text:
DOWN a dingy alleyway lined with beer gardens and hookah bars, an Afro-jazz funk band took the small stage at the Piano Cafe, a smoke-filled lounge in the center of Kosice.
It was not exactly what a first-time visitor expected to find in a Central European town of steel factories and Soviet-era apartment blocs. But as the beat of African samba filled the cramped cafe, an arty crowd of young Slovaks in metal-rock T-shirts and bookish glasses sat in rapt attention, slow-sipping their Mojitos and ignoring the techno music downstairs.
For decades, Kosice, a city of 250,000 in eastern Slovakia, was considered an industrial backwater if it was considered at all. (Bratislava, Slovakia's capital, got the attention.) But in the past several years, a beautifully refurbished center has emerged from behind Kosice's ugly veneer of gray concrete and steel, drawing artists, entrepreneurs and a growing number of tourists.
Hlavni Namesti, the city's newly renovated Main Square, now gleams with intimate art galleries, white-tablecloth restaurants and upscale hotels equipped with wine cellars. Dormant mines and military barracks have been refashioned into studios for underground artists. And a hilltop collection of unused warehouses is being converted into a site for open-air festivals, electronica parties and laser shows.
"It's really booming," said Michael Hladky, 27, a local architect who specializes in new urbanism. "It's no longer the case where public art gets decided by old guys from Communist times. A younger generation is coming in."
The transformation was no accident. With its steel factories slowing down, Kosice, a former Soviet Bloc city, decided in the late 1990s to restore the town's cobblestone center. The idea was to stimulate culture and the arts.
"We want to be an incubator for young artists," said Marek Kolarcik, project manager of Kosice 2013, a public task force lobbying to have the city named a European Capital of Culture. "We're lagging behind Bratislava, but in two years' time, the boom will come."
Its historic diversity may help. Thanks to its location along the border of the Hapsburg Empire, Kosice has Slavic as well as Magyar roots. The region's only Roma theater can be found there, and bookstores carry both Slovak and Hungarian magazines. Locals also like to point out that in 1968, when Moscow sent tanks into the country to suppress the reform movement known as the Prague Spring, some of the Czechoslovak intelligentsia were hauled off to work in Kosice's steel mills, laying the foundation for the city's renaissance in culture.
On an intermittently soggy afternoon last fall, the beer gardens along the main square were emptied of their regulars a mix of university students and steel workers but the sidewalks swelled with the rush of passersby. A pair of elderly women fed pigeons in the park as faint elevator music could be heard from a nearby singing fountain.
A fog lifted over the towering spires of St. Elizabeth's Cathedral. Begun in the late 14th century, it is Slovakia's largest church, and its gargoyle-studded exterior leaves one wondering if Quasimodo is hunched over its Gothic entranceway. The top of the cathedral's clock tower offers panoramic views, and the crypt below lets you mingle among the tombs.
Next to the church stands the medieval bell tower of St. Urban. Its vaulted interior has been turned into a tacky wax museum devoted to hometown heroes like Andrej Varchola otherwise known as Andy Warhol who has familial roots in the region. His wax likeness, complete with the signature shock of white hair, stands next to a general and other heroes from Slovak history.
Indeed, Kosice seems to have embraced its quirkier side. Filmmakers and media types descend on the town each June to hand out a documentary film award called the Golden Beggar, which depicts a vagrant tipping his hat.
Nor are locals above showing off their pro-Americanism. Slovak-style spaghetti is served at the Bill Restaurant, named after who else? Bill Clinton, but a waitress said he never stepped foot in the place. The entrance features a cartoon cutout of the former president sporting a wide grin, and the cavernous interior features kitschy American memorabilia splashed across its orange walls, including, of course, a saxophone.
But Kosice's hammer-and-sickle past is never far away. Lurking around the corner is Krcma Nositel Radu Prace, a dive bar straight out of the cold war. A group of blue-collar men cluster around tables, singing what sounds like Soviet songs and washing down cheap Topvar beer, while portraits of Lenin and Marx peer from the peeling walls and an angry-looking babushka tends bar. "This is a place for the unemployed, not tourists," said Milan Seliga, a truck driver, before downing a shot of vodka.
Attempts to shed Kosice's provincial image have not come easily. Part of the problem may be Slovakia's reputation not entirely unfounded for poor service and lack of foreign language skills, a holdover from its Communist days. "They go to hotel school for four years but learn to smile on the fifth," said Richard Gibbs, a retired teacher from England, who was visiting the High Tatras, the mountains dividing Slovakia and Poland.
But walk past the Piano Cafe down an unmarked alleyway known as club row, and you might encounter a gregarious man with a mullet haircut tending bar at Diesel, a kitschy bar, and teenagers in hoodies eager to chat up out-of-towners between puffs of Marlboros.
That bonhomie is perhaps most clearly felt by the city's artists. "This place is what I imagine New York was like back in the 30s," said James Austin Murray, 38, a painter from New York City who visits Kosice occasionally. "There is this sincerity that comes with the lack of ambition toward money."
Flights from the United States require a stopover, in Vienna or Prague. A recent online search found a Czech Airlines flight from Kennedy Airport, with a plane change in Prague, starting at $1,176 for travel this month. Kosice is about five hours by bus or train from Bratislava or Budapest.
The 32-unit Hotel Bristol (Orlia 3; 421-55-729-0077; www.hotelbristol.sk) offers cathedral views and a Roman spa, with singles starting at 3,300 Slovak korunas, $171 at 19.65 korunas to the dollar.
The Hotel Bankov (Dolny Bankov; 421-55-632-45-22; www.hotelbankov.sk) has some of the most lavish quarters in town, with park views on its summer terrace and a Finnish sauna. Rooms start at 2,950 korunas.
For traditional Slovak fare, head to Twelve Apostles (Kovacska 51; 421-55-729-5105), where diners sit around wooden pews in a tabernacle-like room.The menu includes chicken breast with cherry (385 korunas) and steamed salmon with grilled vegetables (450 korunas).
Bill Restaurant (Hlavna 117; 421-9-07-970-863) serves American-inspired fare.
Another popular hangout is Diesel Pub (Hlavna 92; 421-55-622-2186), which offers greasy but good food.


text:
On Thursday, August 8, 2019, surrounded by family, Predenice Ann Willis passed away at Mercy Medical Center. Ann was born in Belzoni, MS. She is pre-deceased by her mother and father, DeElla and George Willis, a son, David Eddington, and aunts and uncles, Willie Huddleston of Indianola, MS, Sarah Knight of Gulfport, MS, Ora D. Magee-Lee of Goldsboro, NC, and Curtis Huddleston and Ora Lee Gibbs, both of Springfield, MA. Ann is survived by her life partner, Benjamin Eddington Sr.; five beloved children, Benjamin Willis, Jamar Eddington (Michelle), and Nihgee Eddington, all of Springfield, and Tiekea Eddington-Fowlkes (Brandon Sr.) and Taiesha Eddington of Harker Heights, TX; six grandchildren, Benjamin Jr., Jamar Jr., Tylianna, Tyree, Tyliah, and Brandon Jr.; two siblings, Geraldine Willis and Annie Bell Willis, both of Springfield; two nephews, Todd and Kevin; thirteen aunts and uncles, Abby Hall of Clarksdale, MS, Geneva Barnes of Gulfport, MS, John Huddleston, Jean (and Albert) Carter, Ora Lizana (and Everett Montgomery), and Rosemary Huddleston, all of Springfield. Ann will be most remembered for her kindness and generosity. The calling hour is 9-9:45 am Saturday at her church home, Alden Baptist Church, followed by funeral services at 9:45 with burial at Oak Grove Cemetery.
To send flowers to the family or plant a tree in memory of Predenice A Willis, please visit our floral store.

subset: commoncrawl


text:
Safe Your Household With The Finest Important Sickness Insurance coverage
Important sickness insurance coverage cowl is a sort of insurance coverage cowl the place the insurer is meant to make a lump sum money fee in case the coverage holder is recognized with a illness or dysfunction that's included within the coverage cowl. The ailments are basically life threatening and are of maximum severe concern. These ailments normally are: Most cancers First Coronary heart Assault Open Chest Coronary Artery Bypass Surgical procedure Open Coronary heart Valve Alternative or Restore Coma Kidney Failure Stroke Main Organ Transplant Paralysis Motor Neuron Illness A number of Sclerosis Aplastic Anemia Bacterial Meningitis Lack of Speech Finish Stage Liver Illness Deafness Finish-stage Lung Illness Fulminant Viral Hepatitis Main Burns Muscular Dystrophy These ailments are included in the most effective vital sickness insurances. Nonetheless, totally different vital sickness insurance coverage firms could present totally different insurance policies. This coverage will be taken in two alternative ways. The construction could also be outlined for the affected person to obtain an everyday earnings in the end of his lifetime, or when he/she is being surgically operated on.
For the insurance coverage declare to be legitimate, the affected person should survive for a minimal variety of days from the day of prognosis. The prognosis must be made by a health care provider who's a specialist in that individual space of problems. The tenure of this insurance coverage cowl could also be taken for a 2-year interval to avail a variety of reductions. This cowl, nevertheless, provides renewability for a lifetime and getting it renewed for lifetime won't solely be cheaper for the sufferers but in addition will show to be a clever determination in the long term, because the onset of a illness is all the time unsure. Uncertainty is precisely what the insurance coverage coverage battles in opposition to. There are a lot of advantages provided by vital care insurance coverage firms. For starters, a free look interval of 15 days is obtainable. One takes a plan after which if one doesn't really feel it's a excellent concept, he can get the plan cancelled. The free look zone goes on for about 15 days, which will be cancelled if the policyholder is unhappy and his/her cash might be reimbursed. Secondly, when a illness that's lined within the vital coverage cowl needs to be dissolved and paid out, the immediate customer support division of the insurer will make certain to course of the paperwork swiftly and pay the lump sum to the affected person. This cowl doesn't require any tedious paperwork. The vital insurance coverage cowl can embody a person or a household with a rise of 5% sum assured every time the coverage is renewed. With this cowl, you can even save taxes below the Part 80D.


