Sagee Ben-Zedeff is an entrepreneur and a researcher in the fields of visual communications, video streaming and quality of experience, as well as social networks and interest graph based recommendation systems. He is the co-founder and CEO of Serendip Media, a Tel-Aviv, Israel based startup, building a music interest based social network for music streaming. Before Serendip Sagee was Director of Innovation and New Technologies at RADVISION. Sagee holds a B.Sc. in Computer Science and Statistics and Operations Research from the Tel-Aviv University. Follow him on http://www.twitter.com/sageeb, and subscribe to his blog http://blog.sagee.bz.
Selected topic: Sagee's current research focus is on music interest-based social networks, i.e. social networks that evolve around individuals' music interests, allowing similar individuals to easily find similar individuals and communicate with them.
Keywords: Social Networks, interest-based networks, streaming.


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26 Apr, 2021 15:50
Bluejay announces maiden drill programme at Enonkoski
Greenland and Finland-focussed exploration and development company Bluejay Mining announced the maiden drill and field programme at the Enonkoski nickel-copper-cobalt project in eastern Finland on Monday, with its joint venture partner Rio Tinto, as part of the joint-venture & earn-in agreement.
The AIM-traded firm said a diamond drill programme, targeting 3,000 metres, was scheduled to start next month.
It said the programme would test several geophysical targets in the Tevanjoki and Laukunsuo areas for mineralisation within the Enonkoski project area.
The targets were supported by base of till nickel anomalies, as well as historical observations of mineralised noritic outcrops and boulders similar to the rocks found at the rock package at the nearby former Laukunkangas nickel-copper-cobalt mine.
Drilling result assays would be conducted by ALS, and evaluated by the joint venture partners.
A detailed unmanned aerial vehicle magnetic survey over an area south east of the past-producing Laukunkangas mine was completed in mid-April.
The newly acquired magnetic data was currently being processed and interpreted ahead of the drilling.
Additional exploration activities within the Enonkoski project area were planned for the summer and autumn of 2021, the board added.
It said all exploration activities were being conducted with "strict" Covid-19 protocols in place.
"Our collaborative work with the Rio Tinto team involved in the project is progressing well, and investigations have led to some appealing near-mine targets that will now be tested through drilling," said chief executive officer Bo Møller Stensgaard.
"While entering this initial drilling, the evaluation of other high potential areas of the more-than-15 kilometre-long Enonkoski project area will continue.
"While Bluejay's focus and resources remain on progressing the Dundas ilmenite project to construction and production, I am pleased with the Enonkoski joint venture programme unfolding in the background."
Møller Stensgaard said the drilling programme was an "important recognition" of the quality of the company's project portfolio, in both Greenland and Finland.
"There remains a high level of interest in many of our battery metal projects and we remain confident in advancing those further for the benefit of our shareholders.
"We look forward to updating the market with the results at Enonkoski and further information on the progress at our other assets in due course."
At 1406 BST, shares in Bluejay Mining were down 2.57% at 8.9p.

redpajama_set_name: RedPajamaCommonCrawl


Arrived at boat yard at 05:05 and set off out off Salcombe Estuary with Banger, a local boat builder, engineer, and local Fire brigade member.
We enjoyed the flat calm of the estuary before hitting the strengthening easterly that made the chop quite uncomfortable as we searched for third placed boat BOUDICA with team Oarsome Adventures.
After a long sweep out and round almost to Start Point, we spotted the mixed six crew rowing at quite a lick, taking full benefit from being with tide and with wind.
Heather Rees-Gaunt and Karl Steans and Ian Kavanagh were on the oars.
Skipper, Mikey Buckley stuck his head out of the aft hatch as we approached from astern – and we had a good chat.
All in good spirits and blissfully unaware of race positions as mobile signal coverage poor for last 24 hours. Pleased to be in touch with leaders (7 and 15 miles ahead).
All crew were fresh and chirpy, team spirit high – all contributed to discussion – a shouted interview at about 5metres off the aft quarter.
No injuries apart from some sore bums and a few blisters, settled into a good rowing routine and skipper estimates pass Land's End at approx 02:00 tomorrow morning.
Repairs were proudly reported, notably the steering fixed with gaffer tape, tie wraps and the now missing flagpole aft.
The GB Row flag was flying proudly on the aerial stanchion.
Breakfast, then on to Penzance to catch lead boats, Islanders and Hallin Marine 2, who were too far away for this visit.


