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Yarn shop owner runs closely knit business
Globe Staff Photo/Wendy Maeda
Knitting as a hobby is the "new yoga," said Janet Hampson, proprietor of The Woolpack yarn shop in Acton, where she sees a lot of customers with think-tank jobs who never go home with anything tangible. "Knitting is something you can touch and say, 'I did this today.'"
Long before Julia Roberts, Hilary Swank, Jennifer Aniston and a whole new batch of younger 20 and 30-something knitters made this retro-trend craft fashionable again, Hampson, 64, has been armed with 4mm needles and a skein of yarn. She was a national sales manager for a knitwear company, and when she was laid off nine years ago, she said, "It was time to reinvent myself."
Given her contacts on the wholesale side of the industry, she thought that a knitting shop would be ideal. After intensive consumer research, she opened a shop in Littleton, that moved to its current location this past fall. "We like to play nice in the knitting world," said Hampson. "I didn't want to be too close to any competitors."
With about 38 million knitters in the US, Hampson sees knitters from all demographics browsing through the yarn, needles, and buttons in her shop. From her perch behind the counter, Hampson approaches knitting with a sense of humor that she hopes to pass onto her customers. No physical is required to sign up for her Knitting Needle Aerobics which "exercises needles," she said, and when it comes to knitting for mature figures, she asks, "Does your front look like your back? How about your husband's front and back?" offering advice on how to adjust patterns accordingly.
Q: How has the downturn in economy affected knitters?
A: Typically when the economy goes sour, the interest in knitting goes up – not because it's less expensive to knit, because in most cases it's not – but because gives a sense of purpose. Knitting is very meditative, allowing your mind to relax and go wherever it wants. It can be as intricate or basic as you want.
Q: What's hot for the spring 2011 season?
A: The hottest thing is new fibers manufactured with soy and bamboo, both by themselves and in combination with each other. The fibers are very luxurious but lightweight.
Q: Do you have any male knitters in your clientele?
A: I have both male knitters and crocheters; one of them does a lot of knitting for his grandchildren. Another travels extensively and fills time on the plane and airport while away from home. They enjoy it and don't feel there's any stigma attached to it.
Q: A lot of knitting shops play off of puns – A Good Yarn, Have Ewe Any Wool, String Theory. How did you come up with the name for your shop?
A: The name and logo are from an English Tavern Sign. About 20 years ago, my husband's boss, a former antiques dealer, brought back a replica of the original tavern sign and it hung over our fireplace mantel for years. When I started thinking about names, I initially went for the "cutesy" ones, but I realized I wanted the shop to have the feel of the old Boston Cheers tavern, so "The Woolpack" it is.
Q: As a knitter yourself, what are you working on now?
A: My latest project is a linen shawl to display in the store as an example for our new upcoming spring collection. Every spring and fall we bring in new yarns and designs, with the discontinued inventory going into our so-called orphans and oddballs sale corner.
Q: What does your husband think of your knitting?
A: He gets really relieved when I finally put it down to go to sleep. But seriously, he knows how much happiness it brings me, and a happy wife is a good wife.
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Home › Forums › Rumors › get well big scoob
This topic contains 18 replies, has 18 voices, and was last updated by James Clougher 2 years, 7 months ago.
missed you in chi big homie the crew said u were having some issues i wont discuss for your privacy but get better soon…STRANGE
i dont think its private on here. everybody pretty much knows whats goin on with him…and yes get well big homie!
Get well scoob
Get better Homey for the Show.Me
I gotta say I have huge respect for Scoob staying crunk at his own risk but it is definitely a tragedy that hopefully turns around for the big fella
whats up with scoob i haven't heard anything about him? i was wondering why he wasnt on tour. either way stay strong scoob
unfortunately his kidneys are failing him…he said it on his twitter a while ago. he said he might make it he might not
Jbone9 said:
Get well Big Scoob.
Salues up.
get well homie.. hopefully kc dont lose another big guy.
Hopefully we get some new updates on Scooby soon. And no more salue, get them kidneys in order.
Stay Up^ Scooby…Get Well Soon Homey.
Damn my nigga you cant be drinking like that everyday allday get well villian strange and us need you !
Just bump my old thread, it's easier lol
Get well Scoob!
damn i didn't know about this. i pray for a quick recovery
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Category: Erotica/Erotic Romance/Romance Description: An empathic young nurse driven to help and heal others since childhood after watching her mother languish for months before finally succumbing to cancer, Aziza Lopez abhors cruelty and suffering in any form. When she is assigned comatose patient David Healey, Aziza is confronted with the depth of her abilities for the first time since her mother's death and has a chance to contribute to a patient's recovery when modern medicine fails. But can she convince anyone else outside of David's family that she knows who is responsible for his injury when she's finding it hard to deal with the knowledge herself? The youngest of five brothers, David Healey comes from a close-knit, no-nonsense family of psychics and shapeshifters. He has never suffered fools--or demanding, jealous girlfriends--lightly. But on the eve of a bitter break-up he realizes he is about to suffer a woman scorned when he glimpses his ex behind the wheel of a car careening towards him. Now Aziza and David are in a race to pull him out of his coma before Aziza's vengeful stepmother can get to him and finish the job she started on a dark road. [Erotic Urban Fantasy/Interracial: Contains graphic sexual content and adult language.] eBook Publisher: Siren-BookStrand, Inc./Erotic Romance, 2007 March 2007 eBookwise Release Date: May 2007
77 Reader Ratings: Great Good OK Poor Available eBook Formats: OEBFF Format (IMP) [90 KB] Words: 16286Reading time: 46-65 min.
4.5 Flags: "Gracie C. McKeever delivers another fantastic paranormal tale of intrigue! Nine Inches of Snow and the Ebony Princess is a quick read that has an easygoing flow to it. In the beginning of the book, what I noticed was the establishment of the characters' voices. Aziza speaks with slang while David is acting in a way befitting to his upper crust upbringing. This is most certainly a well written new-styled fairy tale. One thing is for sure, when you read a Gracie C. McKeever book: you'll always get a delightfully crafted story with her guaranteed special twist! If you haven't read a title by the author you are missing out. Nine Inches of Snow and the Ebony Princess is one book that I unquestionably recommend."--Chantay, Euro Reviews
4 Hearts: "With different slang and fewer modern day references, a reader might imagine that they were reading any one of Grimm's Fairy Tales with a decidedly sexy bent. Ms. McKeever has drawn elements from several traditional fairy tales and given them her own trademark twist. Who would have ever though that the big bad wolf would turn out to be a hero? Or that Sleeping Beauty would be male? Because it is presented as a fantasy tale, this reviewer was immediately able to suspend any sense of reality and enjoy this bon-bon of a tale simply for what it was--another fantastic story by the great Ms. McKeever. Aziza and David are an extremely likeable pair and the reader will find themselves rooting for them as one does a favorite sports team. Their sexual chemistry is absolutely combustible, and David's grandfather is a hoot! The only complaint this reviewer had about this tale is that it was too short, though the story was definitely complete! Recommended to all fairy tale lovers!"--Leah, Love Romances and More
4 Stars: "This adult fairy tale is a cross between Cinderella and Sleeping Beauty. David and Aziza instantly connect at the fundraiser; both know by instinct that they belong together. Aziza is a strong woman who does not take anything from anybody including David. David is a man who is used to being in charge and getting what he wants. It was wonderful to read about Aziza and David finding their happily ever after. Ms. McKeever has written an excellent fairy tale."--Racine, Ecataromance
4 Champagne Flutes: "Oh wow ... Liking this tale more and more as I read along ... The book is written in such a way that it seems entirely natural that a man can be a wolf, sniff out his mate and find out where she lives and then go to visit her. I liked that aspect of this story. It was a natural progression in the tale ... [Philomena, the stepmother] is totally creepy and utterly weird. I love the way she is shown in this book. I keep getting goose bumps when reading about her...I feel the need to race through and see what's going to happen. Good job ... Shape-shifters, mind readers and bunny boilers. Just my cup of tea. I am so glad I read this book. I haven't been given the chills like this with a character for quite some time."--Wilga Hill Boomerang, Cocktail Reviews
"Sassy and sizzling from the get-go, Nine Inches of Snow and the Ebony Princess is an entertaining tale. Aziza and David are both engaging characters who practically jump from the pages. However, it's David's ornery grandfather who just about steals the show. Toss in a bit of a mystery to add to the romance and you have a short and sweet pick-me-up to begin or end the day with."--Phillipa Ann, Romance Reviews Today
"Someone call 911!"