text:
God Seed (ゴッドシード Goddo Shiido) is a race of tree creatures that is a part of the Wood Dragon God Aldoron.[1]
God Seeds are a race of tree creatures that grows from Aldoron's body whose purpose is to heal the Dragon God's wounds once he awakens.[2] They also have the ability to read their target's mind by putting their hand on their target's head in order to distinguish which person their target thinks is the most powerful and uses it to their advantage against them. After reading their target's mind, the God Seed can copy the appearance and Magic of that person in their target's mind and uses it to eliminate them.[3]
Known God Seed
- ↑ Fairy Tail: 100 Years Quest Manga: Chapter 52, Page 9
- ↑ Fairy Tail: 100 Years Quest: Chapter 50, Pages 5-7
- ↑ Fairy Tail: 100 Years Quest Manga: Chapter 52, Pages 13-17
|Earth Land
|Artificial Lizardman • Bakshi • Celestial Spirit • Clipper • Curily • Demon • Doscadon • Dragon • Etherious • Fish • Giant • Goblin • God • God Seed • Grand Magic Games Monsters • Hane-Sakana • Hodras • Cubina Gamal • Lizardman • Machias • Mole • Rollidillo • Spirit-Luminescent Bug • Tenrou Squirrel • Vulcan • Weretiger • Wyvern
|Exceed • Legion


text:
Defying the speculations, Britain has hit the UN target of spending 0.7% of national income on aid for the third year in succession….reports Asian Lite News
According to figures from the Department for International Development (DFID), Britain has fulfilled its commitment to spend 0.7 per cent of national income on aid. Indian-origin British politician Priti Patel MP is heading the department. The figures shows Pakistan got £374 million British aid ahead of Ethiopia's £339 million. India, a rising economy power in the world, gets £186 million.
Other recipients are: Afghanistan (£300 million), Nigeria (£263 million), Syria (£258 million). All of the top 20 recipients were in Africa – which took almost £2.8 billion (55%) of the total – or Asia – which received around £2.1 billion (41%). Just 3% of spending went to the Americas, 1% to Europe and 0.2% to the Pacific region.
The statistics released by the DFID showed that the £12.1 billion of overseas development aid in 2015 represented exactly 0.7% of the UK's gross national income. However, spending on aid fell below the target when measured by new international accounting standards adopted in 2014, which put the level at 0.66%.
The British Government has pledged to meet the new standards – which came into effect after spending plans for last year were set – in its aid spending for this year. Total aid spend in 2015 was up by £437 million (3.7%) compared with 2014.
British aid to developing countries, especially former colonies and troubled economies, was a main issue during the Brexit campaign. Even Priti Patel was in supportive of abolishing the system.
The government even hinted it would stop sending aid to countries like India and China because their rapid economic growth had made it unnecessary, but it said some "technical assistance" would continue.


text:
NY12001 - Nursery Industry Environmental and Technical Research and Extension 2012/2013
Nursery Industry Environmental and Technical Research and Extension 2012/2013 provided the Australian nursery industry with the capacity to address several environmental and technical research and development issues that were aligned to the Nursery Industry Strategic Investment Plan 2012–2016. Each issue was developed through consultation with whole of industry which involved all State/Territory Associations, an industry needs assessment process and industry technical committees.
The national Environment Committee funded through this project met twice on 8 November 2012 and 6‐7 June 2013 and provided technical input and strategic direction into this project as well as input on future research, development and extension opportunities for the Australian nursery industry.


text:
... with an official guide
As we walked our guide Leigh reminded us to alway look up and pointing out the busts of philosophers on the piers surrounding the Sheldonian Theatre.
In 2007 school children were encouraged to submit ideas for new 'grotesque' sculptures to replace some of the crumbling ones on the Bodleian Library which were unveiled in 2009 ... including
... Three Men in a Boat, Tweedledee and Tweedledum among others
The Divinity School (Great Hall on the ground floor and Duke Humphrey's Library above) is attached to the Bodleian Library building. Built in between 1427-1483 it is the oldest purpose-built university building in Oxford specifically for lectures and oral exams in theology.
The external door was added in 1669 by Sir Christopher Wren for access to the Sheldonian Theatre. The boss above the door bears his initials.
Academic degrees date from the second half of the 12th century. Oxford academic students who have passed their final exams receive their degrees at The Sheldonian Theatre where the whole proceeding are conducted in latin including the speech given by the Public Orator.
Inside the Divinity School ... Sir Christopher Wren's door and a wonderful ceiling
The information board explains the use of the two pulpits (1813) you can see in my photo above (left behind the chest and to the left of Wren's door on the right). In the past, Pupils would have taken their oral exams here. The pupil would stand in the box on the right to deliver his thesis and the teacher would sit on the right listening. Other pupils may be in the hall at the same time. This type of exam (Viva (viva voce) is still used today especially at the end of a DPhil course.
And Harry Potter at the Divinity School ...
The Philosopher's Stone ... This famous hall with its classic gothic vaulted ceiling was used as Hogwarts Infirmary. Harry ends up here at the end of the film after his confrontation with Voldermort.
The Duke Humphrey's Library is the oldest reading room in Oxford and the information boards show Humphrey, Duke of Gloucester (1390-1447) who was the younger brother of King Henry V and who was responsible for the finance and collection of rare, important manuscripts which eventually formed the basis of this great library in 1488. (click on any of the photos to enlarge).
Unfortunately a visit to the library was not part of our guided tour today.
And Harry Potter in the Duke Humphrey's Library ...
The Philosopher's Stone ... Harry in his invisibility cloak looks for clues in Hogwarts library to be terrified by the monster in the book and then in real life by caretaker Argus Filch.
Readers will undoubtably know that the Inspector Morse series were film mainly in Oxford and include scenes taken within the Duke Humphrey's Library at Bodleian.
Sir Thomas Bodley's Chest has an elaborate mechanism of bolts operated by a key in the centre of the lid.
This was his personal strong-box and contained the deeds of his properties and endowments and was mentioned in his will.
The University decreed in 1613 that the chest be kept at Corpus Christi College but it was brought to the Library in 1622 and used as a safe until as late as 1774. It is currently used to take donations from visitors and the funds used to purchase rare books and manuscripts in addition to ordinary funding.
Only two other Oxford colleges were used in the Harry Potter films ...
New College in the Cloisters
Christ Church at the top of the stairway ...
Goblets of Fire ... Harry has fallen out with everyone and comes face to face with Malfoy sitting in the tree. Malfoy is then turned into a ferret in front of our eyes to the annoyance of Professor McGonagall.
In the Philosopher's Stone Harry, Ron, Hermione and the other 'first years' walk up the grand stairway to Hogwarts to be met by Professor McGonagall under the magnificent gothic vaulted roof. It is here also that the three are reunited at the end of the film
Christ Church at the bottom of the stairway ...
In the Chamber of Secrets ... Harry and Ron fly into Hogwarts in their Ford Anglia, climb these stairs and come face to face with Argus Filch. It is also the location used for the first meeting between Harry and Tom Riddle.
Christ Church's Cloisters.
In The Philosopher's Stone ... Hermione shows Harry the trophy his father won as a seeker in Quidditch. The scene was shot just outside the current bookshop.
Christ Church's Great Hall ...
One of the most famous rooms in Oxford became the inspiration for Hogwarts Dining Hall for all of the Harry Potter films. A studio set was created from photographs of the Tudor Great Hall and used in several film shoots with a few differences.
Although it's taken a long time to write this posting (lack of internet and too busy walking our surroundings) I have thoroughly enjoyed doing it. Hope you've enjoyed reading it too.


text:
We are looking for outstanding team members to support our growth.
Among our priority hirings, we are looking for:
– Pre-sales engineers
– Sales executives
– Marketing executives
– Customer success specialists
– Back-end software engineers
Job perks include:
– Attractive salaries and benefits packages
– Opportunities to work with large international accounts
– Multiple locations and home office is possible
Interested in joining our team?
Tell us more about yourself and upload your resume.


text:
According to figures published by Promocija Plus there were 3,209 new light vehicles registered in Croatia during April, 2013
There were 2,813 passenger cars registered.
Leading brands
Volkswagen: 553 units
Opel: 337 units
Citroën: 199 units
Kia: 186 units
Peugeot: 177 units
Škoda: 144 units
Audi: 138 units
Hyundai: 137 units
There were 396 LCVs registered
Leading brands:
Volkswagen: 88 units
Renault: 68 units
Peugeot: 50 units
Mercedes-Benz: 48 units
Citroën: 43 units
If you are interested in Central and East European automotive markets, we've got all the data you need! Please let us know your needs.


text:
Baia Blu Apartment Lerici, Liguria - Italy
Property Detail
Property Description
Baia Blu is a stylish and newly designed apartment, carefully thought and realised with a great taste of beauty and architectural details.
The peculiarity of this house is the attention given at every single detail, expressing the sense of beauty, elegance and care in the choice of each element… the amazing seaview makes the ambience even more sophisticated.
The house is on the top of the hill dominating the Baia Blu, a cosy bay where guests would find pristine water and a well equipped beach. From the terrace guests could admire the entire Gulf of La Spezia and its islands, like a special nest for breakfast and lazy aperitivi enyoing spectacular sunrise and romantic sunset.
The Baia Blu is a penthouse flat surrounded by olive trees and flowers.
Entering the apartment, guests will be welcomed by a large and bright living room, where a confortable design sofa will allow guests to relax admiring the seaview, or watching Tv.
A great round marble table with a perfect lamp over ,is the heart of the property. "Foodies" will have the chance to challange themselves with the italian receips, thanks to a contemporany, hand-made wooden kitchen, fully equipped with professional elements like Alpes Inox Grill, perfect for cooking steaks, prawns, veggies…. The real wine cellar (where temerature is set on 18° celsius degrees), is there to help guests to enjoy good wines at its best !!
The house is made of two levels: besides the living area, a hidden door opens the bedrooms area,where guests would find a double bedroom, a modern bathroom with a large blue shower, and the master bedroom with a stilish ensuite bathroom with tub.
From the master bedroom, a private wooden stairs armoniously integrated in the furniture ,allows guests to reach a bright studio on the upper level.
The first floor can also be reached by a spiral staircase from the living room. On the second floor a bright twin room completes the floor. This special room has a secret hit… Lying from one of the two beds guests can admire the sea from a small window just by the bed!
The rooms on the first floor overlook the living room through wide windows, catching the sunlight coming from the windows below, enjoyng the seaview… Moreover they take light from the ceiling windows too… creating an armonious and bright ambience.
This property is perfect for families or for groups of people who do not compromise the comforts of a beautiful design house, set in an impressive surround, made of nature and sea.
Info Location
|Car recommended
|Distance to Shopping
|San Terenzo 1,5 km
|Nearest Airport
|Pisa 90 km
|Nearest Train Station
|La Spezia
|La Spezia
|Nearest City
|La Spezia
|Nearest Beach
|Baia Blu
|Nearest Golf
|Lerici 4km


