on berk is relatively brand new.
How to Train Your Dragon focuses on the relationship between the hiccup with a dragon which later he named toothless. Hiccup is a unique viking boy, a weakling and a screw up who desperately wants to show his father that he is worth something, a viking kid who happens to be more technically than brawn, more scrawny than big body, and this of course makes him apart from the rest of his warrior clan folks. Hiccup trying so hard to prove to father and his clan he can do things that can be done by common viking peoples, such as killing a dragon.
In the heat of battle, Hiccup bring downs a flying dragon with a bolas-shooting cannon made by him. The dragon lands in the forest not far from the village but no one believes that he hit a dragon even his father. The next day hiccup through the forest to find the dragon and he found out that the dragon is a night fury ( a dragon who no one ever see it, no one ever kill it ). poor hiccup, he is always trying so hard to prove his existance but when the time comes he unable to do anything. instead killing the dragon he release it. Dragon is a smart creature, hiccup and the dragon became a friend.
Being friends with a dragon hiccup aware that the dragon is not the wild animals and likes to steal food. especially after he discovered that the dragons were forced to steal food for fear of the great dragon who inhabit their nests. Hiccup tried to tell this to father and his clan, but her father had upset and bring toothless as a signpost to the dragon's lair. .
He father and the clan warrior who did not know about the great dragon broke through the dragon's lair and then ran away when the great dragon came out and attacked them. Then, hiccup came with his friends riding the dragon, freeing toothless and then fight against the great dragon, hiccup win and become the hero of the village. he never killed a dragon before, and the first one he kill is a Great dragon.
All in all, the story is a top one, the music is gorgeous, the animation fantastic, the lesson valuable and the characters true and pure. There is plenty of laughs, and fun for all ages.


hello, I need a Design (presentation template) to present my service, It is a service for a website creation. It should be very professional and very appealing Design.
- Under the price, a part with additional costs for server, domain etc.
- at the end a footer for contact.
It would be best if you edit it via Photoshop or XD, so that I can later edit it and convert it to PDF.


text:
"""Parser for BigMLer

"""

import argparse
import pkg_resources

from bigmler.options.common import get_common_options
from bigmler.options.delete import get_delete_options
from bigmler.options.source import get_source_options
from bigmler.options.dataset import get_dataset_options
from bigmler.options.dataset_trans import get_dataset_trans_options
from bigmler.options.test import get_test_options
from bigmler.options.multilabel import get_multi_label_options
from bigmler.options.main import get_main_options
from bigmler.options.analyze import get_analyze_options
from bigmler.options.whizzml import get_whizzml_options
from bigmler.options.cluster import get_cluster_options
from bigmler.options.anomaly import get_anomaly_options
from bigmler.options.sample import get_sample_options
from bigmler.options.report import get_report_options
from bigmler.options.reify import get_reify_options
from bigmler.options.project import get_project_options
from bigmler.options.export import get_export_options
from bigmler.options.association import get_association_options
from bigmler.options.fusion import get_fusion_options
from bigmler.options.logisticregression import get_logistic_regression_options
from bigmler.options.linearregression import get_linear_regression_options
from bigmler.options.pca import get_pca_options
from bigmler.options.topicmodel import get_topic_model_options
from bigmler.options.timeseries import get_time_series_options
from bigmler.options.deepnet import get_deepnet_options
from bigmler.options.execute import get_execute_options
from bigmler.options.retrain import get_retrain_options
from bigmler.options.externalconnector import get_external_connector_options

SUBCOMMANDS = ["main", "analyze", "cluster", "anomaly", "sample", "dataset",
               "delete", "report", "reify", "project", "association",
               "logistic-regression", "topic-model", "time-series",
               "execute", "whizzml", "export", "deepnet", "retrain",
               "linear-regression", "pca", "fusion", "connector", "source"]

MAIN = SUBCOMMANDS[0]

def parser_add_options(parser, options):
    """Adds the options to the sucommand parser

    """
    for option, properties in sorted(list(options.items()), key=lambda x: x[0]):
        parser.add_argument(option, **properties)

#pylint: disable=locally-disabled,dangerous-default-value
def create_parser(general_defaults={}, constants={}, subcommand=MAIN):
    """Sets the accepted command options, variables, defaults and help

    """

    defaults = general_defaults['BigMLer']

    version = pkg_resources.require("BigMLer")[0].version
    version_text = """\
BigMLer %s - A Higher Level API to BigML's API
Copyright 2012-2022 BigML

Licensed under the Apache License, Version 2.0 (the \"License\"); you may
not use this file except in compliance with the License. You may obtain
a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations
under the License.""" % version
    constants['version_text'] = version_text
    main_parser = argparse.ArgumentParser(
        description="A higher level API to BigML's API.",
        epilog="Happy predictive modeling!",
        formatter_class=argparse.RawTextHelpFormatter)
    main_parser.add_argument('--version',
                             action='version', version=version_text)
    subparsers = main_parser.add_subparsers()

    # list of options
    common_options = get_common_options(defaults=defaults, constants=constants)
    delete_options = get_delete_options(defaults=defaults)
    source_options = get_source_options(defaults=defaults)
    dataset_options = get_dataset_options(defaults=defaults)
    test_options = get_test_options(defaults=defaults)
    multi_label_options = get_multi_label_options(defaults=defaults)

    # subcommand options
    subcommand_options = {}
    # specific options
    subcommand_options["main"] = get_main_options(defaults=defaults,
                                                  constants=constants)
    # general options
    subcommand_options["main"].update(common_options)
    subcommand_options["main"].update(source_options)
    subcommand_options["main"].update(dataset_options)
    subcommand_options["main"].update(multi_label_options)
    subcommand_options["main"].update(test_options)
    subcommand_options["main"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--model-tag': delete_options['--model-tag'],
        '--ensemble-tag': delete_options['--ensemble-tag'],
        '--prediction-tag': delete_options['--prediction-tag'],
        '--batch-prediction-tag': delete_options['--batch-prediction-tag']})

    main_options = subcommand_options["main"]