"Did you see that? The car just ran right over him and didn't even slow down!"
"Is he dead? He has to be after that."
"Did anyone get the license plate?"
David saw and heard everything clearly--the people hovering over his body, their words of concern and cries for help. He just could not respond.
He was trying to figure out whether or not this was a bad thing when he realized he was in wolf form and outside of his body.
Oh, fuck.
Something had gone wrong, something he'd never encountered or heard of before.
He'd started to shift when he saw the car coming at him and recognized Philomena behind the wheel. It was a natural reaction, his body instinctively changing to another form to avoid maximum damage, or at least trying to change. She'd come at him so fast, it was a wonder he'd had time to react at all. It was a wonder, too, that he'd seen her face. But he had. There'd been no mistaking that long, platinum blonde hair or hateful green-eyed glare.
She'd meant to kill him.
David trotted over to his body to see if she'd succeeded, nuzzling his neck and releasing a howl at the non-response. He gaped up at the spectators and realized when none of them reacted to his presence that they couldn't see or hear him.
Double fuck.
Either he was dead, or he wasn't. Either he was wolf, or he was man. He couldn't be both, could he? David had never heard of a split or bilocation of this nature. He needed to get to his father or grandfather to find out what was going on.
Would either of them be able to hear or see him any better than the spectators could?
He glanced up at the nearby apartment building, drawn to his original destination, the question momentarily moot. Something beckoned him. Someone.
Aziza was close. He could feel her.
David stepped back when an ambulance sped to a stop outside the circle of spectators and parked. The surrounding crowd opened their ranks to make room for the two EMS technicians who rushed to his body with a stretcher and other equipment. He stayed with his body for the several minutes it took them to stabilize and prepare him for transport and watched them head back to the hospital, sirens wailing and red lights flashing in the night.
David eyed the back of the departing ambulance longingly, torn between following or going to his new mate.
He chose his mate.
Aziza jerked awake in her favorite corner of the sofa. The textbook she'd buried her nose in when she drifted asleep fell to the floor with a thwack. She wondered what had startled her out of her sleep until she spotted the large timber wolf standing on the threshold of her living room, staring at her.
He had azure eyes! Not that she was an expert in such things, but she had never heard of this in a wolf before, especially not so human a shade, so human an expression.
She wasn't sure how she knew the animal was a wolf and not a big dog or a coyote. There was just something too majestic and extraordinary about him to be either of those.
Where had he come from, and how in God's name had he gotten into her apartment?
Aziza shook herself, wondering whether she had conjured him from her subconscious and not that she was still asleep and dreaming or going crazy.
She had a second to question the vision and release a small yelp when the animal slowly advanced, paws surprisingly silent against her polished wood floor.
Don't be afraid. I'm not here to hurt you.
She froze and gaped at the animal.
I came to warn you. Watch your back. Your stepmother is on the warpath.
"No shit."
She immediately heard a familiar deep chuckle at this and peered when the wolf came closer.
Aziza assured herself none of this was real--the wolf was just a manifestation of her longings, an animalistic symbol of her wildest desires--even as she reached out a hand to touch him, strangely unafraid.
She expected to encounter the softness of his dense-looking pelt, palm tingling right before her hand went straight through the animal.


text: Results 1–10 of 57 for "Review"X related to "APA Center for Psychology in Schools..." Refine Your Search Refine Your Search TopicTherapy (9)Sexuality (5)Lesbian, gay, bisexual, transgender (2)Parenting (2)Trauma (2) 7 more... [+] Aging (1)Autism (1)Children (1)Death & dying (1)Race (1)Sport & exercise (1)Women & men (1)Hide detailsDocument TypeReviewXYear2013 (2)2012 (3)2011 (8)Author/ContributorRothschild, Louis (3)Stafford, Mark (3)Auerbach, John (2)Basseches, Harriet (2)Mills, Jon (2) 39 more... [+] Tasso, Anthony F. (2)Tessman, Lora Heims (2)Ahbel-Rappe, Karin (1)Anastasi, Anne (1)Bernstein, Jeanne Wolff (1)Bishop-Towle, Wandajune (1)Charles, Marilyn (1)Corn, Andrea (1)Corn, Andrea S. (1)Cushman, Philip (1)DeMattos, Susan (1)Downing, David L. (1)Goldsmith, Marcella Tarozzi (1)Hartman, Stephen (1)Helm, Fonya Lord (1)Himes, Mavis (1)Hollwitz, John (1)Kimmel, Douglas (1)Lewis, J. Scott (1)Maroda, Karen J. (1)Masling, Joseph (1)Mattson, Mark E. (1)Most, Charles (1)Nierenberg, Ona (1)Pharis, Mary E. (1)Reis, Bruce (1)Reynaga-Abiko, Geneva (1)Ridenour, Jeremy (1)Russell, Glenda M. (1)Schulman, Martin A. (1)Strenger, Carlo (1)Suchet, Melanie (1)Tabin, Johanna Krout (1)Thurer, Shari (1)Webster, Jamieson (1)Weisbard, Karen (1)White, Kathryn (1)Winn, Martin (1)Zelan, Karen (1)Hide details Results 1–10 of 57 Previous 1 2 3 ... Next Relevance Title A-Z Title Z-A Newest First Oldest First Sort by: 1.Review of "Psychological Testing" by Anne AnastasiA 1954 review of this volume described it as a consideration of the principles of psychological testing, which employs examples of tests of general classification, aptitude and achievement, and ends with measures of personality characteristics ranging from inventories through projective techniques and situational tests. Review 2.When the Body Is the Target: Self-Harm, Pain, and Traumatic Attachments (Book Review)By unraveling some of the paradoxes of self-harm, by demonstrating a successful method for dealing with individuals who engage in this behavior, Farber has enlarged the scope of psychoanalytic treatment and provided hope for an underserved group. Review 3.Toward a Psychology of Uncertainty: Trauma-Centered Psychoanalysis (Book Review)This book, about trauma and the discomfort we have with uncertainty, is grounded by case examples and personal perspective that bring her thinking alive with the experience of insight and empathic resonance.Review 4.Mentalizing in Clinical Practice (Book Review)The two books reviewed, the first edited by Jon Allen and Peter Fonagy, the second written by Jon Allen, Peter Fonagy, and Anthony Bateman, present discussions of mentalization for everyday clinicians, especially for those that have little or no interest in an approach that touts unapologetically its origins in psychoanalysis.Review 5.Handbook of Mentalization-Based Treatment (Book Review)This book is a clear and comprehensive introduction to mentalization and its relationship to psychotherapeutic practice.Review 6.Engaging Autism: Using the Floortime Approach to Help Children Relate, Communicate, and Think (Book Review)Greenspan and Wieder's comprehensive book on Autistic Spectrum Disorder (ASD) describes in detail how their "engagement" model is radically different from past and present methods of assisting autistic youth. Review 7.For And Against Psychoanalysis (Book Review)The second edition retains the remarkable breadth and scope of the original edition, while expanding and updating Frosh's examination to additional subject areas, such as the ways in which psychoanalysis has contributed to examination of social issues.Review 8.Group Treatment of Adolescents in Context: Outpatient, Inpatient, And School (Book Review)This book described as being down-to-earth and user friendly for both the analyst and non-analyst, acknowledges the sad reality that most outpatient treatment centers have undergone significant internal changes as financial reimbursements have superceded patient needs.Review 9.The Collapse of the Self and its Therapeutic Restoration (Book Review)David Downing's review describes this book, which is organized into three related progressive dialogues, as one that is bound to become an important touchstone for those interested in theory as well as clinical practice.Review 10.World, Affectivity, Trauma (Book Review)Carlo Strenger reviews the book "World, Affectivity, Trauma" by Robert D Stolorow.Review (January 2011) Previous 1 2 3 ... Next Relevance Title A-Z Title Z-A Newest First Oldest First Sort by: ADVERTISEMENT Results 1–10 of 57 for "Review"X related to "APA Center for Psychology in Schools..."