text:
Advanced Search |
Search Tips
Baby beets, sugar, spice.
Enjoy a taste of farm-fresh goodness straight from the mountains of northern New Hampshire.
Our products feature the best all-natural ingredients, made in small batches with no additives or preservatives.
We promise to never spam you, and just use your email address to identify you as a valid customer.
This product hasn't received any reviews yet. Be the first to review this product!
Click the button below to add the White Mountain Canning Company Sweet Baby Beets 16oz to your wish list.
All prices are in USD
Copyright 2020 Zeb's General Store.
Sitemap |


text:
This paper describes some experiments in "book learning" in the computer chess program Crafty, developed by the author. Crafty plays on the various Internet chess servers, and as a result, typically plays over 20,000 games per year. A favorite tactic of human chess players is to find a weak book line that a program will follow repeatedly, and then play that opening over and over, until they find a way to win the game. They then repeat this game many times. In years past, the author would simply edit the book by hand when such "cooks" were found, to prevent the program from playing them repeatedly. This paper describes an approach that automates this "book tuning" by letting Crafty determine which openings are good and which are bad, and adjusting its book selections accordingly.
Computer chess programs have used an "opening book" from the early days of computer chess programs such as Mac Hack through the 1970's and 1980's (Chess 4.x, Cray Blitz, Belle, HiTech) and into the 1990's. The opening book is an important part of a computer chess program, because it addresses several issues that are difficult to handle with other approaches.
This "opening book" is made by taking thousands (or hundreds of thousands) of GM games and creating a database of opening moves. Then, when your opponent plays a move you have in your database, you have a move to play in response, instantly. These moves are generally considered to be "good" because they were played by grandmaster players, and if they are played often enough, with good results, they are considered to be "opening theory" and are played whenever possible.
Without going into detail, the purpose of an opening book is to provide variability in games so that the program avoids playing a losing line repeatedly and also so that it avoids playing the same line repeatedly even if it wins. To accomplish this, it is common to build an opening book from a large collection of PGN games, but doing so runs the risk of a program following a bad line and losing, and then continuing to repeat this losing line.
It would seem, then, that using a large collection of games is required to avoid repeating the same opening too often, but that using a large collection of games can be bad because the games may well include serious blunders. This turns into a time-intensive task that takes time away from the engine development.
The problem resolves into maintaining a very large database of opening moves that have been played by strong players in tournament games. But since the database is so large, it is desirable that a chess-playing program take this database, try the various moves in real games, and then "learn" which are good and which are bad.
The first issue to be addressed is choosing a method that decides whether a book line is bad or good. There are two obvious approaches.
Approach number one is called "result-driven" and simply looks at how the game ends. If the program loses, that opening line is called a "loser" and action can be taken to avoid playing it again (how this is done is described later.) I chose to go beyond this approach because it is quite common for a book line to only extend 10-15 moves into the game, while most games last well beyond 50 moves. The question that must be answered is "was this game lost because of a bad opening, or was it lost because of poor play by the program?"
If the result-driven approach is taken, program weaknesses will cause incorrect opening selection. For example, imagine playing a super-GM such as Kasparov, who would be expected to win most games against most any program under tournament time controls. Such a method for deciding whether an opening is playable or not would eventually convince the program that no book moves are playable, based on the outcome against Kasparov. While this might be quite important in a computer vs computer test scenario that plays many games, it can lead to problems.
Result-driven learning has one important short-term impact on the way Crafty uses the book. If someone tries an opening variation that has not been tried before, and if the program loses this game, it backtracks through the opening variation to find the last point where there were alternative moves. The move actually played is given a large negative learned value so that it will not be played again.
The advantage to this is that there are openings which are going to produce lots of trouble because the program simply does not understand what is required to be successful (yet). Using this algorithm, even if the score looked good after playing 10 moves beyond the end of the book variation, Crafty will still vary and not play that game again. This doesn't happen often enough to be bothersome, but it does prevent some cases where the normal learning algorithm decides that the book variation is playable, but the game is lost anyway. And it might be lost again and again if it continues to play that book move.
Approach number two can be called "search-driven" and uses the early search results, obtained after following a book line, to determine whether the book line resulted in a game with reasonable chances or not. Crafty might still lose the game, but if it is "satisfied" with the position after leaving the opening book, then the loss might not be the fault of the book, rather it might be the fault of playing bad moves later in the game.
When I started on this project, I originally planned to use the first real search after leaving the book, and taking that value to determine whether the resulting position was suitable to play again or if it should be avoided. Unfortunately, I discovered that this did not produce accurate results, for several reasons.
The first problem I encountered occurred on gambit openings where Crafty was offered a gambit pawn and accepted it. The opponent then might play some move not in the book at all, and Crafty would drop out and do the first search, and it could generally find that it could hold on to the pawn and remain material ahead. The learned result might show it 1/2 pawn ahead for example, this produced by being a pawn ahead, but with the opponent having a lead in development. If I used this value, Crafty would assume this gambit should be accepted whenever offered, even though a few moves later it had found that accepting this gambit led to a bad or lost position.
The second problem is the inverse of this. Crafty would offer a gambit, the opponent would accept it (which was known to be bad and might not even be in the book file) and the first non-book search would show a negative evaluation (again, assume -1/2 pawn, Crafty being down a pawn, but up a big lead in development). It would incorrectly assume that this was a lost position and not play it again.
It became apparent that the first search result was not enough. I chose to spread this over several searches to try to "get a feel" for what is going on in the position. The current algorithm remembers each of the results from the first ten searches, and then looks at these values to determine what is happening. There are several possible things that can happen, as described below.
If Crafty accepts a gambit that it should not, the first search result is often going to show a positive score, because it will be ahead in material. But over the next 10 moves it will begin to "see the truth" and the search values will drop either quickly or slowly. The speed at which the evaluation drops is not nearly so important as the fact that the evaluation is continually declining move by move. Result number one then, is a steadily declining evaluation for the first ten non-book moves. If this happens, the last search result (the lowest evaluation) is saved as the first approximation of the learned result.
If Crafty offers a gambit that is perfectly playable, the first search result is often going to show a negative score, because recovering the material might take several moves. In this case, the ten search results will show the opposite slope from case one, because the scores are steadily increasing. In this example, the last search result is again saved as the first approximation of the learned result.
The other case is one where there is an inflection point in the curve that fits the ten search results. For example, after accepting a gambit, the score might actually continue to rise for several moves before the effect of the gambit is realized and the score starts to drop. The opposite case also happens when offering a gambit, where the score continues to drop for several moves before the benefits of the gambit become apparent and the score starts to rise again. In these cases, the learning algorithm searches for the best (or worst) value that occurs after the slope of the curve stabilizes.
At this point, the first approximation to the learned result is simply the search result chosen from the first ten non-book moves, as described above. However, there are complicating issues that make this value very difficult to use in its current state.
Remember that this algorithm is designed to learn how to use the opening library, while playing on a chess server. The servers allow many types of games to be played, from game in one minute, to game in over two hours. The problem with using the learned result as chosen above is that it might lead to difficulty if Crafty learns that an opening is quite bad while playing very fast games, so that it will refuse to play it again, even at longer time controls where the search result will be more accurate due to the increased depth possible with more time. Since these learned results are essentially permanent, it became obvious that things learned while playing a very long game were more reliable than things learned while playing a game where a move might be made in less than one second.
To handle this case, the first approximation to the learned value is modified based on the depth of search for the search that produced that learned value. As a result of this, Crafty now stores the first ten search values, and the depth for each of those first 10 searches, so that the depth that goes with the learned value can be found. I chose to call a ten ply search "normal" and then developed a multiplier that scales the learned value based on the depth of the search which produced this value. (this is given in the LearnFunction() code in figure 2.1 below.)
The next issue is that of the skill of the opponent. If the opponent is much weaker than Crafty, then Crafty should win easily, and using such learned results would be very misleading against stronger players. As a result, Crafty notices the rating of the opponent and compares this to its own rating (both are obtained from the chess server or from the human opponent if this is not a server-based game). It then uses this rating difference to modify the learned result.
This is complicated, however, because the learned result and rating difference mean different things depending on whether the opponent is better or worse than Crafty. The first case is a good learned result (score is positive.) If the opponent is lower rated than Crafty, then this score should be distrusted, since Crafty should win even those games where the book line was a bad one. But if the opponent is rated higher than Crafty, then this score should be trusted even more than normal, because to produce a good score against a better opponent means this book position gave the program exceptionally good chances.
Negative scores (bad learned results) are different. If the learned result is bad, and the opponent is rated lower than Crafty, then the bad result should be trusted more than normal, because we would expect that the program could take a bad position and still win, unless the position is really bad. On the other hand, negative scores against a stronger opponent are expected, and we don't want to avoid playing openings that a better player was able to win, because that is the expected result for most any opening position.
One other issue has to be addressed, and we can produce the final learned result and then apply it to the opening book line. In most chess games, but particularly in fast games, blunders (tactical mistakes) occur fairly frequently. In thinking about this, I became convinced that positive scores are not as trustworthy as negative scores, because a positive score can be produced by a human (opponent) mistake, while negative scores mean that Crafty had to play poorly to reach these bad positions. Since the program is not prone to blunders and mistakes, it became obvious that negative scores were fairly reliable, while positive scores were not. So the final step in modifying the original learned value into the final form is to decide whether the score is trustworthy or not, based on its sign (positive or negative).