    subcommand_options["dataset"] = dataset_options
    subcommand_options["dataset"].update(get_dataset_trans_options( \
        defaults=defaults))
    subcommand_options["dataset"].update(common_options)
    subcommand_options["dataset"].update(source_options)
    subcommand_options["main"].update(multi_label_options)
    subcommand_options["dataset"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--max-categories': subcommand_options['main']['--max-categories'],
        '--labels': subcommand_options['main']['--labels'],
        '--multi-label': subcommand_options['main']['--multi-label'],
        '--objective': subcommand_options['main']['--objective'],
        '--reports': subcommand_options['main']['--reports']})

    dataset_sampling_options = { \
        '--replacement': main_options['--replacement'],
        '--sample-rate': main_options['--sample-rate'],
        '--seed': main_options['--seed']}

    subcommand_options["source"] = source_options
    subcommand_options["source"].update(common_options)

    defaults = general_defaults["BigMLer whizzml"]
    subcommand_options["whizzml"] = get_whizzml_options(defaults=defaults)
    subcommand_options["whizzml"].update(common_options)
    defaults = general_defaults["BigMLer analyze"]
    subcommand_options["analyze"] = get_analyze_options(defaults=defaults)
    subcommand_options["analyze"].update(common_options)
    # we add the options that should be transmitted to bigmler main subcommands
    # in analyze
    subcommand_options["analyze"].update({
        '--dataset': dataset_options['--dataset'],
        '--objective': main_options['--objective'],
        '--max-parallel-models': main_options['--max-parallel-models'],
        '--max-parallel-evaluations': main_options[
            '--max-parallel-evaluations'],
        '--model-fields': main_options['--model-fields'],
        '--balance': main_options['--balance'],
        '--no-balance': main_options['--no-balance'],
        '--number-of-models': main_options['--number-of-models'],
        '--missing-splits': main_options['--missing-splits'],
        '--pruning': main_options['--pruning'],
        '--weight-field': main_options['--weight-field'],
        '--ensemble-sample-no-replacement': main_options[ \
            '--ensemble-sample-no-replacement'],
        '--ensemble-sample-rate': main_options['--ensemble-sample-rate'],
        '--ensemble-sample-seed': main_options['--ensemble-sample-seed'],
        '--objective-weights': main_options['--objective-weights'],
        '--model-attributes': main_options['--model-attributes'],
        '--ensemble-attributes': main_options['--ensemble-attributes'],
        '--boosting': main_options['--boosting'],
        '--boosting-iterations': main_options['--boosting-iterations'],
        '--early-holdout': main_options['--early-holdout'],
        '--no-early-out-of-bag': main_options['--no-early-out-of-bag'],
        '--learning-rate': main_options['--learning-rate'],
        '--no-step-out-of-bag': main_options['--no-step-out-of-bag'],
        '--randomize': main_options['--randomize'],
        '--no-csv': main_options['--no-csv'],
        '--no-no-csv': main_options['--no-no-csv'],
        '--to-dataset': main_options['--to-dataset'],
        '--datasets': main_options['--datasets'],
        '--dataset-file': main_options['--dataset-file'],
        '--dataset-tag': delete_options['--dataset-tag']})
    subcommand_options["analyze"].update(dataset_sampling_options)

    defaults = general_defaults["BigMLer cluster"]
    subcommand_options["cluster"] = get_cluster_options(defaults=defaults)
    # general options
    subcommand_options["cluster"].update(common_options)
    subcommand_options["cluster"].update(source_options)
    subcommand_options["cluster"].update(dataset_options)
    subcommand_options["cluster"].update(test_options)
    subcommand_options["cluster"].update(dataset_sampling_options)
    subcommand_options["cluster"].update({
        '--cpp': main_options['--cpp'],
        '--fields-map': main_options['--fields-map'],
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--cluster-tag': delete_options['--cluster-tag'],
        '--centroid-tag': delete_options['--centroid-tag'],
        '--batch-centroid-tag': delete_options['--batch-centroid-tag'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--no-csv': main_options['--no-csv'],
        '--no-no-csv': main_options['--no-no-csv'],
        '--to-dataset': main_options['--to-dataset']})

    defaults = general_defaults["BigMLer anomaly"]
    subcommand_options["anomaly"] = get_anomaly_options(defaults=defaults)
    # general options
    subcommand_options["anomaly"].update(common_options)
    subcommand_options["anomaly"].update(source_options)
    subcommand_options["anomaly"].update(dataset_options)
    subcommand_options["anomaly"].update(test_options)
    subcommand_options["anomaly"].update(dataset_sampling_options)
    subcommand_options["anomaly"].update({
        '--cpp': main_options['--cpp'],
        '--fields-map': main_options['--fields-map'],
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--anomaly-tag': delete_options['--anomaly-tag'],
        '--anomaly-score-tag': delete_options['--anomaly-score-tag'],
        '--batch-anomaly-score-tag': delete_options[
            '--batch-anomaly-score-tag'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--no-csv': main_options['--no-csv'],
        '--no-no-csv': main_options['--no-no-csv'],
        '--to-dataset': main_options['--to-dataset']})

    defaults = general_defaults["BigMLer sample"]
    subcommand_options["sample"] = get_sample_options(defaults=defaults)
    # general options
    subcommand_options["sample"].update(common_options)
    subcommand_options["sample"].update(source_options)
    subcommand_options["sample"].update(dataset_options)
    subcommand_options["sample"].update({
        '--cpp': main_options['--cpp'],
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--sample-tag': delete_options['--sample-tag'],
        '--reports': main_options['--reports']})

    subcommand_options["delete"] = delete_options
    subcommand_options["delete"].update(common_options)

    defaults = general_defaults["BigMLer report"]
    subcommand_options["report"] = get_report_options(defaults=defaults)

    defaults = general_defaults["BigMLer export"]
    subcommand_options["export"] = get_export_options(defaults=defaults)
    export_common_options_list = ['clear-logs', 'username', 'api-key',
                                  'version', 'org-project',
                                  'output-dir', 'verbosity',
                                  'resume', 'stack-level', 'debug', 'store']
    export_common_options = {}
    for option in export_common_options_list:
        option = '--%s' % option
        export_common_options.update({option: common_options[option]})
    subcommand_options["export"].update(export_common_options)