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CHARLOTTE, N.C. (AP) — The relatives of a Charlotte man who killed three family members and himself are suing the Carolinas Healthcare System hospital where he had sought treatment the night before the killings, saying his care there was inadequate.Read the full article
The Charlotte Observer reported (http://bit.ly/nsMxNj) that the family of Kenneth Chapman filed the lawsuit Thursday in Mecklenburg County Superior Court. The lawsuit argues that the 33-year-old Chapman received inadequate care when he went the mental health emergency room of Carolinas Medical Center-Randolph the night before the killings on March 16, 2010.
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Incremental Policy, Learning: An Equilibrium Selection Algorithm for Reinforcement Learning Arrents with Common Interests U Nancy Fulda and Dan Ventura Department of Computer Science Brigham Young University Provo, Utah, 84602 email: fulda@ hyu. edu, ventura@ cs. byu. edu Abstract- We present an equilibrium selection algorithm for by its countemarts) and ( 2) they all m; reinforcement learning agent; that incrementally adjusts the probability of executing each action based on the desirability of the outcome obtained in the last time step. The algorithm assumes that at least one coordination equilibrium exists and requires that the agents have a heuristic for determining whether or not the equilibrium was obtained. In deterministic environments with one or more strict coordination equilibria, the algorithm will learn to play an optimal equilibrium as long as the heuristic is accurate. Empirical data demonstrate that the algorithm is also eflective in stochastic environments and is able to learn good joint policies when the heuristic's parameters are estimated during learning, rather than known in advance. I. INTRODUCTION Learning to play an optimal equilibrium is a non- trivial task. Non- communicating agents must both determine the location of equilibria in the joint action space and learn which equilibria are enabled by the other agents' strategies. Wang and Sand-holm describe this task in terms of two interrelated learning problems: identifying the game and learning to play [ Y]. We use the phrase ngenis wirh common inreresis to describe agents whose preferences coincide in at least one point in the joint action space; that is, there is at least one joint action that maximizes expected reward for all agents. We call such a joint action a coordination equilibrium. A coordination equilibrium is strict if the system contains no joint actions that maximize expected reward for one agent without maximizing it for all other players. Coordination equilibria are a special case of opiimnl equilibria, which are defined as pareto- efficient Nash equilibria. An optimal equilibrium does not necessarily maximize payoff for all players. A coordination equilibrium does. Recent algorithms that address equilibrium selection in multiagent reinforcement learning systems include Claus and Boutilier's Joint Action Learners [ I], Hu and Wellman's Nash Q- learning algorithm [ 3], Michael Littman's Friend- or- Foe Q-learning [ 6], and Wang and Sandholm's Optimal Adaptive Learning [ Y]. The algorithms described above share two characteristics in common. ( I) They all rely on global perception of the joint action space ( i. e. each agent can perceive the actions executed assumptions about the motives of the other agents. These two characteristics correspond to Wang and Sandholm's taxonomy: Perception of other agents' actions allows the game structure to be identified, while assumptions about other agents' motives help in determining which potential equilibria the other agent is willing to play. Incremental Policy Learning ( IPL) is a novel approach to selecting between multiple coordination equilibria. This approach uses a weakened form of condition ( I ) above: The agents do not need to know the entire structure of the joint action space. Instead, they require a heuristic ( for example, the reward associated with a coordination equilibrium) that indicates whether the desired equilibrium was obtained. The heuristic information can be inferred from the joint action table if it is available, may be provided by an external oracle, or can be estimated based on known characteristics about the environment and observed individual rewards. One of IPL' s greatest advantages is that, depending on how the heuristic information is obtained, optimal solutions may be found without learning the complete game structure. In its most basic form, Incremental Policy Learning relies on condition ( 2) by assuming that a coordination equilibrium exists and by using the reward associated with this equilibrium as a parameter for the heuristic. We show in Section IV- C that this basic form can be augmented through the use of other heuristics so that the algorithm can play optimally un-der other assumptions about opponent motivations, including Nash- seekers and Minimax players. 11. RELATED WORK One of the simplest reinforcement learning techniques for selecting between multiple equilibria is to use a pre- arranged coordination mechanism such as that employed by Lauer and Riedmiller, in which the agents retain as their optimal policy the first action that successfully maximized reward [ 5]. This approach is effective in deterministic environments, but ceases to be effective when nondeterministic rewards are introduced or when the environment is unpredictable. 0- 7803- 8359- 1/ 04/$ 20.00 02004 IEEE 1121 The equilibrium selection problem can also be addressed through on- policy learning. The underlying principle is that each agent's individual utilities shift to reflect the frequency with which the agent has achieved a desirable reward, causing the agents to settle towards complementary policies in which both agents benefit [ I]. Unfortunately, agents using this tech-nique do not always settle to an optimal equilibrium. Some environments particularly those resembling penalty games) camoflauge desired equilibria so that the weighted sum of received rewards still appears less desirable than some other action. Biased exploration techniques have been utilized to en-courage convergence to an optimal equilibrium. For example, Kapetanakis and Kudenko's FQM heuristic biases exploration based on the maximum reward received for a given action and the frequency with which that reward has been observed [ 4]. This approach increases the likelihood of convergence to an optimal equilibrium in cooperative games, but does not guarantee it. Another option is to allow the agents to percieve the actions selected by all other agents. However, this augmentation destroys the power of on- policy learning as an equilibrium selection technique. Unlike typical reinforcement learners, whose utility estimates change in response to the biased exploration of their counterparts, agents who perceive the joint action space learn the same joint utilities regardless of the behavior of the other agents. The frequency with which each joint utility is updated is affected, but not the value to which the utilities converge. To remedy this problem, researchers have again resorted to biased- exploration techniques such as Fictitious Play and Optimistic Boltzmann [ I]. This results in improved performance hut does not guarantee convergence to an optimal solution. Incremental Policy Learning resembles the biased explo-ration techniques described above, with the critical distinction that IPL uses information about the optimal equilibrium to guide the search. This results in guaranteed convergence to an optimal joint policy if at least one strict coordination equilibrium exists. 