Taking all of these elements into account, the following function was written to take the first approximation of the learned value and turn it into the final value used to learn.
/* sv=search value (first approximation to learned value) */ /* rd = Crafty's rating - opponent's rating */ /* trusted = 1 if confidence in this value is high */ /* this means if Crafty is white and score is < 0, we trust */ /* it more. If Crafty is black, and score is > 0 we trust */ /* this more as well */ int LearnFunction(int sv, int sd, int rd, int trusted) { float rating_multiplier_trusted[11] = {.00625, .0125, .025, .05, .075, .1, 0.15, 0.2, 0.25, 0.3, 0.35}; float rating_multiplier_untrusted[11] = {.25, .2, .15, .1, .05, .025, .012, .006, .003, .001}; float multiplier; sd=Min(sd,19); rd=Max(Min(rd/200,5),-5)+5; if (trusted) multiplier=rating_multiplier_trusted[rd]*sd; else multiplier=rating_multiplier_untrusted[rd]*sd; sv=Max(Min(sv,600),-600); return(sv*multiplier); } Figure 2.1: LearnFunction()
This function works as follows. The search depth (SD) is constrained to the interval (0,19) to avoid numbers that would produces adjustments that might be too large. The rating difference (RD) is rounded to "classes" of 200 points, much like the USCF scale, and then constrained to the interval (-5,5) and scaled to 0-10, which corresponds to a rating difference of +/- 1000 points. Next, before doing the calculation, we choose between two different sets of multipliers, based on whether this is a trusted score (negative) or not (positive). (Note that we can't rely on score < 0 being trusted, because the score can be positive and be trusted, if Crafty is playing black.) Finally, the learned value (SV) is limited to +/- 600 (6 pawns) to limit the range of the final product. After all of these values are computed, they are used to produce the final learned result that reflects all of the discussion points above.
Now we have a value that estimates the position that results from following the book line being studied. This value has been adjusted based on the search depth used to produce it, plus the rating difference between Crafty and the opponent. The next step is to apply this in some way so that the program will play this opening again if the value is good, and so that it will not play it if the value is bad.
Once Crafty has produced the learned value, the next issue becomes how to apply this value to affect the way it chooses book lines. The current approach is actually quite simple to follow.
The idea is to look at an opening from back to front, while still treating it as a tree. The tree has branches at any point on the way back from the last move to the first move where there was more than one choice that is playable (playable means a move that could actually be played in a game, not a move flagged as "?" or one which has learned to be bad).
We start with LV=LearnFunction(...) to get the initial value for LV. This value is stored with each move starting at the last move, and working back toward move 1. At each known book move, we store LV with the move, and then divide LV by the number of alternatives at this point. For book positions with only one playable move, LV remains constant, but whenever there are alternatives, moves prior to that point get a smaller LV value applied.
The effect of this algorithm tends to propagate really bad scores far back up the book line because these scores remain large even after the division, while small scores do not get to affect choices beyond the last one or two in the book line since the division reduces them to very small values. This effectively treats the book line as a tree, but in reverse order. The last point in the book where there was a choice of moves looks like the first branch point. The next branch point is closer to the root of the book line. This information is then used when searching forward through the book, so that Crafty can avoid choices which were learned to be bad, while favoring choices that were learned to be good. And the most important feature of this is that all of this is done automatically inside Crafty with no external "help" required.
One important goal of this experiment was to take advantage of the many copies of Crafty running on servers all over the world. I wanted to be able to take advantage of the things other copies of the program would learn, as well as be able to share what the original Crafty learns with other programs. To accomplish this, I chose to write a PGN file at the same time the book learning update operation is done. The complete game score is written, along with the learned value, search depth and rating difference between Crafty and the opponent for that game.
This file contains only simple ASCII text, which eliminates any sort of compatibility problems between different architectures, and it can be imported with a simple "import" command (built in to Crafty) which will read in the game moves, then pretend it has played the game and use the included learned value to update the book, just as if it had actually played that game and learned the result.
This has one major benefit, based on the fact that most opening books are now being built from the millions of electronically readable PGN game scores available on the Internet. If you want to build your own book, you can locate PGN files and make your own book, based on specific players, specific events, or specific openings. If your book ends up with several hundred thousand games in it, you will discover that many of the moves played are bad and lead to quick losses by your program. If you import the learned results from Crafty, it has probably tried many of those same openings and you don't have to let yours stumble around to find out which openings are good and which are bad.
The overall result of this has been a form of "distributed learning" where copies of Crafty are playing games all over the world, and learning things about the opening as they play. These learned results can then be collected and imported into many different programs, so that these programs suddenly become as aware of those new openings as the program that actually first played them.
This has proven to be extremely useful in Internet play, since all of the programs can play using different opening libraries, and then share what they learn with other programs. In effect, this accelerates the learning speed dramatically, because thousands of programs are learning, and sharing this learned information quickly and easily.
It has been suggested that this could be turned into a "gang-learning" facility by adding a "learning server process" to a chess server. When a program learns something from the opening, it can transmit this to the "learning server" and when it is not playing a game, it can query the learning server to obtain new learned results from other programs. This would eliminate the current facility of using email to share the PGN book learning files and let one program learn something very quickly when another program loses by playing some new opening.
As an example, a common line from the Ruy Lopez is given below, with an obvious blunder thrown in. The main line here is 1. e4 e5 2. Nf3 Nc6 3. Bb5 a6 4. Ba4. This example includes an odd choice at move 4, which loses the bishop by not retreating it as is required. (4. Nc3). This blunder game was included in the input file three times with different choices at move 6, to illustrate how learning works.
The raw input used to construct this opening book is given below.
[this is a bad line] e4 e5 Nf3 Nc6 Bb5 a6 Nc3 axb5 Nxb5 Nf6 Nc3 Bb4 d3 O-O O-O [this is a bad line] e4 e5 Nf3 Nc6 Bb5 a6 Nc3 axb5 Nxb5 Nf6 d3 [this is a bad line] e4 e5 Nf3 Nc6 Bb5 a6 Nc3 axb5 Nxb5 Nf6 O-O [this is the normal line] e4 e5 Nf3 Nc6 Bb5 a6 Ba4 Nf6
Crafty then played a game using this book with the book selection options set to force Crafty to choose the first move that is playable. After playing this game for ten moves, Crafty discovered it was a piece down, with a learned score of -2.53 (before being modified by the search depth, rating and so forth.) After analyzing the search depth (which was very shallow for this test), this learned value was scaled down to -1.35 by the LearnFunction() procedure given in figure 2.1.
At this point, the game was played again, and the book statistics are given below for the two moves where Crafty has alternative moves in the opening database, at move 4 and 6. At move 4, this is what Crafty uses to choose a move in game two if this opening is played: (the format of this information is (move, learned value): {(Nc3,-0.45), (Ba4,0.00)}. At this point, Nc3 looks bad, but not bad enough to not play, because the book selection option forces Crafty to sort the moves into order based on how frequently they were played and then pick the most frequent move unless the learned value is less than -.80.
Recall that the learned score is based on what happens below this point in the tree, and also recall that the original book input gives three alternatives two moves later. As a result, 1/3 of the original -1.35 was backed up to this book move. Two moves further along in the game, Crafty finds this book status: {(d3,0.00), (Nc3,0.00), (O-O?,-1.35)}. From this set of three possible book moves, Crafty has already determined that O-O will not be played because it has a learned result of -1.35, and has flagged that move with a "?" indicating that it appears to be a blunder.
In the first game, after playing 4. Nc3 and then 6. O-O, Crafty found the previous bad score of -1.35. In the second game, it gave up on trying 6. O-O, because the learned score is below a lower bound that makes this move not playable. Of course, 6. O-O is not the problem, but Crafty has not figured that out just yet. In this game, it therefore tries 6. d3 hoping to somehow save the piece. It then discovers that the raw learned result is -2.61 because it is still a piece down. After LearnFunction() modifies this score, Crafty remembers -1.35 for this move.
In game three, at move 4, the book statistics look like this: {(Nc3,-0.57),(Ba4,0.00)}. The move Nc3 has dropped further, since two alternatives below it appears to be blunders. This leaves only one playable move further along. This means that 1/2 of the learned value is backed up to this move, but it is averaged in with the previous learned result to avoid learning that a move is bad if it was playable in another game. Crafty finds this book status at move 6: {(O-O,0.00), (d3?,-1.35), (Nc3?,-1.39)}. Notice that after game two, it decided that d3 was also not playable, leaving only the move O-O as playable here. After trying this, it once again is faced with a learned value of -2.61, and it updates the book once again. However, this time things change further back in the book line, because at move 6 there is only one playable move left before this learning cycle is executed. This marks the last move as not playable, and the entire learned value is backed up to move 4, which is the next place (working backward) where there is a choice of moves.
In game four, at move 4 once again, the book statistics now look like this: {(Ba4,0.00), (Nc3?,-0.98)}. At this point, Crafty has learned that Nc3 loses material. It might not be the fault of this move, but at least it has learned that the alternatives at move 6 did nothing to prevent losing the bishop. As a result, it will no longer try Nc3? since it has learned, totally by itself, that this leads to a lost position.
That is an example of how this learning facility can automatically filter out bad moves without needing any sort of human intervention at all, which was one of the original goals leading to the development of this approach. Note that in this first example, the normal book move selection algorithm (based on simply playing the first move found) was used to choose moves from the book, but that the learned values eliminated moves that led to poor positions. This can be improved on as the next short example shows.
The above strategy takes too long to learn how to avoid losing due to a bad book line, because the bad move occurs in the tree above points where there are other choices. Each of the choices deeper in the tree have to be eliminated, one by one, before eventually eliminating the move that ultimately caused the problem.
For the second example, Crafty was set to sort moves based on the learned value and then was set to play the move with the largest learned value rather than the move most frequently played (unless the learned value was below the -.8 threshold which would eliminate it as in the previous example. Also note that if all the learned values for a set of book moves are zero, it reverts to using frequency at such positions since it has not learned anything there yet.)
After the book was rebuilt to clear the learned values, the same game was played again. Since all of the learned values were zero at each point where there was a choice, Crafty reverted to the frequency of play, as before, to break the ties. The first game produced the same learned value as before.