    defaults = general_defaults["BigMLer reify"]
    subcommand_options["reify"] = get_reify_options(defaults=defaults)
    reify_common_options_list = ['clear-logs', 'username', 'api-key',
                                 'version', 'org-project',
                                 'output-dir', 'verbosity',
                                 'resume', 'stack-level', 'debug', 'store']
    reify_common_options = {}
    for option in reify_common_options_list:
        option = '--%s' % option
        reify_common_options.update({option: common_options[option]})
    subcommand_options["reify"].update(reify_common_options)

    subcommand_options["project"] = get_project_options(defaults=defaults)
    subcommand_options["project"].update({
        '--project': source_options['--project'],
        '--project-id': source_options['--project-id'],
        '--name': common_options['--name'],
        '--description': common_options['--description'],
        '--category': common_options['--category'],
        '--tag': common_options['--tag'],
        '--resources-file': main_options['--resources-log']})
    project_common_options = {}
    for option in reify_common_options_list:
        option = '--%s' % option
        project_common_options.update({option: common_options[option]})
    subcommand_options["project"].update(project_common_options)

    defaults = general_defaults["BigMLer connector"]
    subcommand_options["connector"] = get_external_connector_options( \
        defaults=defaults)
    subcommand_options["connector"].update({
        '--name': common_options['--name'],
        '--description': common_options['--description'],
        '--category': common_options['--category'],
        '--tag': common_options['--tag'],
        '--project-id': source_options['--project-id'],
        '--resources-file': main_options['--resources-log']})
    connector_common_options = {}
    for option in reify_common_options_list:
        option = '--%s' % option
        connector_common_options.update({option: common_options[option]})
    subcommand_options["connector"].update(connector_common_options)

    defaults = general_defaults["BigMLer association"]
    subcommand_options["association"] = get_association_options( \
        defaults=defaults)
    # general options
    subcommand_options["association"].update(common_options)
    subcommand_options["association"].update(source_options)
    subcommand_options["association"].update(dataset_options)
    subcommand_options["association"].update(test_options)
    subcommand_options["association"].update(dataset_sampling_options)
    subcommand_options["association"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--association-tag': delete_options['--association-tag'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--no-csv': main_options['--no-csv'],
        '--no-no-csv': main_options['--no-no-csv']})

    defaults = general_defaults["BigMLer logistic regression"]
    subcommand_options["logistic-regression"] = \
        get_logistic_regression_options( \
        defaults=defaults)
    # general options
    subcommand_options["logistic-regression"].update(common_options)
    subcommand_options["logistic-regression"].update(source_options)
    subcommand_options["logistic-regression"].update(dataset_options)
    subcommand_options["logistic-regression"].update(test_options)
    subcommand_options["logistic-regression"].update(dataset_sampling_options)
    subcommand_options["logistic-regression"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--logistic-regression-tag': delete_options[
            '--logistic-regression-tag'],
        '--objective': main_options['--objective'],
        '--evaluate': main_options['--evaluate'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--to-dataset': main_options['--to-dataset'],
        '--no-csv': main_options['--no-csv'],
        '--fields-map': main_options['--fields-map'],
        '--dataset-off': main_options['--dataset-off'],
        '--operating-point': main_options['--operating-point'],
        '--max-parallel-evaluations': main_options[
            '--max-parallel-evaluations'],
        '--cross-validation-rate': main_options[
            '--cross-validation-rate'],
        '--number-of-evaluations': main_options[
            '--number-of-evaluations'],
        '--batch-prediction-attributes': main_options[
            '--batch-prediction-attributes'],
        '--prediction-attributes': main_options[
            '--prediction-attributes'],
        '--prediction-tag': delete_options['--prediction-tag'],
        '--batch-prediction-tag': delete_options['--batch-prediction-tag'],
        '--no-no-csv': main_options['--no-no-csv']})

    defaults = general_defaults["BigMLer linear regression"]
    subcommand_options["linear-regression"] = \
        get_linear_regression_options( \
        defaults=defaults)
    # general options
    subcommand_options["linear-regression"].update(common_options)
    subcommand_options["linear-regression"].update(source_options)
    subcommand_options["linear-regression"].update(dataset_options)
    subcommand_options["linear-regression"].update(test_options)
    subcommand_options["linear-regression"].update(dataset_sampling_options)
    subcommand_options["linear-regression"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--linear-regression-tag': delete_options[
            '--linear-regression-tag'],
        '--objective': main_options['--objective'],
        '--evaluate': main_options['--evaluate'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--to-dataset': main_options['--to-dataset'],
        '--no-csv': main_options['--no-csv'],
        '--fields-map': main_options['--fields-map'],
        '--dataset-off': main_options['--dataset-off'],
        '--field-codings': subcommand_options['logistic-regression'][ \
            '--field-codings'],
        '--bias': subcommand_options['logistic-regression'][ \
            '--bias'],
        '--no-bias': subcommand_options['logistic-regression'][ \
            '--no-bias'],
        '--max-parallel-evaluations': main_options[
            '--max-parallel-evaluations'],
        '--cross-validation-rate': main_options[
            '--cross-validation-rate'],
        '--number-of-evaluations': main_options[
            '--number-of-evaluations'],
        '--batch-prediction-attributes': main_options[
            '--batch-prediction-attributes'],
        '--prediction-attributes': main_options[
            '--prediction-attributes'],
        '--prediction-tag': delete_options['--prediction-tag'],
        '--batch-prediction-tag': delete_options['--batch-prediction-tag'],
        '--no-no-csv': main_options['--no-no-csv']})

    # time-series
    defaults = general_defaults["BigMLer time-series"]
    subcommand_options["time-series"] = get_time_series_options( \
        defaults=defaults)

    subcommand_options["time-series"].update(common_options)
    subcommand_options["time-series"].update(source_options)
    subcommand_options["time-series"].update(dataset_options)
    subcommand_options["time-series"].update(test_options)
    subcommand_options["time-series"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--fields-map': main_options['--fields-map'],
        '--time-series-tag': delete_options[
            '--time-series-tag'],
        '--objective': main_options['--objective'],
        '--evaluate': main_options['--evaluate'],
        '--prediction-header': main_options['--prediction-header'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote']})