111. INCREMENTAL POL. lCY LEARNING A. Terminology Let A = { a1, ..., a,} be the action selections available to an agent, and let P = { p( al), ..., p( a,)} be a probability distribution over those actions Then 0 5 p( at) 5 1 and We assume that the agents are repeatedly playing a single-stage game in which the ( external) state of the agent never changes. In any time step t, each reinforcement learning agenl executes an action a( t) E A and receives an information vector I ( t ) back from the environment. This information includes the agent's reward r( t) and may also include the action selections of other agents, the payoffs received by other agents, or othet information about the environment. The IPL algorithm uses a binary heuristic H( t) that returns a value of 0 or 1. This heuristic may use as parameters the C , p ( a , ) = 1. information vector I ( t ) , the agent's utilities ( if it is maintaining them), or any other information accessible to the agent. One of the simplest heuristics a reinforcement learning agent can use returns 1 if and only if the reward received by the agent matches or exceeds the expected ' reward associated with a coordination equilibrium, that is, if r( t) 2 T,,~. An inequality is used in addition to the equality because the maximum expected reward may he exceeded due noisy payoffs. This heuristic is used for the basic form of IPL because of its simple nature and because of the potential for inferring T~~~ from observations or from a priori information about the environment. E. Algorirhnr The basic principle of IPL is that, if the heuristic indicates that the agent's objectives were successfully obtained, then the agent increases the probability of repeating the action just executed while slightly decreasing the probability of executing any other action. This algorithm is purely policy- based; the agent's utilities have no influence on the agent's behavior unless they are used by the heuristic function. The basic form Incremental Policy Learning Algorithm functions as follows: . Initialization Vi, p( ai) = wi, where w is an arbitrarily chosen initialization vector that satisfies Cy= owi = 1 and Vi, wi > 0. Action Selection In each time step t, the agent selects an action a ( t ) E A such that pTob( a( t) = ai) = p( ai). The agent executes this action, receives an information vector I ( t ) , and updates P as described below. . Probability Updates Let H( t) = 1 if r( t) 2 rmar. 0 othemise. Let 0 < a 5 1. If H( t) = 1 then V i : if ( a( t) = ai) then p'( ai) = p( ai) + a( 1 - p( a;)) if ( a( t) # ai) then p'( ai) = p( ai) - ap( a,) The update rule used preserves the probability distribution P. Hence C i p ' ( a i ) = 1 and for all $( a;), 0 5 p'( a,) 5 1. The general form of the algorithm differs from the basic form in that the heuristic H( t) is not specified. It is intended that the general algorithm can he adapted to suit varied situations by selecting an appropriate heuristic. C. Convergence Figure 1 shows a generalized payoff matrix for a deter-minstic two player game. We will assume that the game is constrained such that it contains at least one coordination equilibrium and that all coordination equilibria are strict. This means that there exist values x* and y* such that Vi, j, x* 2 xij, y* 2 yij, and xij = x* iff y, j = y'. 1122 Suppose that we have two IPL agents, a and b, repeatedly playing a single- stage game with this payoff matrix using x* and y* as their respective T,,,~= values. Under these conditions, the agents' heuristics will always be positively correlated. Hence, if ( a,, bj) is a coordination equilibrium, then x'- 3 .= x*, yij = .' y and H( t) = 1 for both agents. If ( U,, bj) is not a coordination equilibrium, then xij < XI, yij < y'. and H ( t ) = 0 for both agents. We wish to determine whether the agents will lean to play an optimal equilibrium. We begin by noting that the combination of the agents' IPL probability distributions creates a probability distribution over the joint action space such that p( a,, bj) = p( ai) p( bj) ( 1) Each time a coordination equilibrium is played, the heuristic of both agents is satisfied and each joint action takes on a new probability p'( ai, bj) = p( ai, bj) + Ap( ai, bj) ( 2) The value to which p( a;, bj) can increase is bounded for all joint actions that are not coordination equilibria, as shown in Theorem 3.1. Theorem 3.1: If ( a;, b j ) is not a coordination equilibrium and if p ( a i , b j ) > 0.5, then Ap( ai, bj) 5 0. Pro08 We, wish to establish the conditions under which Ap( ai, bj) 5 0. Using equation ( 2) to derive Ap( ai, bj) and substituting, we obtain p'( ai, bj) - p( ai, bj) 2 0, which by equation ( I ) is equivalent to p'( ai) p'( bj) - p( ai) p( bj) I 0 ( 3) The values of p'( a,) and p'( bj) depend on the nature of the action executed by the system at time t. Let ( as, b,) he this joint action. If ( as, b,) is not a coordination equilibrium, then the IPL probabilities are not adjusted. In this case, p'( ai) = p( a,), p'( bj) = p( bj) and A ( a , , bj) = 0. If ( as, b,) is a coordination equilibrium then joint action ( a,, bj) can be related to it in three ways: They can share a row ( i = k , j # z), share a column ( i # k , j = z), or be completely disjoint ( i # k , j # 2). They cannot share both a row and a column because ( a s , b,) is a coordination equilibrium and ( ai, bj) is not. If the two actions are disjoint then p'( ai) = p( ai) - ap( ai) and p'( b3) = p( bj) - ap( bj). This means that p'( a,, b j ) < p( a;, bj). so Ap( ai, b j ) < 0. If the actions share a row or a column the situation is less clear because one term of p'( ai) p'( bj) is increasing while the 11 other is decreasing. Without loss of generality, assume ( i = k, j # z). Then p'( a;) = p( ai) + a( 1 - p( a,)) and p'( bj) = PVJj) - ap( b,). Substituting into equation ( 3) we get ( p ( a i ) + a ( l - p ( a i ) ) ) ( p ( b j ) - a p ( b j ) ) - p( ai) p( bj) 5 0 ( 4) which resolves to p( a,)( a - 2) 5 ( a - 1) ( 5) Dividing by a - 2, a negative quantity, we find that Ap( ai, b j ) 2 0 whenever p( a;) > s. The right side of the equation is maximized when a = 0, so as long as p( ai) > 0.5, A ( a i , bj) 5 0. The above proof demonstrates that the system can never converge to a solution that is not a coordination equilibrium: whenever the probability of a suboptimal joint action is greater than 0.5, it will decrease on the next update. We also notice an interesting phenomenon. In equation 4, the value p( bj) exists in all multiplicative terms and factors out of the calculation. Thus, if a suboptimal joint action ( a i , b j ) shares a column with a coordination equilibrium, the sign of Ap( a;, b j ) depends only on the value of p( ai). Let us now consider the case where ( ai, bj) is a coordination equilibrium. In this case we find that there is some critical value of p( ai, bj) beyond which Ap( ai, bj) is always positive. Theorem 3.2: If a system contains at least one strict coor-dination equilibrium and at least one joint action that is not a coordination equilibrium, then 3p* such that if p ( a i , b j ) > p' then p( a,, bj) is more likely to increase over time than to decrease. We wish to determine under what conditions Ap( ai, b j ) > 0. In order to do so, we examine two types of update situations. Since ( a,, bj) is a coordination equilibrium, p( ai) and p( bj) will increase each time it is executed. When some other coordination equilibrium ( as+, b,+ j) is executed, p( ai) and p( bj) both decrease. To reflect these situations, we define Pro08 p-( ai, bj) = ( p ( a i ) - a p ( a ; ) ) ( p ( b j ) - 4 b j ) ) ( 7) Let p( c) represent the probability that the executed action is some coordination equilibrium other than ( a;, b,). Then the value of p'( a,, b j ) can be probabilistically described as a weighted average of the above possibilities, using p( ai, bj) and p( c) as weighting factors. When p'( ai, bj) - p( a;, b j ) > 0, Ap( ai, b j ) is positive. We therefore seek the conditions that satisfy 23 We note that the term p( c) p-( ai, bj) is somewhat pes-simistic, since the executed coordination equilibrium might share a row or column with ( a i , b j ) . In this case, either p( ai) or p( bj) would increase, rather than decrease. However, these cases only improve the chance that the inequality in equation ( 8) will be satisfied. We therefore assume the worst-case scenario that the executed coordination equilibrium shares neither a row nor a column with ( a,, bj). After substituting from equations ( 6) and ( 7), equation ( 8) can be reduced to j In the worst- case scenario, p( c) = 1 - p( a,) p( b,). In this case, equation ( 9) can be simplified to p( a,) + p( b,) > 2; an impossible condition. However, p( c) = 1 - p( ai) p( bj) only if all joint actions are coordination equilibria, which defies the premises of the theorem. We quickly see that for any value of p( c) = 1 - p( a;) p( b,) - E, where 0 < E < 1 - p( ai) p( b,), then equation ( 9) resolves to : which is not an impossible condition. There are values of p( a;) and p( b,) that will satisfy it, even though they may be high. Thus there exist critical values for p( ai) and p( bj) ( and correspondingly, for p( ai, b,), beyond which Ap( a;, b j ) tends to he positive. We can now proceed to examine the overall system behavior. By Theorem 3.2, there exists some critical value p' beybnd which p( a;, bi) tends to be continually increasing. The greater the amount by which p( a,, b j ) exceeds this threshhold, the less likely it becomes that p( ai, b j) will decrease. The threshhold effectively represents the point at which a single coordination equilibrium dominates all other possibilities and begins to be executed with steadily increasing frequency. With continued positive updates, p( ai) and p( bj) converge towards 1 ( because the iterative series z' = z + cy( 1 - z) converges to 1 for 0 < a 5 1). Consequently, p( ai, bj) also converges to 1. Getting the ball rolling on this convergence issue may take a while. If p' is relatively high, then it may take many iterations before the probability of one of the coordination equilibria happens to reach it. Fortunately, we have a guarantee from Theorem 3.1 that no suboptimal equilibrium can maintain a probability greater than 0.5, so there is no risk of converging suboptimally while waiting for a coordination equilibrium to dominate. In the degenerate case where all joint actions are optimal, the agents will, of course, also play optimally, even if their probabilities never converge. IV. ALGORITHMBE HAVIOR Most environments are not conveniently deterministic, and most heuristics are not 100% accurate. How does the IPL algorithm perform in the face of such uncertainties? 