In the second game, at move 4, Crafty found the following two alternatives: {(Ba4,0.00), (Nc3,-0.45)}. In this example, 4. Ba4 is ordered first, because it has the higher learned value, so that in the second game, Crafty avoids the blunder line completely.
There are potential problems with either approach that are discussed in the next section, but given enough time, Crafty can learn quite successfully which openings are good and which are bad, at least as the openings apply to its unique skill level. It should be noted that the learned result can really reflect more about the opponent's skill level than to Crafty's in certain cases. It is certainly possible that a particular opening is not very good, but the opponent handles it very poorly leading to what appears to be a good result for Crafty.
One non-obvious problem is that any opening book that is made from a raw input file that contains over one million games is going to have a generous variety of choices. And learning by playing these openings is going to take some time. The net result is that even after playing as many as one hundred thousand games in a year, that represents only 10% of the possible book lines that can be played. If steps are not taken to reduce the number of alternatives, learning may never influence all of the games.
With the example given in section 5.1, the problem is quite obvious. It simply takes a long time, and a large number of games, to discover that a particular move is bad or leads to positions that Crafty doesn't handle very well. On the other hand, if a move is frequently played by GM players, it is unlikely that it is an outright losing move, although it certainly can lead to positions where a computer chess program might get into considerable difficulty. The positive side of this is that even if a move is popular, it will be eliminated eventually, if it leads to bad positions; and it is eliminated automatically without any outside intervention required, which was one of the original goals of this project.
With example 5.2, the problem is not quite so obvious. When Crafty plays a game as white, it learns for both sides of course. That is, assuming it wins as white, then it also learns to not play that opening variation as black since black lost. But when it plays white again, it will tend to follow that same opening line again since it will have a positive learned result at each move for white. This leads to trouble, because if it repeats the same opening enough times, someone will learn how to beat it.
It turns out, then, that example two learns quickly to avoid losing lines, but it also then learns to repeat winning lines, until it loses. Then it will learn to avoid that line and move on to something fresh. If this is repeated often enough, and this actually happened during the early development of this algorithm, Crafty eventually learns that all openings lead to losses and it starts playing as though it has no opening library at all.
To avoid this, the normal book selection criteria includes both the frequency of play for each alternative move, plus the learned result for each alternative. This still tends to avoid losing lines, but does avoid repeating the same winning line over and over until it becomes a losing line.
Before this modification was added, Crafty generated quite a bit of amusement one evening after learning was added. Playing on the Internet Chess Club server, it played a GM that tried his favorite opening line against Crafty, and he won. He then played a second game, which reversed the colors, and, as expected, Crafty played that same opening for black since it knew it was good. The GM had a chuckle, and thought it quite amazing that it learned so quickly. For the next game, the GM tried a different opening which turned out to be OK for Crafty, but in game 4, he was greeted by his favorite opening line again. He asked "when will it stop playing this?" I was forced to respond (with a chuckle) "when you manage to beat it."
One problem with the overall approach is that this sort of learning is appropriate for the version of Crafty that is used to produce the learning, but it may (or may not) be appropriate for future (and supposedly better) versions of Crafty. For example, early versions of Crafty handled bishops poorly, and learned that playing a g3/g6 type of opening led to positions that caused problems. Later, this was problem was addressed by evaluation changes that improved the way it handled these positions. Unfortunately, it had already learned that such openings were to be avoided when possible, and the new improvements were never given a chance to influence games.
It is certainly possible that as an opening move is played, or skipped, the learned value can be pulled slightly closer to zero, so that after a move has been learned to be bad, each time it is skipped it looks a little less bad (we might call this learning aging). This would allow program changes that modify the way the program plays to have a chance to influence games, because every so often, moves that were once thought to be bad slowly lose their "badness" and eventually can be tried again to see if the program has improved enough to understand the positions that gave it trouble previously.
This "aging learning" is not presently implemented in Crafty. The main issue is that moves that are "sort of bad" can have their learned value decayed over time, but moves that are "really bad" should be avoided forever. The current opening book is so large that this has not yet become a problem. However, I have found it useful to occasionally (every year or so) to clear the learning data from the book and let Crafty start fresh. After a year, it is likely that it plays differently enough to justify trying old openings again, although the ones that simply lose material are pointless and will produce losses again.
It is possible that learning might apply more to the abilities of the opponent than to the characteristics of the opening line/position. For example, Crafty might play a wild gambit line and overwhelm an opponent that does not like wild tactical lines, and then conclude (learn) that this opening looks great. Games against a stronger opponent (particularly against a computer) will show this to be foolish and the second learning cycle will turn that variation off in the book.
There is an up side to this however, as it has a significant benefit in match play against the same opponent. If Crafty wins, it will try to repeat the same opening again, putting the onus on the opponent to vary and avoid a repeat loss. If Crafty loses, it will not repeat that opening, so that if the opponent has book learning capabilities, it will be unable to repeat the winning opening line against Crafty. Matches between a learner and a non-learner can be both ugly and repetitive, for obvious reasons. There has been much discussion about "is this fair?" I think the answer is that if a program author eschews book learning because it is complex to design and write, then he/she leaves the door open for terrible match results. The answer is to do whatever you can to assist your engine in avoiding repetitive losses, and this is clearly one such solution, that is probably much better than just trying to randomize play to prevent repetitions of old games.
This has turned into an highly effective methodology for creating a useful and modern opening library for Crafty. It requires no intervention from a human operator and no hand-tuning or hand-crafting of an opening book that fits the "style" of the program, because the program is given the task of modifying the book after each game to favor opening variations that result in good positions and to reject opening variations once they are shown to lead to a bad position.
With older chess programs (Cray Blitz to name one that I worked on) this would have been a wonderful methodology to have available, because the opening book was the weakest link in the way the program played. We actually used to "hold our breath" until we dropped out of the book and started searching on our own, hoping that the first search result would be something that was not already losing. I can recall several games that were played at ACM Computer Chess tournaments where a program was lost before it ever searched the first node.
Another problem is someone "cooking" an opening for you, based on a game you played in a prior round or prior tournament. In one notorious case, Chess 4.x lost a famous game to Chaos at a World Computer Chess Championship tournament. The opening book from Chess 4.x was used for later versions, and at a later event with humans and computers, two humans played the same opening and won their games in the same way, and the new program (named NuChess) was helpless to prevent this without human intervention. With Crafty, this is impossible and we don't have to be on guard to prevent a repetition of a losing book line. If we lose in round N of a tournament, we don't have to worry about playing that same opening in later rounds and take time to modify the book by hand to avoid doing this.
This learning methodology was originally intended to learn what not to play to avoid poor positions, but it also is able to learn which openings actually lead to positions where the program is capable of using its skills to best advantage to produce winning results.
Crafty also uses the transposition table to implement a third form of learning, as described by David Slate [Slate87]. This is yet another book learning defense, and gives some protection to handle the case where an opponent tries some odd opening (1. h3 ... 2. a3 ...) that takes Crafty out of book very early. In such a case, it is still possible to find a way to beat Crafty, and now book learning won't help at all since there are no book moves to choose between.
In this case, for the first 10 non-book moves, "position learning" is used to remember positions where the evaluation drops significantly. These positions and evaluations are saved on disk, and loaded into the transposition table as permanent entries when the program is executed. This provides a form of learning, even when there are no book lines, so that it is nearly impossible to repeat the same opening and win the same game over and over.
There are obviously many things left to try. The most interesting is the concept of "gang-learning" where multiple programs play on a common chess server, and share their learned results in real-time, so that when one plays a game, they all learn from it instantly. The present email facility used to share learning results is too slow to be effective.
A common problem on the chess servers is that a player will find a line that easily wins against a Crafty player, but that Crafty player learns how to avoid the line that causes the problem. The human will then move on to another program and go through the same games again until that program learns to evade that opening just like the first one. This is often used to inflate a player's rating in an obvious way, and it would be nice to see the first program player notify all of its "brothers/sisters" as it learns how to avoid such a loss. Of course, it would also be disconcerting to the humans that use this form of abuse as well.
Another idea that has been suggested several times is to allow Crafty to add to its opening book. After playing a game where the position out of the book appears to be favorable, and the first moves out of book lead to a position that is also favorable, then those first few non-book moves could be added to the opening book so that the next game is played using the extended book line. This is not unlike humans learn various openings beyond what the opening books provide, in that once a few moves have been played and lead to a favorable game, those moves will likely be played again.
The only danger of this is that the moves might be added after playing a quick game (fast time control) while a longer time control might show that the newly added book moves are really not good enough to play. Fortunately, normal book learning would still apply and Crafty would, after playing the longer game, possibly mark as UN-playable the moves it had added previously.
H. Berliner, "Computer Chess at Carnegie-Mellon University," in Advances in Computer Chess 4, D.F. Beal (ed.), Pergamon Press, Oxford, pp. 166-180 (1985).
R. Greenblatt, D. Eastlake. and S. Crocker, "The Greenblatt Chess Program," Proceedings of the Fall Joint Computer Conference, pp 801-810 (1967).
R. Hyatt, H. Nelson and A. Gower, "Cray Blitz," in Advances in Computer Chess 4, D.F. Beal (ed.), Pergamon Press, Oxford, pp. 8-18 (1985).
T. Marsland and J. Schaeffer, Computers, Chess and Cognition, Springer-Verlag (1990).
D. Slate and L. Atkin, "Chess 4.5--The Northwestern University Chess Program," in Chess Skill in Man and Machine, P. Frey (ed.), Springer-Verlag, pp. 82-118 (1977).
D. Slate, "A chess program that uses its transposition table to learn from experience," ICCA Journal, Vol 10, No. 2, pp 59-71 (1987).