    defaults = general_defaults["BigMLer execute"]
    subcommand_options["execute"] = get_execute_options(defaults=defaults)
    execute_common_options = {}
    for option, option_value in common_options.items():
        execute_common_options.update({option: option_value})
    subcommand_options["execute"].update(execute_common_options)
    subcommand_options["execute"].update(
        {'--project': source_options['--project'],
         '--upgrade': subcommand_options['whizzml']['--upgrade'],
         '--project-id': source_options['--project-id'],
         '--script-tag': delete_options['--script-tag'],
         '--library-tag': delete_options['--library-tag'],
         '--execution-tag': delete_options['--execution-tag']})

    defaults = {}
    subcommand_options["retrain"] = get_retrain_options(defaults=defaults)
    # shared options are like the ones in reify
    subcommand_options["retrain"].update(reify_common_options)
    subcommand_options["retrain"].update( \
        {'--output': subcommand_options['reify']['--output'],
         '--org-project': common_options['--org-project'],
         '--upgrade': subcommand_options['reify']['--upgrade'],
         '--model-tag': delete_options['--model-tag'],
         '--ensemble-tag': delete_options['--ensemble-tag'],
         '--logistic-regression-tag': delete_options['--logistic-regression-tag'],
         '--deepnet-tag': delete_options['--deepnet-tag'],
         '--cluster-tag': delete_options['--cluster-tag'],
         '--anomaly-tag': delete_options['--anomaly-tag'],
         '--association-tag': delete_options['--association-tag'],
         '--time-series-tag': delete_options['--time-series-tag'],
         '--topic-model-tag': delete_options['--topic-model-tag']})

    defaults = general_defaults["BigMLer topic model"]
    subcommand_options["topic-model"] = get_topic_model_options(
        defaults=defaults)
    # general options
    subcommand_options["topic-model"].update(common_options)
    subcommand_options["topic-model"].update(source_options)
    subcommand_options["topic-model"].update(dataset_options)
    subcommand_options["topic-model"].update(test_options)
    subcommand_options["topic-model"].update(dataset_sampling_options)
    subcommand_options["topic-model"].update({
        '--cpp': main_options['--cpp'],
        '--fields-map': main_options['--fields-map'],
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--topic-model-tag': delete_options['--topic-model-tag'],
        '--topic-distribution-tag': delete_options['--topic-distribution-tag'],
        '--batch-topic-distribution-tag': delete_options[ \
            '--batch-topic-distribution-tag'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--no-csv': main_options['--no-csv'],
        '--no-no-csv': main_options['--no-no-csv'],
        '--to-dataset': main_options['--to-dataset']})

    defaults = general_defaults["BigMLer deepnet"]
    subcommand_options["deepnet"] = \
        get_deepnet_options(defaults=defaults)
    # general options
    subcommand_options["deepnet"].update(common_options)
    subcommand_options["deepnet"].update(source_options)
    subcommand_options["deepnet"].update(dataset_options)
    subcommand_options["deepnet"].update(test_options)
    subcommand_options["deepnet"].update(dataset_sampling_options)
    subcommand_options["deepnet"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--deepnet-tag': delete_options[
            '--deepnet-tag'],
        '--objective': main_options['--objective'],
        '--evaluate': main_options['--evaluate'],
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--default-numeric-value': main_options['--default-numeric-value'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--to-dataset': main_options['--to-dataset'],
        '--no-csv': main_options['--no-csv'],
        '--fields-map': main_options['--fields-map'],
        '--operating-point': main_options['--operating-point'],
        '--dataset-off': main_options['--dataset-off'],
        '--max-parallel-evaluations': main_options[
            '--max-parallel-evaluations'],
        '--cross-validation-rate': main_options[
            '--cross-validation-rate'],
        '--number-of-evaluations': main_options[
            '--number-of-evaluations'],
        '--batch-prediction-attributes': main_options[
            '--batch-prediction-attributes'],
        '--prediction-attributes': main_options[
            '--prediction-attributes'],
        '--prediction-tag': delete_options['--prediction-tag'],
        '--batch-prediction-tag': delete_options['--batch-prediction-tag'],
        '--no-no-csv': main_options['--no-no-csv']})

    defaults = general_defaults["BigMLer PCA"]
    subcommand_options["pca"] = \
        get_pca_options( \
        defaults=defaults)
    # general options
    subcommand_options["pca"].update(common_options)
    subcommand_options["pca"].update(source_options)
    subcommand_options["pca"].update(dataset_options)
    subcommand_options["pca"].update(test_options)
    subcommand_options["pca"].update(dataset_sampling_options)
    subcommand_options["pca"].update({
        '--source-tag': delete_options['--source-tag'],
        '--dataset-tag': delete_options['--dataset-tag'],
        '--pca-tag': delete_options[
            '--pca-tag'],
        '--projection-tag': delete_options[
            '--projection-tag'],
        '--batch-projection-tag': delete_options[
            '--batch-projection-tag'],
        '--objective': main_options['--objective'],
        '--evaluate': main_options['--evaluate'],
        '--reports': main_options['--reports'],
        '--remote': main_options['--remote'],
        '--no-batch': main_options['--no-batch'],
        '--to-dataset': main_options['--to-dataset'],
        '--no-csv': main_options['--no-csv'],
        '--fields-map': main_options['--fields-map'],
        '--dataset-off': main_options['--dataset-off'],
        '--no-no-csv': main_options['--no-no-csv']})

    defaults = general_defaults["BigMLer Fusion"]
    subcommand_options["fusion"] = get_fusion_options(defaults=defaults)
    # general options
    subcommand_options["fusion"].update(common_options)
    subcommand_options["fusion"].update(test_options)
    subcommand_options["fusion"].update(source_options)
    subcommand_options["fusion"].update(dataset_options)
    del subcommand_options["fusion"]["--train"]
    del subcommand_options["fusion"]["--source"]
    del subcommand_options["fusion"]["--source-file"]
    del subcommand_options["fusion"]["--dataset"]
    del subcommand_options["fusion"]["--datasets"]
    del subcommand_options["fusion"]["--dataset-file"]
    subcommand_options["fusion"].update({
        '--prediction-info': main_options['--prediction-info'],
        '--prediction-header': main_options['--prediction-header'],
        '--prediction-fields': main_options['--prediction-fields'],
        '--operating-point': main_options['--operating-point'],
        '--reports': main_options['--reports'],
        '--project-id': source_options['--project-id'],
        '--project': source_options['--project'],
        '--remote': main_options['--remote'],
        '--batch-prediction-attributes': main_options[
            '--batch-prediction-attributes'],
        '--prediction-attributes': main_options[
            '--prediction-attributes'],
        '--prediction-tag': delete_options['--prediction-tag'],
        '--batch-prediction-tag': delete_options['--batch-prediction-tag'],
        '--no-batch': main_options['--no-batch'],
        '--evaluate': main_options['--evaluate'],
        '--to-dataset': main_options['--to-dataset'],
        '--no-csv': main_options['--no-csv'],
        '--fields-map': main_options['--fields-map'],
        '--dataset-off': main_options['--dataset-off'],
        '--no-no-csv': main_options['--no-no-csv'],
        '--locale': main_options['--locale'],
        '--training-separator': main_options['--training-separator'],
        '--fusion-tag': delete_options['--fusion-tag']})

    subparser = subparsers.add_parser(subcommand)

    parser_add_options(subparser, subcommand_options[subcommand])