11 Fig. 2. IPL performance as a function of noise A. Noisy Rewards Figure 2 shows algorithm performance as a function of noise. Two IPL agents, each having five actions, repeatedly played a single- stage game until they executed the same joint action 50 times in succession. Each cell of the payoff matrix was randomly initialized to an. integer between 0 and 24 ( different random payoffs were assigned to each agent), with the exception of 5 randomly placed coordination equilibria whose payoff was 25 for both agents. Gaussian noise was simulated using Peitgen et. al's equa-tion [ 2]: Using values A = 100 and n = 50. The result D was multipled by a scaling factor of S to provide different degrees of noise. The value SD was added to the agents' reward signals. The agents used T~~~ = 25 and a = 0.1, and the results of 100 trials were averaged for each data point. We found that even for very large values of S with respect to the range of possible rewards, the IPL algorithm was able to focus in on a near- optimal solution with reasonable frequency. B. Estimation of T,,,~= A critical question for IPL is ' how the algorithm performs when the value of T~~~ is not known in advance, but must instead be inferred from known information. We implemented a set of Q- leaming agents who were each able to observe the action selections of the other agents. The agents used an initial utility value of 0, a learning rate 9 = 0.1, and a simplified joint Q- value update equation &'( ai, b j ) = ( 1 - q) Q( ai> bj)+ q ( ~ ) ( 121 where &( ai, bi) is the estimated utility of performing joint action ( a;, b,) and T is the reward received for executing joint action ( a,, b j ) . 124 Fig. 3. IPL performance as a function of a with rmor estimation. Scaling factor S = 0 was used for the deterministic environment, S = 5 for the stochastic environment. In each time step, each agent estimated T , , , ~ ~ = max;, j Q( a,, bj) and exceuted the IPL update equation. Payoff matrix generation and noise generation were carried out as described in the previous sub- section, and the results of 100 trials were averaged. The results are shown in Figure 3. As one might expect, IPL performance was better with lower values of a. This is not surprising, since a high value for cy might cause the IPL algorithm to converge before the joint Q- values accurately reflected the relative magnitude of the expected rewards. C. Extensions of the Algorithm The IPL algorithm lends itself naturally to several possi-ble heuristics. Here, we discuss only a few of those which intuitively appear most useful and which seem to reflect other results obtained in the field of multiagent reinforcement learning. If agents have access to the full payoff matrix of the game being played ( either because it was provided a priori or because they have inferred it by watching the action selections and rewards of other actions), then they can determine whether a given joint action represents a Nash equilibrium. By letting H( t) = 1 if the executed action was a Nash equilibrium and H( t) = 0 otherwise, the agents can select between multiple Nash equilibria. Similarly, agents interacting in strictly adversarial envi-ronments can learn to play a Minimax strategy byletting H( t) = 1 if the executed joint action is a Minimax solution and H( t) = 0 otherwise. Naturally, both of these approaches require that the agents be able to see the action selections of their counterparts, and also rely on the assumption that all agents in the system are using the same heuristic. One potentially interesting application of the IPL algorithm is in satisficing environments. In satisficing, agents seek ac-tions that are " good enough" rather than seeking actions that are optimal 171, [ SI. A satisficing criterion could be chosen ( such as a threshhold value for T,) such that H( t) = 1 whenever the criterion is satisfied. In this way, the agents could select between multiple satisficing solutions. v. CONCLUSIONS AND FUTUREW ORK We have presented an equilibrium selection method for agents that are able to determine with reasonable accuracy whether or not an optimal equilibrium was obtained in the last time step. When heuristic information is provided by an external source, the algorithm is able to search through policy space directly, without learning ut the actions of other agents. When the heuristic information rred or approximated based on observed rewards, and observation of the complete action space may be useful tools for the acquisition of good heuristic data. Incremental Policy Learning provably learns to play an optimal solution if the heuristic is accurate, the environment is deterministic, and at least one coordination equilibrium exists. Empirical studies indicate that IPL performs well in the presence of noise and when the heuristic information is approximated rather than precisely known. Future work should concentrate on theoretical bounds on the effectiveness of such methods, as well as on an analysis of the effect of the joint action space size on convergence speed. Because IPL updates only when the heuristic's requirements are satisfied, convergence may take a very long time in large joint action spaces with sparse equilibria. Compounding this problem, if the environment is noisy and the joint action space has several near- optimal solutions, the agents may learn IO play one of these before a true optimum is discovered. Both of these problems might be alleviated by adding a decay factor such that the probability of an action's execution decreases each time an optimal solution is not found. This would encourage more uniform exploration of the joint action space. Finally, other possible heuristics and methods for approx-imating them should be developed so that the algorithm's usefulness can he expanded to new situations. REFERENCES [ I] Caroline Claus and Craig Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In AAAINAAI, pages 746- 752. 1998. [ 2] H. Jurgens H. 0. Peitgen and D. Supe. Chum and Frncrols. Springer- Verlag, New York. 1992. [ 3] J. Hu and M. Wellman. Nash q- learning for general- sum stochastic games. Joumol ofMachim Learning Research. to appear, 2003. [ 4] S. Kapetlnakis and D. Kudenko. Improving on the reinforcement leaming of coordination in cwperative multi- agent systems. In Second AISB Symposium on Adoptive Agent.$ and MulriGAgent Systems, 2W2. [ 51 Marun Lauer and Manin Riedmiller. An algoithm for diswibuted rein-forcement learning in cooperative multiLagent systems. In Proceedings of the 17rh Inremtioml Conference on Machine Learning, pages 535- 542. . San Francisco, CA, 2000. Morgan Kaufman. [ 6] Michael Littman. Friend or foe q- learning in general- sum markov games. In Proceedings of the Eighreenth Inrermriowl Conference on Machine ~ e ~ r n i npga. g es 3 2 2 - 3 2 8 , 2 ~ 1 [ 7] H. A. Simon. A behavioral model of rational choice. [ 8] W. C. Stirling, M. A. Goodrich, and D. J. Packard. Satisficing equilibria: A non- classical approach to games and decisions. Auronomous Agenrs and Mulri- Agenr Sysrems Journal. 5: 305- 328. 2002. [ 9] X. Wang and T. Sandholm. Reinforcement learning to play an optimal nash equilibrium in team markov games. In Advonces in Neural Informorion PWC~ S@ Sysrems IS ( NIPS- 2002). Vancouver, 2W2. 1125
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A medical license is required for a doctor to practice medicine in a particular state. Requirements vary by state but most require, at a minimum, post-graduate training in the doctor's specific specialty. An NPI number is a national identifier unique to an individual health care provider and is managed by the Center for Medicare & Medicaid Services (CMS).
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Product Code: 42794
For removing grout from between wall and floor tiles. Features easy depth adjustment and guide to keep bit centred between tiles to reduce the risk of chipping.
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Angled cutting guide and 1.6mm grout removal bit.
Shank dia: 3.2mm. Working dia: 1.6mm Max. 20,000rpm.