text:
The Leading Voices in Real Estate podcast series interviews some of the most successful, interesting, entrepreneurial people who shape our cities and the built environment.
Host Matt Slepin gets to the personal side not often heard from these legends and visionaries, their career stories and advice, and their role in creating vibrant communities with character, beauty, and a high quality of life.
Engaging Inner City Kids in Development via Real Deals
Cedric Bobo is the Co-Founder of Project Destined, a 501c3 that educates both inner city kids and military veterans in financial literacy and community development by their investing, shark tank style, in real estate deals in their communities.
This episode is made possible by our sponsor JLL. Learn more at jll.com/voices.


text:
The Hans III Youth Device is designed and manufactured specifically for young racers and smaller frames. Sharing the same comfortable, lightweight design as the adult-oriented Hans III Device, the Youth-sized model features a specially engineered hollow collar that reduces device weight substantially. By engineering specific reinforcements into the design, the exceptionally strong structure provides the same level of safety as every other Hans Device, but allows for the lightest and most comfortable injection molded Hans Device ever. Featuring a low-profile, sculpted round collar that allows for increased driver comfort and easier entry/exit from the car. Includes your choice of standard Post or Quick Click Anchors (select type).
Technical Information
|Part Number:
• SFI 38.1 certified
• Youth size is perfect for smaller drivers!
Anchor Styles:
Hans Anchors are available with or with-out backing plates. Many helmets are manufactured with a threaded, M6 insert bonded directly inside the helmet shell. If your helmet is equipped with this option, select the M6 option.
Note: The width of the HANS Device is sized to fit your neck or shirt collar size comfortably. You may fit several sizes – comfort is the final deciding factor.


text:
Today was supposed to be THE DAY that I finally sat down and worked on my master's project. I have barely looked at it all summer, but yesterday while I was at work I got super motivated. I had today off, zero obligations. IT WAS GOING TO HAPPEN.
My plan: eat breakfast, go to the gym, GET SHIT DONE until Mr. Peachy gets home from work (usually around 6-7pm).
Mr. Peachy and I own a duplex and we have new tenants moving in. Today they are supposed to come by to do a walk through, pay rent, and pick up the keys. Initially, I told them I'd be home all day and just told them to text me when they were on their way. Yesterday, I let them know I'd be gone from about 10:30-12:15 and they replied that they were going to come around one.
I got home from the gym at 12:20, quickly cleaned up, got together everything I needed and was ready at 12:55pm. I didn't start working on my paper because it takes me awhile to get in the groove and I thought I'd be interrupted at any minute, so I've just been on GT/Facebook/etc. That was an hour and half ago. The tenants have not showed up or texted. (ETA: They arrived while I was writing the next paragraph, at 2:45pm).
Now, I would still have plenty of time to get work done, except I work for a nanny service and they booked me for a job this afternoon. When they have a "on-call" job, they used to just email everyone on the on-call list and the first person to respond got the job. A few months ago, the switched to just booking you for the job if you are down as being available. There are some pros to this system, but I've kind of been hating it. I'm glad that I'll be making some extra money, but if they had emailed this job out in the morning, I might have decided it would be better for me to stay home and work on my project. There are also times when I'm not sure if I should mark myself down as being unavailable. Tomorrow I'm supposed to go to a friend's birthday party that starts at 7pm. I might not skip the party for a small job, but if something bigger came up, I definitely would take the job instead. And yes, I may have class from 1-2pm on MWF, but maybe I know it's not a big deal to skip it every once and awhile. I'm also not the best at remembering to mark down every single hour I have something going on (the on-call jobs I get are pretty few and far between, so it's not always at the forefront of my mind). I just hate not being able to decide if I want to take a job or not.
Anyway, I have to leave for that job in less than an hour now, so I basically have done nothing all day. I don't know what the point of this post is, I just needed to whine.
TL;DR- I hate waiting for people and I hate my job's new booking system and I hate myself for barely working on my paper all summer. And I hate this paper. I JUST WANT TO GRADUATE AND START MY CAREER ALREADY PLZ THX.


text:
Privacy Policy
This privacy statement discloses the privacy practices for Woods Hole Oceanographic Institution.
Information Collection and Use
Woods Hole Oceanographic Institution is the sole owner of the information collected on this site. We will not sell, share, or rent this information to others in ways different from what is disclosed in this statement. Woods Hole Oceanographic Institution collects information from our users at several different points on our Website.
No personally identifiable information (e-mail address, name, etc.) is collected with the cookies that we set, and accepting cookies while on the Woods Hole Oceanographic Institution site will not put the user at risk for marketing to other sites.
Different browsers have different cookie-settings. With Netscape you can ask the browser to allow, warn you, or completely disable cookies. Internet Explorer has an additional feature where you can specify different settings for different security zones. You can choose to allow Websites to create cookies for you in your "trusted sites" (like Woods Hole Oceanographic Institution), to warn you before you create them in your local Intranet zone, and to give you an option to never allow them in a "restricted zone." See the "Help" section of your particular browser for more information on working with cookies.
Web Statistics
We use IP addresses to analyze trends, administer the site, track user movement, and gather broad demographic information for aggregate use for reporting and sponsorship purposes. IP addresses are not linked to personally identifiable information.
We will share aggregated demographic information with our sponsors and donors. This is not linked to any personal information that can identify any individual person. We only share this information so that we can secure funding to continue providing this site free of charge.
This Website may contain links to other sites. Please be aware that Woods Hole Oceanographic Institution does not claim any responsibility for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every Website that collects personally identifiable information. This privacy statement applies solely to information collected by this Website.
This Website takes every precaution to protect our users' information, and we have security measures in place to protect the loss, misuse, and alteration of the information under our control.
Surveys and Feedback section
From time-to-time our site requests information from users via Web surveys. Participation in these surveys is completely voluntary and the user therefore has a choice whether or not to disclose this information. Information requested may include demographic information (such as education level), but no information that can identify any individual person will be collected. Survey information will be used for purposes of monitoring or improving the use and satisfaction of this site.
Notification of Changes
If we decide to change our privacy policy, we will post those changes to this page.
Donor Privacy
The Woods Hole Oceanographic Institution (WHOI) is committed to respecting the privacy of our donors. We have developed this privacy policy to ensure our donors that donor information will not be shared with any third party.
WHOI provides this Donor Privacy Policy to inform you of the way your information is used. We also provide you with the opportunity to remove your name from (or opt out of) our mailing list, if you desire to do so.
Donor Contact Information
WHOI collects and uses various information from donors that includes: amount donated, address, telephone number, donor comments and e-mail address. Tax laws in the United States require WHOI to keep contact information and contribution level of donors on file.
WHOI uses donor information to understand donors' needs and provide excellent service. WHOI will never sell, trade, rent or share names (unless released for publication), e-mail or mail addresses, or telephone numbers of our donors. Donors names will be listed in our annual donor report, unless otherwise instructed. This report is distributed only to donors (not the general public). WHOI will use contact information (e-mail, telephone number and address) of donors for these purposes only:
- Distribute receipts for donations
- Thank donors for their donation
- Inform donors about upcoming fundraising and other activities at WHOI
- Internal analysis and record keeping
- Reporting to relevant U.S. and State agencies (these reports are not for public inspection)
- Contact donors about changes to this policy
Properly anonymized donor information is used for promotional and fundraising activities. WHOI allows donors the option to have their name publicly associated with their donation in an annual donor report unless the donor explicitly chooses to remain "anonymous".
Questions or Comments
If you have any questions about this privacy statement, the practices of this site, or your dealings with this Website, you can contact us using the information below.


text: image by: mk vecchitto I wander halls with many doors Of varied woods and endless cores The choice I make will not be forced On cosmic course. On cosmic course I skip through one of oak that shines Am in a place of flowered vines Each bloom displays precise guidelines There will be fines! There… Continue reading OctPoWriMo2019 Day 5 and MM Saturday Mix – Aperture


text:
The all-new Polaroid Design 3D pen is the subject of a new crowdfunding campaign on Indiegogo that specifically targets professional artists, designers and engineers.
When the printing pen was first unveiled at this year's CES, it was initially presented as a product for at-home users and families. However, Polaroid now says: "Because of the positive reception the Polaroid Draw 3D pen received, we decided to take a look at other segments of the market that were in need of quality 3D products at the right price point."
The Polaroid Design 3D pen includes features like six speed presets, a built-in cooling fan, temperature settings and an OLED LCD screen for displaying settings. Some of the filaments that are compatible with the printing pen include everything from wood to metal.
Polaroid is Launching Its New 'Design 3D Pen' on Indiegogo
Laura McQuarrie — May 16, 2017 — Art & Design


text:
Among classical methods of knowledge transfer, the complex issue of sustainability can be delivered using special interactive methods. Based on the assumption that a sustainable future requires a global population that can make themseselves heard, develop convincing arguments and reflect critically , the role play "Scientific Conference - Panel Discussion" has been developed.
Within various disciplines, such as educational science and psychology, the role play is an acknowledged and valuable method to reflect your own social action and behavior. In the context of sustainability at the university, this method helps to repeat and critically reflect on participants have learned. Students find themselves in the role of an expert and learn to articulate and defend their own point of view as well as to communicate (professional- or experiential-) knowledge. The role play also allows students o broaden their social competences and strenghthen the knowledge they gained from previous lessons.
The method "Scientific Conference - Panel Discussion" can be adapted for different target groups and topics and has been developed for the project "Sustainicum" to explore inter-and transdisciplinary research. Even Karl Popper expressed (1963:88) "We are not students of some subject matter, but students of problems. And problems may cut right across the borders of any subject matter or discipline."
Issues of sustainable development are characterized by their complexity and make inter- and transdisciplinary approaches necessary to approximately meet the comprehensive requirements. There are different definitions of ID and TD. The National Committee on Science, Engineering and Public Policy (2005) defines interdisciplinarity as follows:
"Interdisciplinary research (IDR) is a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, and/or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline or area of research practice."
Moreover, Pohl and Hirsch Hadorn (2006) say that transdisciplinary research is characterised by four properties that can be combined in various ways. The properties are:
- the exceeding and integration of disciplinary paradigms,
- the participatory research,
- the orientation on life-world problems and
- the search for a universal unity of knowledge beyond disciplines.
This implies changed procedures in the research process, a number of new requirements for the role of the scientists and e.g. the integration with the requirements of different methods, theories and forms of knowledge.
Although the above mentioned definition of ID and TD is only one out of many (different ideas and definitions of ID and TD are also discussed in this role play), it shows significant and new scientific requirements. This, on the other hand, results in the roles for the role play method "Scientific Conference - Panel Discussion". The "building block" is prepared fo a "Panel Discussion, Scientific Conference on inter- and transdisciplinary research" and simulates a real life situation in a scientific environment.
- Specially prepared for the inter-and transdisciplinary teaching
- In this case the tool has been prepared for scientists (scientific role play) who attend a simulated scientific conference
- requires specific preparation time to review literature and should take place at the end of a seminar or training (on a chosen topic).
- If the focus is not on an internal scientific discussion, the role play could be part of a classic TD stakeholder workshop. Organisers should create new roles, such as regional actors who have participated in TD processes, or NGO representatives, etc.
- Moreover, participants could still discuss in their roles as scientists. In their roles they should then get feedback from those who have taken the role as a stakeholder. This sharpens the view regarding the issues beyond the scientific context.
- Regardless of the type and the content of the course, this concept is individually modifiable. Texts need to be replaced and roles should be redefined/adjusted. By further adaption and by adding new articles (English literature) one can achieve an English version of this role play.