    # options to be transmitted from analyze to main
    chained_options = [
        "--debug", "--username", "--api-key", "--resources-log",
        "--store", "--clear-logs", "--max-parallel-models",
        "--max-parallel-evaluations", "--objective", "--tag",
        "--no-tag", "--no-debug", "--model-fields", "--balance",
        "--verbosity", "--resume", "--stack_level", "--no-balance",
        "--args-separator", "--name"]

    return main_parser, chained_options, subcommand_options

redpajama_set_name: RedPajamaGithub


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text:
Taco Bell Fans Won't Want To Miss The New Chipotle Cheddar Chalupa
By Boshika Gupta/Dec. 21, 2021 3:14 pm EST
Taco Bell has news for its fans: according to Thrillist, the restaurant is planning to introduce its customers to a new version of its popular dish, the Chalupa. Taco Bell fans will be able to confirm that this is one item that the brand has experimented with on multiple occasions. Customers have been treated to such varieties as the Naked Chicken Chalupa, a vegetarian alternative called the Naked Chalupa, and even an extra-long version dubbed the Triplelupa.
Per Chew Boom, in September last year, Taco Bell launched the Toasted Cheddar Chalupa, a dish that included ingredients such as seasoned beef, reduced-fat sour cream, cheddar cheese, lettuce, and tomatoes "in a Chalupa shell with six-month aged cheddar [that was] toasted directly onto the shell." This menu item received good reviews from a number of Instagram users. One commenter going by the name of youcanjustcallmeeric offered a pretty vivid description: "The exterior reminds me of the slightly singed superficial layer atop some fancy Mac 'n Chees[e]. It's light, crunchy, and delicious." They even suggested that Taco Bell had "another hit on their hands." Now, the chain is introducing a new cheddary Chalupa to try.
The Chipotle Cheddar Chalupa might be even cheesier
As reported by Thrillist, Taco Bell is getting ready for one of its newest items called the Chipotle Cheddar Chalupa. As you may have guessed from the name, it has a creamy chipotle sauce. Customers will have the option of ordering their Chalupas with fillings such as seasoned beef, black beans, chicken, or steak. The beef and black bean varieties are priced at $3.59. The chicken version is available for $3.99 while the most expensive option is the steak Chalupa at $4.19. The Chipotle Cheddar Chalupa is expected to be cheesier than its predecessors.
The Chalupas will be launched at Taco Bell outlets around the U.S. on December 23 and are only available for a limited period of time. So if you plan on trying it out, it's best to grab one while supplies last. According to Today, Taco Bell is also planning to add some more items to its restaurants such as the Crispy Chicken Wings (for just a week), the Beefy Melt Burrito, the Fiesta Veggie Burrito, and more.