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Tommee Tippee Closer To Nature Complete Starter Kit
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Tommee Tippee CTN Electric Steriliser Kit
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3 reviewsFast and efficient slim line electronic steriliser with digital display to show the progress of the 5-minute cycle. Provided the steriliser stays closed, will also show a countdown of how long the bottles will remain sterilised. Comes apart for easy de-scaling and cleaning, BPA Free.
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Elected as a Democrat in the November 5, 2002 General Election, the Honorable Sylvia Laughter changed her party affiliation to Independent on February 14, 2003. (Journal of the House of Representatives, 46th Legislature, 1st Regular Session, 2003, p. v; Chip Scutari. "Political Insider." The Arizona Republic, February 20, 2003, p. B4; "Correction." The Arizona Republic, March 8, 2003, p. A2). The following is from ALIS for the 46th Arizona State Legislature, 2nd Regular Session (2004):
Sylvia Laughter Independent District 2 House of Representatives 1700 W. Washington Room 312 Phoenix, AZ 85007 Phone Number: (602) 926-5862 Fax Number: (602) 417-3102 Email Address: email@example.com Home City: Kayenta Member Since: 1999
Representative Sylvia Laughter
Sylvia Laughter, a Navajo Indian, is from the heart of the Navajo Nation: Baby Rocks, Arizona. Sylvia earned a bachelor's degree in Broadcast Communications with a minor in music from Brigham Young University in Provo, Utah, in 1993.
Ms. Laughter, re-elected in November 2002, will be serving her third term in the Arizona House of Representatives for Arizona's largest district, Legislative District 2, covering northern Arizona. Sylvia represents a district that includes the largest Native American tribe in the United States, and she is the first Navajo woman to serve in the State Legislature from District 2.
Ms. Laughter has served on the board of American Indian Services since 1990. She also currently serves on the advisory board of the Institute for Native Americans at Northern Arizona University. Sylvia is on the planning board for the Native American Women's Business Council.
In her previous term, Ms. Laughter was instrumental in creating the House committee on Native American Affairs, which she co-chaired. She is currently serving as a member of the committees on Federal Mandates and Property Rights, Natural Resources, Agriculture, Water and Native American Affairs and also on Appropriations.
It has been Ms. Laughter's commitment to first represent the best interests of her district, while also working towards the best interest of the state as a whole. in her two terms as a legislator, Ms. Laughter has been successful in working with her colleagues to secure more than $20 million in education funding for her district, as well as for the seniors and veterans of the community.
Ms. Laughter has co-sponsored the successful passage of bills addressing issues of domestic violence, managed care, water and social issues. It is her continued goal to address these issues as well as those of taxation, economic development, energy, and education while in her capacity as State Representative. 50th Legislature, 1st Regular Session, SR 1002 Native American legislators; recognition: Sylvia Laughter, Navajo, 1999-2004
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HES1299 Features: -Recliner.-Leather faced recliner.-Features high back and padded headrest for extra support and sit up comfort.-Easy finger pull mechanism for conversion to comfortable recliner mode with footrest.-Foot extension: 43.18 cm. Color/Finish: -Black finish.
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Meditation & Health
Tricks of the body
What Happens to Your body if you stop smoking Right now? When you were 9, playing your armpit was a cool trick. Now, as an adult, you can still appreciate a good body-based feat, but you're more discriminating.It seems everyone is interested in meditation...talking about the wonderful benefits, recommending classes and discussing the different ways to "do it". But, for a beginner, just what is "it"? And how do you do "it"?
Spirit Vaults : Meditation - Essay
Meditation Supplies
Most people only think that there is one way to sleep: Go to sleep at night for 6-8 hours, wake up in the morning, stay awake for 16-18 hours and then repeat.


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Twitter gadfly and NBA legend (in order of nerd culture import) Shaquille O'Neal is sitting in front of his computer and pouring his heart out for you.
Two videos were uploaded today that feature Shaq lipsynching to Rick James' "Fire and Desire" and Aaliyah's "At Your Best." Give the guy a web show already.
All I'm taking away from these videos is that dude has a gigantic mouth. Also, that his house is equipped with a drainage system in every room for when Shaq feels like cooling off with a bottle of Evian.
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Shaq Sings Rick James, Aaliyah (The One)
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Rhea Hill
04/21/2013 Rebels Close Out Stay In Southern CaliforniaUNLV track & field witnesses 10 student-athletes set personal bests in seven events Saturday. 04/13/2013 Rebels Run Their Way To Seven WinsUNLV claims seven wins on the track, 17 top-three finishes on second day of Cunningham Invite. 03/31/2013 Rebels Close Out Cal-Nevada ChampionshipsAdrianna Oliva finishes eighth in the shot put. 03/27/2013 Rebels Split Up For The WeekendUNLV track & field will have members participating in meets hosted in Austin and San Diego. 03/24/2013 Oliva, 800m Relay Take First In PasadenaUNLV had 19 individuals, two relays finish eighth or better at the Pasadena Games. UNLV: Listed in the outdoor performance list ... Listed as a member of the outdoor distance medley relay team (second) ... A one-time Academic All-Mountain West Team member (2012). 2012: Ran in four outdoor meets ... Participated in the 400m (four times), 4x400m relay (three times) and distance medley (once) ... Fastest 400m time was 1:01.3 at the Cunningham Invitational ... Fastest 4x400m relay time was 3:56.69 at the Steve Scott Invitational ... Ran the distance medley in a time of 12:26.73 at the UNLV Classic ... Ran in two indoor meets ... Participated in the 4x400m relay (twice) and 400m (once) ... Fastest 4x400m relay time was 3:57.8 at the NAU Invitational ... Ran the 400m in a time of 1:01.69 at the Mountain T's Invitational. High School: A 2011 graduate of Rancho Cucamonga HS in Rancho Cucamonga, Calif. ... Lettered twice in track & field ... Helped the Cougars to two Baseline League team championships in 2008 and '11 ... Team finished second in the Mojave River League ... Earned scholar-athlete honors and was a member of the principal honor roll ... Ran club for Together Elite. Personal: Rhea Nicole Hill was born on May 9, 1993, in Pomona, Calif. ... The daughter of Aaron and Dawn Hill ... Has three siblings: Nastashia, Shakira and Aaron ... Cousin, Torri Edwards, ran on the USA Track & Field team ... Majoring in business. |


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Petr Nedved's ex-wife Veronika Varekova
Tweets by @czechsterVV
I love this girl Veronika Varekova. I've never seen here before, but I am in love with her as of right now.
Wowwww! Who left who? Hopefully not him. I would deal with whatever I needed to be with a women like her. Just sensational. Seems like all the beautiful girls have the most problems. After all, she could have any man she wants. That's probably the problem and being rich helps.
The pictures of her are hot, but to see her in person, leaves allot to be desired….
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Patty Loveless
Patty Loveless
The Patty Loveless Collection
Original Release Date: October 10, 2006
Track Listing
1. Blue Side of Town
2. I Won't Gamble with Your Love
3. Go On
4. If You Think
5. Chains
6. Don't Toss Us Away
7. The Lonely Side of Love
8. I'll Never Grow Tired of You
9. Timber I'm Falling in Love
10. I'm on Your Side
11. Overtime
12. The Night's Too Long
13. Blue Memories
14. Some Morning Soon
15. You Can't Run Away from Your Heart
16. On Down the Line
17. I've Gotta Stop Loving You (And Start Living Again)
18. Looking in the Eyes of Love
19. I'm That Kind of Girl
20. Feelings of Love
Matraca Berg: Composer
Patty Loveless: Composer
Lucinda Williams: Composer
Karen Brooks: Composer
Wendy Waldman: Composer
Claire Lynch: Composer
Tony Brown: Producer
Hank DeVito: Composer
Paul Kennerley: Composer
Kostas: Composer
Bryan MacLean: Composer
Jim Photoglo: Composer
Bud Reneau: Composer
Gary Scruggs: Composer
Carter Stanley: Composer
Tricia Walker: Composer
Jimbeau Hinson: Composer
Kim Tribble: Composer
Hal Bynum: Composer
Ronnie Samoset: Composer
David Alter: Executive Producer
Alexandra de Castro: Production Coordination
Mick Stevanovich: Executive Producer
David Roy: Liner Notes, A&R
Glenn Roskein: Product Development
Brenda Bedard: Creative Director
Larry Lynch: Composer
Laura Guzzo: Copy Editing


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Queensbridge Archives
July 4, 2013 3:28 pmNike Pro City Week 4 Recap
TNP wins in double overtime, while Dyckman cruises past Primetime.