text:
Signature Blends 2oz Scent Shots
- Our 2oz Scent Shot Pots from our exclusive Signature Range
- £2.60
A Dream is a Wish - A dream come true of pink perfumes and soft petals, adorned with twinkling stars and a hint of herbal lavender.
Airy Faerie - Snow Faerie on a fluffy, fresh cloud of ozony air.
Amber Nectar - A smooth blend of golden amber and honey, shimmering florals, sparkling fruits and sensual musk. Utterly beautiful!
Apple Rhubarb Crumble & Ice Cream - A total comfort scent- Warm, sweet apples, tart rhubarb on buttery crumble with a dollop of vanilla ice cream.
Baby Dove - A soothing blend of clean Dove soap and soft Baby Powder.
Blueberry Lavender Cheesecake - Fruity blueberries, flecks of herbal lavender on a vanilla cheesecake base.
Blueberry Lavender Ice-Cream Cake - Kelly's creamy-sweet blend of juicy blueberries, a dot of lavender and vanilla. Lightly bakery and lovely.
Bobbing Apples - Spiced apple, toasted marshmallow and smouldering woods.
Boxing Bray - Emma's birthday blend of Rhubarb & Snow Faerie.
Breakfast at Tiffany's - Breakfast at Tiffany's - A fluffy, light blueberry and lemon muffin. Not too cakey, but a great start to the day!
Buzz Off!- Well known for it's bug-busting properties, we combined essential oil of citronella with fruity notes of strawberry, mandarin, and raspberry.
Calm Your Pants - A soothing blend of lavender and incense.
Champagne Supernova - A fizzy, iced champagne with an explosion of red berries, balanced delicate jasmine and violet.
Cheeky Vimto - a shake up of blue raspberries and forest fruits, poured over crushed ice.
Cocolime- You put the lime in the coconut, drink them both up!
Coffee Ice Cream - Rich, roasted Colombian coffee swirled around creamy, sweet vanilla bean ice-cream. This is mouth-wateringly delicious!
Confetti - Soft, fresh petals with notes of freesia, cyclamen, African violets and jasmine, drifting over a gentle base of white musk, amber and a hint of vanilla.
Cornish Pisky - Piskies are the fairy folk who feature most widely in Cornish folk tales. Although they sometimes have a wicked sense of humour, they will help anyone who treats them with respect. A blend of bubbly soda pop, sweet candy, sweet oranges, cherries and vanilla.
Corpse's Shell - Earthy, pungent and heady, with herby, floral notes.
Cosy Cwtch - Shaila's oh so snuggly blend of Warm & Cosy and Chocolate Orchid.
Cotton-Picking Candy - Barrie's blend of sweet, sugary cotton candy with a loopy mash of oranges, lemons, limes and sweet berries.
Cwtch- A snuggly hug of mandarin, lavender and chamomile, hints of lemon, raspberry, honeydew melon, blackcurrants on a base of musks, sandalwood and patchouli.
Dark Faerie - When faeries go bad. Lingering sweetness taken over by deep, dark fruits, patchouli and sandalwood.
Faerie Cakes - Sweet and fluffy vanilla cake with sugary pear drops and candyfloss
Faerie Farts - Fruity, sweet and full of cheekiness!
Field of Dreams - Zara's blend of clean, green florals and a touch of laundry, softened with a little creamy vanilla, frankincense and woody notes.
Fierce Faerie - A sexy, woody aromatic blend, giving a ferocious edge to our innocent Snow Faerie.
Flirtatious - Innocent vanilla interlaced with oriental petals, tonka bean and exotic woods.
Flower Faerie - Soft pink petals, wrapped in vanilla orchid, sweetened by sugary vanilla and pear.
Fluffy Pink Dragons- Dragon's blood wrapped in cuddly pink fluffiness. Sweet, earthy and totally mysterious.
Forever Young - A feminine heart of Blue Agave, amidst vetiver, orchid and cacao, mingled with masculine frankincense, leather, black pepper and a touch of sweet mandarin. If there was a serum of youth and immortality, this would be it!
Frilly Pink Knickers- Pink Sugar and Fresh Linen take an innocent little scent and give it a saucy twist!
Fruity Love - Nicola's blend of Love Spell, Strawberry and Orange.
Fruity Mama - Zingy hot pink lime and sweet tropical watermelon- one for the summer!
Goldilocks - Sweet and innocent vanilla with decadent porridgy undertones.
'Her' - Rich-ripened strawberries with cotton candy and French vanilla on a bed of fresh cut roses, white musk and amber.
In-Complete Trance - Sexy, masculine notes of green citrus and chilli pepper, mellowed out an infusion of sweet orange, neroli, violet, and herbs, with a bottom of powdery floral musk.
Jessica - Bill's progeny; even though she is a young vampire prone to blood lust and drawn to fairy blood, she is not ruthless. Like her maker, she tries hard to hold on to her humanity. She has a seductive scent of patchouli, Egyptian musk, hints of orange blossom and subtle spices.
Kick- Back & Chill - Karen's beautiful blend of soothing sandalwoods, violets, musk and lavender with Pomegranate Noir. Absolutely stunning!
Kiss From A Rose - Ripe passion fruit, Tuscan grapes, yellow peonies and vanilla orchid, kissed by deep, fresh-cut roses, amber and musk.
Laundry Lady-Killer - Maryanne's blend of shaving cream, hot towels and aftershave, hints of ultra clean spearmint, sage and eucalyptus on a strong laundry base. Phwoooaar!
Lavender's Blue - A walk through a lavender embellished enchanted woodland.
Lavender Chiffon - Pretty pink perfume with a relaxing lavender touch.
Lavender Cotton - Clean, fresh cotton with herbal lavender.
Lavender Laundry - Our fabulous herbal lavender on freshly washed laundry.
Lavender Lemonade - A refreshing citrussy beverage, flecked with herbal lavender. More lemons than lavender, but utterly summery and beautiful!
Lavender Rain - Earthy patchouli, fresh ozone with lavender and soft florals.
Lavender Wish - Pretty perfume and a swirl of lavender. Girly and romantic.
Lemony Bath - Tor's blend of Have a Bath and Lemon Sherbet.
Llandaff Fields - Ozony clean air, wafting through soft florals and freshly cut grass.
Lock Up Your Wives - Zara's blend of sumptuous Tobacco Leaf and deep spices, accented with citrus, Tobacco Flower, rosemary, vetiver and soft florals, bedded with a rich vanilla, Tonka Bean, amber, oakmoss and white musk.
Lucky Dragons- Rich, mysterious Dragon's Blood with sweet Serendipity. Beautiful!
Lucky Lemons- Zingy, sugary lemons on a bed of sweet Serendipity.
Lullaby - Alison's dreamy blend of Nag Champa and Lavender.
Lush- Sweet bubblegum, lemon drops and cotton candy mingled with ripened raspberry, ylang ylang, rose and vanilla beans.
Magic Faerie - Snow Faerie with notes of magical fruits and petals on a base of Nubian Musk.
Moody Faerie - Sweet Snow Faerie meets dark patchouli and golden amber, with ruby-red pomegranate, pink peppercorns and spicy woods.
Mumsy Wumsy - Named by the lovely Thomas. A familiar fabric softener type mingled with all the sweet treats of bubblegum, cotton candy and lemon drops because 'Mummy is a sweetie!'
Noella Sandal-Wood - A glorious blend of all the sandalwoods, gently earthy and soothing, sweetened with a hint of vanilla. Beautiful, just like the lady!
Orange Birthday - Clean, crisp mandarin orange and creamy, white birthday cake.
Our First Birthday (Secret blend)
Our Second Birthday - A secret celebratory blend. Softly sweet and comforting.
Parklife - Take a walk through freshly cut grass, vanilla orchids and pink petals. Strictly no pigeons.
Pirates & Petals - Oceanic sea salt with fresh, tangy ozone enveloped in sweet cherry blossom and mimosa flower petals. This is stunning blend!
Posh Peach Tea - Sam's suggestion of Earl Grey and ripe, juicy peach juice.
Rapunzel - With all that hair to look after, Rapunzel is the smell of fruity, fresh and fun shampoo!
Raspberry Roller - A fresh raspberry and green apple cocktail, embellished with cool notes of cucumber and mint.
Rewrite the Stars- A dreamy hit of herbal lavender, embellished with wild vanilla, a hint of strawberry and delicate violet and jasmine.
Seaside Kiss -Summery melon, purple passionfruit and Tuscan grapes, entwined with vanilla orchids, peonies and a hint of suntan lotion.
Shoo Fly! - Reminiscent of a wild Indonesian Herb used to keep bugs away. With notes of chamomile, citronella, rose, jasmine, lily and pine. Perfect for summer nights outdoors!
Shooting Star- Twinkling citrus notes, succulent strawberries and vanilla embraces the delicate floralcy of violets and jasmine and a clean, herbal heart resting on a base of musks and woods. A little bit of everything special to make wishes come true.
Sleeping Beauty - Powdery and soft, feminine and lovely. Floral bouquets of lavender and violets, entwined with sandalwood, cashmere and white musk.
Sleepy Mermaid - Oceanic florals, gentle woods and a twist of lavender.
Smells Like Teen Spirit - Musky male aftershave and mosh pits!
Sniffle Buster- traditional vapour rub with an essential oil boost to blow away those nasties!
So Solid Sue - In honour of Barrie's lovely mum. A clean and fruity blend of creamy soap and juicy strawberries.
Sonnet - A romantic blend of saffron, pimento berries, white pepper, and a lovely blend of plum, rose, patchouli, and vanilla.
Sooki - Sooki is a beautiful young woman, half-faerie, trying to survive in a supernatural world. Her scent is gently intoxicating: one of glistening powdery florals entwined with musk and greenery.
Soothe - A calming blend of gentle ginger, amber and tuberose, with notes of frankincense.
Stag Do - The Obnoxious Reindeer ventures out on the town with the boys- a splash of cologne and he's ready to party!
Strawberry Detox - Our amazing super strawberry, blended with cool cucumber slices and fresh mint leaves.
Strawberry Laundry - Sweet, ripe and juicy strawberries on freshly laundered sheets.
Strawberry Lemonade - Fizzy and zesty fresh lemonade with ripe, juicy strawberries. The perfect summer scent!
Strawberry Rhubarb Jam- Sweet, sticky strawberries and tart rhubarb are the perfect combination in this jammy treat!
Stench is in the Air - Rich, exotic Oudh wafting amidst rich, dark fruits.
Sugar on the Side - Sultry Blonde Moment and Pink Sugar.
Summer Linen- Fresh, clean linen with a coconutty twist.
Sunshine After the Rain - Clean, oceanic, salty air, mingled with sun-ripened fruits.
Sun-Dried Sheets - Sweet orange and lavender, patchouli, incense and golden amber blended with a dreamy detergent base.
Take a Chill Pill- The ultimate stress-buster, packed with essential oils to bring calm amongst the chaos.
Tangtastic - Perfect for a sweetie addict! Mouthwatering blue raspberries, tangy rhubarb and sweet bubblegum.
The Snow Queen - Wintery holly and pine with hints of rose turkish delight.
Thomas's Peppermint Cake - A buttermint candy blended with birthday cake. Sweet, minty and very vanilla (and of course green, his favourite colour!)
Thomas's Tango Twist - A citrus blast of juicy limes, sugared lemon and sweet fizzy orange! The blend was chosen by our very own mini Scentsible person!
Tooth Faerie - The faerie with the cleanest teeth! Sweet peppermint and vanilla mingled with candyfloss and pear drops
Vaporize - Super strong to help clear the sinuses. A eucalyptussy Vapor Rub with a twist of lavender.
Vishous - Half vampire, half demi-god, adorned in a black leather glove to protect others from his power to incinerate. He omits dark, brooding spices that are irresistible to any female.
Waterfalls - A cool, mediterranean waterfall, framed by olive trees, cyclamen and earthy vetiver.
Weird or Wonderful? - Fresh Outdoor notes of Eucalyptus, Menthol and Pine, with a rich, minty chocolatey base!
Zara's Zen - 100% Essential Oil blend. Aromatic lavender, clary sage, chamomile and geranium entwine with refreshing notes of bergamot.
Zest For Life - Bright and zingy lemons, tart rhubarb and mouth-watering pineapples.
Zingzilla - A zingy mash up of Pink Lemonade, Rhubarb & Lemon.