text:
Entertainment, History, Movies May 26, 2019 May 26, 2019
Nine from 1999: Memorable Films from the Turn of the Century
BY El Gosiengfiao-Santos
Jack Is Back! Gentleman Jack Renewed for Second Season
Nixie Clocks: The Future that Never Was
Ah, 1999. What a time that was to be an impressionable teen!
The year was hailed by many critics as one of the greatest in movies, and just skimming the titles that came out that year is proof enough. A lot of my favorite films actually came out in 1999—never mind that I was only 13, and I only got to watch some of them much later on VCDs (who remembers those?) and cable TV.
For many of my peers, a lot of the movies that came out in 1999 greatly influenced our adolescence, and we look fondly on many of them to this day. Here are nine 1999 films that, while not necessarily the most award-winning, helped shape our young adult minds while paving the way for new cinematic techniques and narratives.
Photo credit: Empire Online
You really can't write about 1999 films without mentioning The Matrix.
It turned 20 years old recently, and it was my gateway drug to the cyberpunk and action genres. It redefined how fight scenes and stunts were done in film.
Everyone is still familiar with the iconic "bullet time" slow-mo sequence that's been copied and spoofed over and over since then. Many films with notably badass action sequences take obvious inspiration from The Matrix, like Kill Bill, Wanted, Sucker Punch, and even Inception.
I would even argue that Love, Death & Robots was inspired by The Matrix, or at least by its epic animated spinoff, The Animatrix. The Matrix left us in awe, but at the same time curious and paranoid—is reality we know actually real?
Photo credit: NY Daily News
"The first rule of Fight Club is: You do not talk about Fight Club. The second rule of Fight Club is: You DO NOT talk about Fight Club."
Twenty years later, and people are still talking about Fight Club. It gives us more than just a glimpse into the minds of angry young men: it offers important lessons in freedom and how much of our potential is wasted when we stick to conforming to what society expects of us.
Photo credit: AV Club
Not necessarily thebestin terms of storytelling, but The Blair Witch Project was so different for its time. The "raw footage" shot with a handheld camera tricked many of us into believing that we were watching real found footage of events that could happen to us should we find ourselves lost in the woods. Horror movies that came out in succeeding years, like Cloverfield and Paranormal Activity, also played with this raw, first-person style to immerse their audiences in terrifying experiences.
Photo credit: Rotten Tomatoes
Of all the movies on this list, this one is my personal favorite—and also the most critically-panned. One look at its 36% freshness rating on Rotten Tomatoes can tell you that it really isn't one of the best from 1999 (and that I possibly have terrible taste in movies).
Admittedly, this tale of a robot becoming human is a bit dragging and could have benefitted from better scriptwriting, but it had just the right amount of heart, humor, and Robin Williams to win a place in my own teenage heart. Plus I do think that this movie, along with The Matrix, successfully got my fantasy-obsessed self to watch more futuristic/sci-fi films, especially the ones involving artificial intelligence and robots, like A.I. Artificial Intelligence, Chappie, and the original Ghost in the Shell (which I had not seen in full at the time; I only watched it after seeing both Bicentennial Man and The Matrix).
Photo credit: Netflix
Growing up watching Indiana Jones and playing a lot of Tomb Raider probably made my generation receptive to The Mummy, but even film critics had to admit that the film is just fun. It's not an award-winning action flick in terms of story, effects, or script, but there's something hilariously entertaining about Brendan Fraser running away from demonic beetles and screaming at the titular villain's face before blasting him with a shotgun.
The first film was successful enough to warrant two sequels (The Mummy Returns in 2001 and The Mummy: Tomb of the Dragon Emperor in 2008), a spin-off movie (The Scorpion King in 2002), and even an animated TV series in 2001.
The eponymous 2017 film was Universal's attempt at rebooting the original 1930s-1950s franchise, but it did so poorly that I'm left wondering if they should have taken cues from what made the 1999 film so enjoyable.
Star Wars Episode I: The Phantom Menace
Photo credit: Bustle
Who wasn't excited by a new Star Wars film coming out after 16 years? It may not be the best film in the franchise (some may even argue that it's the worst), but it was still successful in getting our generation into a franchise our parents loved, and it paved the way for the rest of the new Star Wars films, series, and video games. Without that revival of interest, maybe we wouldn't have gotten great movies like The Force Awakens or Rogue One.
Among the movies in this list, this is the only one I actually got to watch in the cinema. I still remember sitting in awe of Amidala in her impressive costumes and being on the edge of my seat during that fight scene between Darth Maul, Qui-Gon, and young Obi-Wan.
Photo credit: Sony Pictures Museum
I caught this on cable TV in the early 2000s, and only found out that it was a 1999 film later on. Where Fight Club gave us an idea of what went on in the minds of angry young men, Girl, Interrupted let us peer into the minds of young women with varying degrees of psychological and personal issues. This film showed us just how important it is for girls have a support group composed of girls who can relate to each other's problems and quirks.
The film received mixed reviews, but Angelina Jolie's performance as Lisa Rowe was her big Hollywood break, earning her the Academy Award and Golden Globe Award for Best Supporting Actress, as well as the Screen Actors Guild Award for Outstanding Supporting Female Actor.
Photo credit: The Hollywood Reporter
I only got to watch this movie this year, much to the distress of many of my girl friends who view it as one of the most important and most memorable films of their teenage years.
This adaptation of Shakespeare's The Taming of the Shrew features a strong, feminist leading lady while giving us a healthy dose of romance through lovely performances by Heath Ledger and Joseph Gordon-Levitt. Kat Stratford shows us how harshly society can judge outspoken women who refuse to fit the norms, and how important it is to keep being true to yourself, regardless.
Many of the leading ladies in rom-com films that came out in the years that followed are also independent, outspoken, and unafraid to be themselves: Cady Heron in Mean Girls, Violet Sanford in Coyote Ugly, Elle Woods in Legally Blonde, and Mia Thermopolis in The Princess Diaries.
I'm willing to bet that Kat Stratford was the one who set the pace.
The Iron Giant
Photo credit: Mental Floss
Ask any '90s kid what their favorite animated movie is, and they're likely to mention a Disney flick like Toy Story 2.
But, a lot of us also loved Warner Bros.' The Iron Giant. So, you can imagine our joy when the big guy made an appearance in Ready Player One, which came out in 2018. The Iron Giant may not be a Disney classic, but it was yet another film that showed us that being different shouldn't stop us from being human.
These movies were barely the tip of the iceberg: 1999 was a year when movie makers played around with new visual effects and unusual—sometimes even raw and messy—storytelling techniques. It was a year full of movies that made us think, with stories focused less on the obstacles the outside world throws our way and more on the challenges we face within our flawed selves. These movies taught us that it was okay to fail, to be angry, to be honest, to be different, and more importantly, to just be ourselves.


text:
#import <Foundation/Foundation.h>
#import "Base.h"

namespace Cedar { namespace Matchers {

    template<typename T>
    class Equal : public Base<> {
    private:
        Equal<T> & operator=(const Equal<T> &);

    public:
        explicit Equal(const T & expectedValue);
        ~Equal();
        // Allow default copy ctor.

        template<typename U>
        bool matches(const U &) const;

    protected:
        virtual NSString * failure_message_end() const;

    private:
        const T & expectedValue_;
    };

    template<typename T>
    Equal<T> equal(const T & expectedValue) {
        return Equal<T>(expectedValue);
    }

    template<typename T>
    Equal<T>::Equal(const T & expectedValue)
    : Base<>(), expectedValue_(expectedValue) {
    }

    template<typename T>
    Equal<T>::~Equal() {
    }

    template<typename T>
    /*virtual*/ NSString * Equal<T>::failure_message_end() const {
        return [NSString stringWithFormat:@"equal <%@>", Stringifiers::string_for(expectedValue_)];
    }

    template<typename T> template<typename U>
    bool Equal<T>::matches(const U & actualValue) const {
        return Comparators::compare_equal(actualValue, expectedValue_);
    }

#pragma mark equality operators
    template<typename T, typename U>
    bool operator==(const ActualValue<T> & actualValue, const U & expectedValue) {
        return actualValue.to == expectedValue;
    }

    template<typename T, typename U>
    bool operator==(const ActualValueMatchProxy<T> & actualValueMatchProxy, const U & expectedValue) {
        actualValueMatchProxy(equal(expectedValue));
        return true;
    }

    template<typename T, typename U>
    bool operator!=(const ActualValue<T> & actualValue, const U & expectedValue) {
        return actualValue.to != expectedValue;
    }

    template<typename T, typename U>
    bool operator!=(const ActualValueMatchProxy<T> & actualValueMatchProxy, const U & expectedValue) {
        actualValueMatchProxy.negate()(equal(expectedValue));
        return true;
    }
}}


Tonkon attorneys and University of Oregon alums Jessica Morgan and Chris Pallanch, along with their guests, participated in the 25th Annual ID Experts Gold Classic held June 13. The Golf Classic was put on by the Oregon Club of Portland (OCOP) and benefitted the University of Oregon athletics program. Jessica Morgan is a member of the OCOP board of directors.