December 19, 2008 9:03 amQuiet Storm
A Q + A with former NBA player Sean Green.
View all »- Kobe Bryant Says Knee Rehab Has Been Slow (VIDEO)
- Joel Embiid Out of Big 12 Tournament, Maybe Longer With Back Injury
- N.C. State's TJ Warren Wins ACC Player of the Year Over Jabari Parker
- New York Knicks to Reportedly Hire Phil Jackson This Week
- Andrew Bynum to Make His Pacers Debut Tonight
- Kyle Korver Says a Coach Offered His Team Money to Stop His 3-Point Streak
- Sixers Not Confirming Nerlens Noel April 4 Debut
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- Karl Malone Proud to Still Use a Flip Phone (VIDEO)
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August 25, 2011
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Finely grind 1 cup pistachios and 1/4 cup sugar in processor. Bring milk and ground pistachio mixture to boil in heavy large saucepan. Remove from heat. Mix in almond extract. Whisk egg yolks and remaining 1/2 cup sugar in medium bowl. … see full wiki


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How I Met Your Mother Review: "Blitzgiving"
by Chris O'Hara at .How I Met Your Mother's Thanksgiving episode was for the birds - and I'm not talking about a "Tuturkeykey."
Jorge Garcia tried valiantly to make a memorable guest appearance, dropping gems such as Kraft and Croft night and double rainbows. Unfortunately, little worked.
The Lost references, like the use of the infamous numbers (4, 8,15,16,23, and 42), fell short and lacked punch, much like the nod to Ferris Bueller's Day Off, which followed the gang getting stuck in the Thanksgiving Day Parade.
To makes matters worse, Zoey was back. Ah, man!
There were a few moments worth noting, though:- Barney in the back of the cab as he tried to pronounce his driver's name, "Babbaka."
- Robin falling for Wang Guy based solely on a picture of his "junk."
- Barney, completely out of context and clearly agitated, admitting to sleeping with the "hot Indian girl" who cut his hair simply because he had forgotten to brag about it earlier.
The main question of the episode - can enemies ever be friends? - was a good one. It was no doubt a nod to Ted and Zoey getting together, but was this surprising to anyone? Zoey is unhappy in her marriage; not exactly a news flash, right? I mean, they shot Kennedy, too. The show's creators used a typically festive and hilarious episode to weave their silly web of Ted's wife a little further. What happened to Slapgsiving? I guess Marshall just put tradition on hold for a year?
As I watched yet another disappointing holiday episode (See "Canning Randy"), I'm sure I missed some legendary television moment on another channel. While I ended up feeling like I was the Blitz, I fear our beloved show might find itself sacked if it keeps dishing out stuffing like this week's episode.
The best part of Thanksgiving is leftovers, and while I won't be going back for seconds of this episode anytime soon, there were a few tasty quotes to give thanks for and revisit:
Ted: Who canceled, your coven?
Steve: Coven, group of witches, boom! | permalink
Zoey: Barney was here? I was walking around half naked.
Barney: Aw Man! Wait which half? | permalink
Lily: It's a booma-wang.
Robin: Nice,
Lily: Thanks.
Robin: No I meant the wang. | permalink
Barney: Robin! Robin! I will pay you to be the Blitz. A hundred dollars, no! Ten thousand dollars, no! Sixty bucks. What's a lot of money to someone like you? | permalink
Robin: I think the smaller turkey just tried to crawl further inside the bigger turkey. | permalink
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23 Comments New Comment Subscribe
They were two cheezy LOST references and obvious ones. I guess Garcia is going to have to tough these things out for a year or so, but after that I'd suggest he put a moratorium on them. The Ferris Beuller references were way funnier, because the movie has had time to mellow into a small classic. I liked the ep mainly because there was so much movement in it. They were all over the place. There were several sets, and they do this for a studio audience, so they had to pile into that cab all those times in sequence. good times.
My favourite line of the night was Barney realizing, in all the conusion, he hadn't taken credit for a one night stand...Funny stuff.
you have GOT to be kidding me! why is that every time HIMYM makes an episode the reviewer doesn't like, he thinks the show will be cancelled? one, the show was funny, and two, even if it was a little disappointing, every show EVER has a disappointing show every now and again. i feel like the reviewer kind of wants this show to be cancelled.


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Just bought Jessie J tickets for brighton centre for my daughters birthday. She will be thrilled as got front row tickets looking over stage.
Double 8 are brilliant always get the best seats and the costomer service is brilliant,.
Tickets arrived two days after ordering by special delivery.
have recommended to all my friends. Will deffo use again.
Keep up the good work Double 8.
Got One Direction Tickets from Double 8 tickets, they arrived when promised and went to see them on 23rd February. Got 5 rows from front and really felt part of the concert, would deffo use again AND recommend to anyone who wants good seats. Well done Double 8 for a fantastic service.
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Philips home theater & Blu-ray player with Smart TV offer you an array of enhanced features, including Net TV, SimplyShare & MyRemote. Net TV brings a wide range of online information & entertainment to your TV for services like video-on-demand. With SimplyShare, you can access photos, music & movies stored on your PC from the comfort of your couch. You can also use your smartphone/tablet to control your home theater via Philips MyRemote app.
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Spice & Spirit, The Book of Jewish Food: An Odyssey from Samarkand to New York
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Babylon 5: War Without End Version 1.0
Nov 23, 2013 Full Version 23 commentsThis is the mod in its current state packed into a .big archive for ease of use. It's also much smaller then the SVN version. It's a self-extracting archive...
This mod aims to bring strategic combat to the Babylon 5 universe.
We'll start off with the Earth Alliance vs. the Minbari and go from there once we have those two complete factions.
The mod is being developed using a SVN repository. We have made this repository open to the public so you can download and experiment with the mod while its being developed. Instructions for downloading can be found in our files section.
4 comments by Zeelich on Feb 16th, 2013
Afternoon all, it turns out that the SVN information I put up on the website is out of date and as a result uses the wrong address. I've updated the URL and changed the step-by-step guide to make it a bit easier to understand/follow.
The updated instructions are here: B5wwe.sourceforge.net
The new URL for the SVN is: Svn.code.sf.net
Sorry I didn't notice this sooner everyone. If you are using the old URL I suggest a fresh checkout. However, if you are low on quota than you can use the 'relocate' option by right clicking the top folder (Usually something similar to B5WWE or Homeworld2_B5) -> TortioseSVN -> relocate and replacing the URL with Svn.code.sf.net
Don't fear the quite people. Im still working on balancing the MOD and working on the AI. I've been using the B5Wars Role Playing game as a base in an attempt to create some consistency between the races, so far it's looking really good.
If you have any SVN problems feel free to post a comment or to ask on the RelicForums, good luck everyone.
This is the mod in its current state packed into a .big archive for ease of use. It's also much smaller then the SVN version. It's a self-extracting archive...
This is intended as a modder's resource, not a complete mod. This is a pack of the megalith models included with Homeworld 2, updated to look correct...
This is a small set of scripts and objects that can be used by advanced HW2 modders to pass arbitrary numerical data between the .level files and the...
please say the final thing won't be availiable by svn alone. it looks sooo amazing!!!!!!!!!
The SVN version is our development version. Once we get the EA and Minbari races completed (models and balancing) we'll release version 1 as a self installing file and/or a Homeworld2 .BIG file.
That's true, and I can also add that if we do a self-installing version, it won't be the only way to get the mod. I've always found it limiting to have the mod dictate how it installs itself, so at the very least a big version will also be available at that time.