text:
4343 University Parkway, Natchitoches, LA 71457
From $5.00
No upcoming date/times for this event.
Dark Woods Haunted House is located at 4343 University Parkway in Natchitoches, Louisiana between I-49 and Northwestern State University, just 1.5 miles from interstate.
Dark Woods' is a fear-inducing, outdoor adventure that brings the horror, folk-tales, and legends of this region together in a uniquely entertaining early 20th century setting. New for 2016, experience your worst versions of terror inside our new blacklight 3D Dark Carnival. Crazed clowns, floating floors, and walls that appear to move will warp your chromadepth covered eyes for an experience like no other found in Louisiana.
Dark Woods offers an immersive themed experience created by character actors, detailed costuming, realistic sets, and Hollywood style special effects. You will FEAR THE DARK.
Tickets are available at DarkWoodsHaunt.com, or purchase yours at the box office anytime between 6:00pm and midnight on open nights beginning September 23, 2016.
Ticket office and parking with free shuttle service opens a half hour earlier at 5:30pm and will close at 12 midnight. Main gate opens at 6pm. and this year's attraction Dark Carnival 3D opens at 7pm.
Simply put, we love all of our service personel! Dark Woods offers militray and First Responder discounts at our box office on show nights. Get more info below!
Tickets purchased online or at the box office are valid for any open night through the 2016 Halloween season.
No refunds or returns.
In the event the venue cancels an event, you will be refunded within 4 business days of the event date for your purchase. For our severe weather policy visit: http://www.darkwoodshaunt.com/about/severe-weather-policy/


text:
All of those doomsayers about the central banks throwing money in the economy of the countries through quantitative easing (QE) ....and eventually making cash worthless.....is that for real?
Financial bubbles....
by mikeflood 2 Replies latest social current
Absolutely. Does that spell Armageddon..??? NO! Not Watchtower style anyway.
The USD is supported by the fraud of the FED, like Bernie Madoff on steroids.
The CIA is also employed, to destroy the currencies of other nations, creating a vacuum that is then filled with the USD in order to create a false demand.
It all comes apart in the end. The only question is, what will fill THAT vacuum when the USD finally falls apart.
Historically the US is due for an economic contraction 2018-2020
i am not an economist but when watching economists debate the current US condition everything happening with the dollar, interest rates, taxes, spending, trade, etc. this is all old hat pre-contraction stuff
the biggest companies in the market are all tech companies, HUGE worth BILLIONS, but the manufacturing sectirs are starting to show weakening, these huge growth tech companies are propping up the market to appear stronger than it really is at its core
its coming
maybe not 2008 but it's coming


text:
Last night, I went to open gym at my local Crossfit. My adrenals are not in any shape to be able to handle 15 minute met-cons, so I generally skip the WODs and stick with the strength work. Nice, slow strength progression with lots of rest in between max lifts. This was pretty easy to do last night in particular because the box was packed! All present were women (except our coach) and it was awesome to see so many ladies sweatin' it up and moving some pretty burly weight!
Crossfit-style workouts did a lot to help bump up my climbing game during the early fall. Funny thing about having increased strength for climbing- its makes the climbing more fun! When you've got the guns to hang on a little longer, or try a harder grade climb, well, climbing can become down-right addicting! The increased strength & endurance also did wonders for my leading, giving me a cooler, calmer head and fewer instances of sewing-machine leg!
For various reasons (re: excuses), I've not been working out regularly for the last two months. However, with ski season baring down on us (maybe, I'm taking this on total faith that the earth is tilted far enough away from the sun here in the northern hemisphere for winter to happen. Its currently the end of November and today's weather forecast is calling for highs near 60 deg F!), I decided it was finally time to get my ass in gear and start building some strength & endurance in my legs for skiing. Knowing now what seemed to help my climbing, I decided to apply the same principles for ski season training.
So here I am, at Crossfit, doing some back squats. Photo credit: Jennifer Steck
Now this is what I love about Crossfit. Ladies, do not be afraid to lift heavy weights! Unfortunately, the most that typical gyms offer is a set of Nautilus-type machines that often times, are not designed for a woman's biomechanics. This is how injuries happen! Furthermore, while there is a time and place for doing isolated muscle movements (if you're a bodybuilder for example), what I've learned from my training in anatomy and kinesiology is that there is no such thing as a muscle moving in isolation in real life! The buzz word in Crossfit circles is "functional movements." Now that term can be, and is, debated endlessly. But a squat is what I would call a functional movement. Why? Because you are moving multiple muscle groups in a way very near to a situation you would use in real life- there's something on the ground and you need to pick it up. How do you accomplish this? You either bend over at the waist with your knees bent a little and then press up (deadlift!) or you squat down and then press up through your legs. Bonus for our fair sex- squatting is key to building the right amount of tone through the muscles of the thighs, hips and pelvis so that the muscles of the pelvic floor are the correct length and tone to do their job. And what is their job, you ask? Their job is to keep your pelvic organs where they belong- in your pelvis! Incontinence & prolapse of pelvic organs are symptoms that the pelvic floor is not doing its job. So if you pee when you sneeze, you need to squat! (Note: I don't want to get in to a technical discussion of the biomechanics here. But if you are interested in learning more, I highly recommend surfing on over to http://restorativeexercise.com/ and purchasing the "Down There" DVD or the No More Kegels online course. Katy Bowman is an absolute wiz at the biomechanics of a woman's pelvis. She probably knows a thing or two about a man's as well.)
But I digress. What I love about Crossfit is that you can lift like this here. They actually have heavy weight plates, lots of bars and floors that you can drop weight on to if you need to dump them. In contrast, gyms these days seem focused on cardio & toning. Both are useless in my opinion. 30 minutes on the treadmill a day will probably result in just enough weight loss to keep you shelling out $10-$25-$45 bucks a month to keep walking on that treadmill 30 minutes every day, literally, going nowhere. And what about toning? If you want to build muscle, build some freakin' muscle! Lift something heavy!!! If you're a women, unless you are taking anabolic steroids or testosterone injections, it is physically impossible to get "big" lifting heavy. (I promise, the other ladies present at Crossfit last night were all devastatingly good-looking and they were moving some big weight!) You will however, get more tone and actually develop some useful strength in the process. Which brings me back to my squat. Do you ever watch people ski? They are essentially in a squat position the entire time they are going downhill. Squatting helps train the strength & endurance to hold this position during long runs. Meaning more runs, with less pain at then end of them. Which means MORE FUN!
Which, at the end of the day, isn't that what its all about???


text:
|In stock (1)
You will receive a hardcopy high-quality colour-print pattern.
Located in an upland area between the Monashee Mountain range and the Okanagan Valley is Big White Mountain, the highest summit of the Okanagan Highland and home to the third largest ski resort in British Columbia. A family-oriented winter playground affectionately called "Biggie" by locals!
These quick, cozy mittens include options for two sizes.
YARN/YARDAGE: Super Bulky/Jumbo weight yarn approx. 105–145g (65–90y), depending on size knit.
Shown in Malabrigo Rasta (100% merino; 90y/150g), in Plomo (adult L/XL).
GAUGE: 10 st / 4" in pattern, after blocking.
adult S/M (adult L/XL)
to fit hand circumference: 7 (9)"
6½ (8)" around palm by 9 (10)" long, after blocking.
Images courtesy of Knox Mountain Knit Co.