If it was the case, it'd be my pleasure to help to fix its leaks and bring it back up, though, even as a newbie member of this forum.
...And this is only the beggining! You have to see the big picture, for as you probably know, our Precession Equinox Axis have just entered in the age of Aquarius, and one of the greatest characteristics of this age compared to the last Pisces one is the free flow of information summed to a global enlightenment and increase of human perception/awareness. And it is already happening right before our eyes every day.
So I'll repeat what I have said in my introduction post: we are the vanguard here. THIS FORUM is only the beggining to something greater, just like the very first living gold particle affects, motivates and compels all the rest to exponentially evolve towards its perfect qualities. Write what I am saying.
...And this is only the beggining! You have to see the big picture, for as you probably know, our Precession Equinox Axis have just entered in the age of Aquarius, and one of the greatest characteristics of this age compared to the last Pisces one is the [i]free flow of information[/i] summed to a [i]global enlightenment[/i] and [i]increase of human perception/awareness[/i]. And it is already happening right before our eyes every day.
A truly fine forum. Your efforts are greatly appreciated. I hope to have great things to share in the future with all of you.
I believe that this year will see a serious turn of events for our community. I do hope that it is for the better.
Because of your generosity, many have gathered here to learn of the mysteries and for some, the fruits of their labour will soon be harvested.
Extended the hosting service for yet another year (august 2019).
Cerenity wrote: Schmeldvich is one of the most well read members of this forum and contributes continuously without fault, its more than a bit of an understatement to say hes only read "a few" books. Perhaps you're reading into what he said a little too much and finding insult where there isn't any as personally I would have taken someone asking for an "alchemy study qualification" as a joke about how you never complete your studies in alchemy just as you never stop learning in life. A little bit of sarcasm can be misinterpreted as insulting if you aren't used to it.
I'd have to agree with this wholeheartedly! Schmeldvich's relentless work to bring some clarity to the art goes without saying. His posts are well structured as to be highly informative.
Schmeldvich is one of the most well read members of this forum and contributes continuously without fault, its more than a bit of an understatement to say hes only read "a few" books. Perhaps you're reading into what he said a little too much and finding insult where there isn't any as personally I would have taken someone asking for an "alchemy study qualification" as a joke about how you never complete your studies in alchemy just as you never stop learning in life. A little bit of sarcasm can be misinterpreted as insulting if you aren't used to it.
Thanks for stating your concerns. Life was to consuming for me at that time to continue moderating this forum like I used to do. Therefor I looked for someone who was willing to help keeping this forum alive. Schmeldvich's attitude and positive character was in line with what I did in the years before and he was willing to take the responsibility. There was and still is, no better person to continue this forum with such great contributions and continues efforts.
This art is full of secrecy and jealousy, let me kindly suggest that you bring this into a constructive discussion in the Great Work Theory session instead of making this a personal matter between you and him.
This forum intends to create a meeting place for practical lab alchemists. If people are willing to contribute, this place will turn into an alchemist cookbook. Members will have the opportunity to learn tested recipes/processes, and benefit from the guidance and experience of other members.
We have no intention to claim any authority on the alchemical art. Best we can do is to share our thoughts and experiments and hope we learn something from each others mistakes. In this regards, Schmelvich was not selected because of this knowledge or experience, but because of his good character.


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text:
How Creative Europe works
Audiovisual Training, Markets & Festivals
European Networks
Francofonia
Curzon Film World
Distribution: Selective
https://www.facebook.com/CurzonFilmWorld/
https://twitter.com/curzonfilmworld?lang=en-gb
Total project grant (euros)
Sub-programme
Call publication date
Result publication date
UK release date
Francofonia is a co-produced drama directed by Russian filmmaker Alexander Sokurov (Russian Ark). The film tells the story of museum director Jacques Jaujard (Louis-Do de Lencquesaing) and German officer Count Franz Wolff-Metternich (Benjamin Utzerath) who work together to protect Louvre artworks from the Nazis.
It was screened in the main competition section of the 72nd Venice International Film Festival and in the Masters section of the 2015 Toronto International Film Festival.
Louisa Dent, Managing Director of Curzon Artificial Eye, said:
"Creative Europe support makes a significant contribution to Curzon's ability to champion European film. It not only helps us take acquisition risks and mount ambitious releases of non-national European films, but also encourages collaboration with European partners such as sales agents and filmmakers."
Curzon has also received funding from Creative Europe to support the release of European films in the UK through the Automatic Distribution scheme.
Sunset (Napszallta)
This website replaces culturefund.eu & mediadeskuk.eu
Creative Europe Desk UK is led by
In partnership with Arts Council England, Creative Scotland, Welsh Government
With support from the UK Department for Culture, Media and Sport and the European Commission
Terms of Use, Privacy and Cookies


text:
1953: Panic!
This year saw an extraordinary outburst of anti-gay panic in the British press which was to contribute, surprisingly enough, to a process by which the lives of British homosexuals (and those of many other countries) would actually be improved.
As Patrick Higgins, in his meticulously researched (if somewhat extravagantly titled) history of British law reform, Heterosexual Dictatorship, has pointed out; 'In a six-month period beginning in October 1953 more space was devoted to homosexuality in the British press than in any period since the trials and conviction of Oscar Wilde during 1895'. During that time three high-profile cases involving apparently respectable men, soldiers from the elite Guards regiments, cash and gifts, all-male orgies, bamboo canes, drummer-boys, dirty pictures, titillated the public on an almost daily basis. Other cases exposed actors, film directors, members of parliament and even junior ministers, churchwardens, accounts clerks and schoolmasters engaging in unspeakable behaviour in public lavatories, public parks, army barracks, holiday hotels and lodgings.
The effect upon the public was to create an unsettling sense that the highest places, no less than the respectable middle orders, in society had been captured by the forces of debauchery and depravity, represented above all by male homosexuals. The press, the police force and the politicians agreed – Something Had To Be Done.
The government inquiry that resulted – chaired by John Wolfenden – moved slowly, but in the end its conclusions were clear: homosexuality between consenting adults in private should be decriminalised. Not, perhaps, what the panic had been intended to produce.
Brought to you by the Australian Lesbian and Gay Archives