Sounds greeeeat! I remember complaining about the SVN thing at first too. Way back though.
For some reason GRBackPro Service doesnt like this mods files and wont copy them for a ghost each night. Its quite frustrating ; /
Vidmaster is proud to see that this B5 mod is still alive and even better, alive and kicking :-)
hey I am trying to add a new race to the warlords mod and I can't figure out how to make it work it keeps crashing. can anyone help me please?
I think you're posting this in the wrong place. Try asking for help on the relicnews forum, found here: Forums.relicnews.com
Thank you!
Another thing is if I have the shaderless version on one machine and the shiny shiny shader-ed version on another will they be able to play together in multiplayer?
I'll be experimenting myself of course but I thought i'd still ask ^_^
IIRC, the -forceLAN command line switch, as seen on this page: Hw2wiki.net should force the two computers to connect, even if it would lead to synchronization problems, which it shouldn't in itself do, since the change is purely cosmetic.
Once more, thank you!
Deleting the shaders file worked and it didn't connect in multiplayer, i'll try the forceLAN command line next. Keep up the great work guys! In the mod and in the community :)
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A Group Effort
Rally up the troop and get ready to look awesome for this year's Halloween bash. From DIY to ready and waiting to be purchased, these group costumes are sure to be a hit.
Like itPhoto credit: Keep FunnyThe totally obsessed social media-ites will love to go as their favorite site. Use an iron to transfer the logo or use your artistic skills to recreate the logo on a T-shirt. Go for the gold by adding "likes," "hashtags" or your very own group handle, and by constantly taking selfies all night long. 2
The bee honey and his hivePhoto credit: ZinkeWhether or not you have a baby, this bee costume is great for a trio. DIY your bee costume with a black and yellow outfit, create the bee keeper's outfit with some coveralls and tulle, and make the bee hive using foam piping and twine. Put the three together and you'll have costumes people will be buzzing about until next year. 3
Rock, paper, scissors... I win!Photo credit: Costume WorksSolve any disagreement at this year's party by going as rock, paper and scissors. Another costume idea perfect for a trio, the scissors and paper are made out of painted poster board, while the rock is constructed of tulle. Randomly play a game with each other for a few laughs. 4
Latte, pleasePhoto credit: PinterestHave a group of Starbucks junkies? Go as your favorite lattes! Using a white dress (or shirt, if you feel more comfortable), enlarge the logo on your computer, adhere it using an iron-on transfer, and display your drink and name with a Sharpie. Make steaming noises and randomly tip over, just like a real latte would. 5
S'more of thatPhoto credit: Summer Camp CultureCreate a costume that the group can enjoy once the party is over with this s'mores creation, which is great for a group of five. Two can be the graham crackers with cardboard cutouts, while one is in all white as a marshmallow, another is the fire in red, and last but not least, one is the chocolate bar with a candy bar headband. Just make sure that you don't eat your sweets before the night is over. 6
Hipster princessesPhoto credit: Suburbs of UtopiaInspired by the princess Instagrams and Pinterest memes, this blogger and her lady friends laced up their boots and created a few tutus to resemble a couple of hipster Disney princesses. This is an easy costume — you can wear your favorite princess's colors with a flannel cover-up and dark-rimmed glasses for the full effect. Up next: Group costumes you can purchase >> |


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Penn State tickets Football
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Redd, Hill and the residuum of the Nittany Lions are essay to defy anopposite breezy time period after former FBI Director Louis Freeh's research of the Jerry Sandusky nestling activity ill-usage dirt reasoned out that Paterno and three opposite upper educational institution skilled workers hid accusals against his former en garde coordinator.Most Nittany Lions, before a player-organized foundation case Friday, uttered they maden't observe the group discussion Thursday about the probe, but had leastways perceived of the findings.


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Chargers quarterback Philip Rivers leaves game against Titans | |
Written by Admin |
Sunday, 09 December 2007 09:22 |
NASHVILLE, Tenn. (AP) -San Diego Charges quarterback Philip Rivers left Sunday's game against the Tennessee Titans, limping off the field after taking a blow to his knees from a Titans lineman in the second quarter. Rivers handed the ball to LaDainian Tomlinson, rolled out and was clipped to the ground. He tried to walk off the field, nearly falling on his way to the sideline. Rivers headed to the locker room, and was replaced by Billy Volek. No immediate update on Rivers' status was announced. |


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Saskatchewan Vacations - Travel guide to Saskatchewan accommodations and vacation packages. Visit Saskatchewan for getaways and adventure travel. Plan your Saskatchewan vacation today.
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Lanigan, Saskatchewan Hotels & Resorts - Lagana Hotel is located in Lanigan -the heart of the potash mining area. (Near BHP Jansen and PCS Lanigan Division.) Our newly renovated guest rooms provide comforts of home. We promise the most comfortable stay at budget rates in the region.
North, Saskatchewan Campgrounds & RV Parks - Saskatchewan Accommodation: Campgrounds/RV Parks
North, Saskatchewan Fishing Trips - Minor Bay Lodge & Outposts, a deluxe, American-Plan, fly-in fishing lodge, offers the ultimate in catch & release angling for Monster pike, lake trout, walleye and Arctic grayling in a pristine wilderness setting. Maximum only 18 guests per trip.
Maple Creek, Saskatchewan Hotels & Resorts - 34 Spacious Rooms, Wireless high speed internet-free , Cable TV, Air conditioning, fridge, laundry facility,Huge free Car Park space . Just 5km South of the Trans-Canada Hwy, and 30 minutes driving to Cypress Hills Interprovincial Park.
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Saskatoon, Saskatchewan Bed & Breakfasts - Enjoy the comforts of home across from the University of Saskatchewan and steps from the Meewasin River Trails ... fully equipped kitchens and tastefully decorated rooms make this your place to stay when visiting Saskatoon. Free wireless Internet.
Regina, Saskatchewan Hotels & Resorts - Regina's historic landmark, located downtown, overlooking Victoria Park. Within 10 minutes of the Regina International Airport. The elegant accommodations and gracious service complement Cortlandt Dining Room, Victoria Tea Room, and Monarch Lounge.
East, Saskatchewan Hotels & Resorts - Welcome to the Best Hotel in Saskatoon, Saskatchewan Our downtown Saskatoon hotel near Midtown Plaza has recently undergone a $5 million renovation in celebration of its 25th anniversary. All of our 291 guest rooms now feature LCD TVs with high def
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Food and Beverage Manufacturers Key Terms
Learn the terminology associated with food and beverage manufacturers
Food and beverage manufacturers help to keep food on our tables. If you are just getting started in this profitable industry, you may be confused by all of the new terminology. However, learning these new words is a key to your success, such as modified atmosphere packaging, air curtain, and SKU. Once you know the basics, you'll feel more confident working in the industry.Store brand vs. national brand
Air curtain
An air curtain is used in warehouses as a buffer zone between storage areas of two different temperatures. It helps to ensure that hot air doesn't enter a refrigerated space. This is essential for manufacturers that make and store different types of products.Modified atmosphere packaging
Modified atmosphere packaging helps to extend the life of perishable goods. If your company produces items that can "go bad" after just a few days, you'll want to consider this type of packaging.Stockkeeping unit (SKU)
Stockkeeping units, or SKUs are used by manufacturers, warehouses, and retailers to keep track of their products. It's an alphanumeric number that is registered in their computer database.Hazard Analysis and Critical Control Point (HACCP)
Hazard Analysis and Critical Control Point, or HACCP, is an effort to control food safety by the U.S. Food and Drug Administration. Efforts must be made to control potential hazards in food, such as microbes, toxins or glass. HACCP offers guidelines.Food and Drug Administration.
Private label foods
Private label food manufacturers produce food products, but allow companies to put their name on the label. Some private label companies will also produce a product based on the customer's recipe.Copyright © 2014 Business.com, Inc. All Rights Reserved.
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