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text:
Bon Jovi Superfan
November 23, 2010 12:00 am by Jessica Lawrenson Views: 11
She is standing in the crowd, 13 rows back, with a florescent orange thong on her head with the flower on the front directly in the center of her forehead above her rock star shades. She sings her heart out to the group of men on stage singing back to the 50,000- person crowd she's among. Merle Bronson is in her glory at a Bon Jovi concert.
Looking at the 58-year-old Bronson on the street or walking across campus, you might not expect this other side of her.
Go to her office, though, and the clues are everywhere.
There's a bulletin board with 17 photos of concerts she attended. There are six photos of album logos, the Jon Bon Jovi background on her desktop computer and her jean jacket with Bon Jovi patches.
There's even a Bon Jovi Smurf playing a keyboard that her co-worker gave her near her board and a Bon Jovi CD playing.
"I'm and idiot fan," she said with a big smile.
Bronson heard Bon Jovi for the first time on MTV in 1986. She was living on a Navy base in California with her now second ex-husband, rocking her newborn son. She was immediately smitten with Bon Jovi and his music, saying she thought to herself, 'boy he can wear the hell out of a pair of jeans.' She never saw him live until 2003 because as a single mother she said she had other financial obligations.
She has been married twice, but Bronson said the first one wasn't long enough to count. It was a year and two months exactly from marriage to divorce. Bronson has lived as far away from Castleton as California and as close as Poultney. She has one son, Dennis Bronson.
"[Dennis] thinks I'm nuts," said Bronson.
That's an accurate depiction, he said.
"Sometimes she gets carried away with what she likes," explained Dennis Bronson, "but what ever makes her happy I guess."
It's obvious Bon Jovi makes her happy, proven by the huge smile while watches videos online of the band or reminiscing with her scrapbook. Every page of the scrapbook is crammed with photos, confetti, decorations, her seven or eight fan club cards and even the thong from her first concert that was given to her as part of a concert survival kit that her colleagues in the registrar's office gave her. In addition to the thong, it contained sunglasses, earplugs and three types of liquor among other items, she said.
Going on her eighth concert now, she still has not opened anything from the kit – aside from pulling the thong out, of course.
"Merle is just a very happy person at a concert and so focused," said Judy Holcomb, a fellow Jovi go-er.
"It is a hellacious good time," said Bronson.
But Bronson also has fun outside of the concerts, saying getting there is half the fun. Getting there has also provided some memorable moments, though. It was going to her first concert in 2003 that she had the "limo ride from hell" to The Pepsi Arena in Albany, N.Y.
The limo was late and was covered in dirty tissues and cigarette butts on the inside – and there was no heat. The driver got lost causing her to have to hustle down the streets of Albany to make the show. Another night she managed to get a ride home from a state trooper because she could not find her cab. She convinced the officer to give her a ride by explaining her blisters on her feet and her C-O-P-D lung condition.
Her longest trip to see her beloved band took her to Rutherford, N.J. It only took her four and a half hours to get there because of her lead foot, which explains the "I drive like a Cullen" bumper sticker next to the Bon Jovi one on her grey Toyota Yaris.
Bronson has worked at Castleton in the registrar's office for 26 years now. Everyone knows of her love for this band. President Dave Wolk even jokes with her about it. Members of the Castleton community may joke about her Bon Jovi obsession, but they still respect her and her dedicated work at Castleton.
"Merle is a hard worker, very frugal, does a good job and is modest," said Melissa Paradee who has sought information on a Bon Jovi concert from Bronson before she went.
Bronson will be going to another concert in March, and has already requested for the time off to go, said Paradee.
"This stuff keeps me young. I'm like a kid at a concert," said Bronson, swaying her head back and forth to her "boredom breaker mix" of all Bon Jovi songs.


(April 1, 2014) Innovative Food Processors, Inc. (IFP) is pleased to provide sponsorship for the 10th annual Industrial Workshop on Microencapsulation to be held in Minneapolis, on September 30 and October 1, 2014. The two day interactive workshop will include lectures on state-of-the-art microencapsulated ingredient techniques and practices, product demonstrations, and two plant tours including IFP's Faribault, MN fluid-bed powder processing and retail packaging plant.
The workshop offers attendees an opportunity to interact and network with applications and processing experts to gain better understanding of specific challenges and state-ofthe- art solutions, build relationships, and move the industry forward.
• Tom Tongue, IFP - Hot-Melt Fluid-Bed, Understanding the Hurdles.
• Bob Sobel, FONA – Matrix Encapsulation of Flavors and Alginate Beadlet Technology.
• Markus Wysshaar – Erbo Spraytec – ProCell Encapsulation of Food Ingredients.
• John Foley, BASF - Encapsulation of Omega-3s and Vitamins.
• Willie Hendrickson, Aveka - Three Big Issues: Water, Oxygen and Heat.
• James Oxley, Southwest Research - Coacervation and Chemical Processes.
People interested in attending can contact Walt Zackowitz at IFP (waltz@ifpinc.biz) or Nedra Sneed (nedra.sneed@membraneworld.com).
IFP, Inc. manufactures powder products that provide benefits beyondbasic nutrition. They specialize in functional beverages, sports/ nutrition supplements and medical foods containing high value ingredient s such as fibers and prebiotics, probiotics, proteins, antioxidants, natural sweeteners, vitamins and minerals and amino acids. NSF registered GMP and SQF Level III certified.
For more information on IFP, Inc. visit http://www.ifpinc.biz or e-mail: Info@ifpinc.biz.
Free from Partially Hydrogenated Oils.


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Pins! It's how we know what you're all about. This pin comes courtesy of our friends from The Beguiling in Toronto (the best little comic book shop in Canada), and is inspired by the "18 and over only" signs that announce the Ikebukuro and Shinjuku peep shows, night clubs and other fun joints of Tokyo meant only for adult eyes. *eyebrow dance* Let the world know you are an adult, in style.


Tell us about your childhood experience, music career, your musical background, experience and skills.
Later on I was one of 3 or 4 boys who sang 3rd soprano in front of the high school choir while I was in grade school. We were the finale when we hit our high notes. We had no idea what we were doing, but people seemed to like it. That was my 1st public performances as I recall. Funny how life events do seem to move in circles.