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Daijouboo
Princess Connect! Re: Dive Review: Season 1
September 18, 2020 September 18, 2020 / justinsixtyfour
I went into this show with mixed expectations. Upon learning that it was directed by Takaomi Kanasaki, who also directed Konosuba, I had high hopes. However, this show is also an adaptation of a mobile game that I haven't played, which left me worried that I wouldn't have the necessary background knowledge to enjoy the show.
Princess Connect is an isekai that uses slice of life aspects to break up the well worn paths of the genre. Much of the show is built around character development as you watch the main characters enjoy life with one another, and less about an over arching plot. The protagonist is a soft-spoken, charming, amnesiac who fell out of the sky, and everyone loves him. Throughout the show, he is treated as the little brother that everyone wants to see succeed. Unlike Konosuba, the characters aren't constantly antagonizing one another, but are genuine and caring instead. They even form a guild together, called the Gourmet Guild, with the goal of finding new, exciting food and ingredients.
Each member of the guild is the embodiment of a different emotion, and watching everyone mesh together brings about incredibly entertaining situations. What happens when you have a tsundere catgirl mixed with an insatiable bundle of energy? How about when the friendly amnesiac goes missing and his timid, caring follower runs around looking for him? Exactly.
Animation and art style have been large talking points recently amongst anime fans, and Princess Connect has that in full. To put it simply, the show is gorgeous. The animation throughout the show is incredible, but what really sets the show apart is the attention to detail given to spells, abilities and attacks. It's jaw dropping. The bursts of colors and silky smooth movements of Princess Strike are the greatest feats of animation I've ever seen. Princess Connect is drawn extremely well; every frame could be a standalone picture, no problem. The attention to detail, the crisp lines, the cute art style… It all compliments the vibe that the show is going for.
Normally, I would have mentioned the storyline by now in a review, but I don't think it's important when talking about Princess Connect. The show has an interesting plot, but what I keep coming back for is the character development. It's the small trials and tribulations of daily life in a fantastical land that we see these characters embark on. With each interaction between characters, we get just a slightly better understanding of them. After awhile, each new episode felt like it was time to hang out with my friends for 23 minutes and 40 seconds.
That Time I Got Reincarnated as a Slime Review: Season 1
June 15, 2020 September 18, 2020 / justinsixtyfour
That Time I Got Reincarnated as a Slime isn't the first isekai to take the wholesomeness angle, but it does commit much harder than other shows are willing to. The protagonist will take the diplomatic route whenever possible, but that doesn't stop them from fighting if needed. This balanced mix between social and combat progress allows for richer character development. Even the side characters have their own supporting arcs that make you feel invested in their lives. Everyone loves and respects the protagonist, which enables them to bring different races together and cooperate as they attempt to build up their small goblin village into the capital city of the Jura Tempest Federation.
The art style matches the aesthetic of the characters and story line; it's clean, lighthearted, and vibrant. Even the spookier, moonlit or lantern-lit scenes remain pleasing, while also conveying the vibe they're going for. The fight scenes are animated very well, but they also spent time animating the more impactful non-fight scenes as well – reinforcing the balance.
Music is often underrated in anime, but it adds a lot to this show. Most of the songs are in a major key to help accentuate the upbeat wholesome angle. The songs enhance the current vibe and are never overpowering or dissonant. Similar themes have the same song to immediately signal what's taking place.
If there's one downside to That Time I Got Reincarnated as a Slime, it's the off balance pacing at times. The first and last few episodes are a little slow when compared to the rest of the season. The duration of some scenes doesn't match their significance, but every slower scene or episode was followed up with something exciting and important. If they keep following this pattern, the beginning of Season 2 will be something you don't want to miss.


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The ISSF Academy
Training Academy Courses
The Fundamentals of Clay Target
Olympic Clay Target shooting is an exciting and modern shooting sport. Since its appearance in the first modern Olympic Games in 1896, Clay Target shooting has grown into a worldwide sport and with shooters actively competing in over 100 countries.
Three clay target disciplines make up the modern Olympic Clay Target events. Each of these events requires a different shooting technique and requires from the shooter determination, commitment and skill to rise to the top level.
To enable clay target coaches and shooters to access a basic course in the Olympic disciplines, a special e-learning course has been designed and is now hosted on the ISSF Academy e-learning site. Start the Course
The Fundamentals of Pistol
Modern Olympic Pistol shooting has come along way since its debut at the 1st modern Olympic Games in 1896. With precision and rapid fire events, there is enough variety and skill required to ensure that it a sport which appeals to young and old alike.
Modern Olympic Pistol shooting has developed as a technical and highly skilled sport, requiring both mental and physical ability to succeed. The degree of skill involved requires coaching skills to match and the ISSF Academy is to the forefront in coach education for pistol.
To enable pistol coaches and shooters access to a basic and fundamental introduction to the Olympic pistol disciplines, a special e-coaching course has been designed and is now hosted on the ISSF Academy e-learning site. Start the Course
The Fundamentals of Olympic Rifle Shooting
Many authorities in the field of shooting and sport in general consider shooting to be a technical sport. It is not without its reasons. While in other sports, strength, speed and agility are required, shooting demands stability, calmness and micro-coordination. Alongside high level of psychophysical abilities, the results also depend on the technical aspects: the quality of rifles, ammunition, equipment and working conditions. Improving the shooting technique is also complicated, because in most cases, the coach is unable to see the minor errors that occur during shooting, so he relies on the shooter's opinion about what happens to him and, on the basis of that, he takes action to improve technique. Nowadays, the work of a coach is made easier by the use of training equipment (Noptel, Scatt, etc.) where the coach can perceive the main aspects of shooting: movement of the rifle, aiming, pulling the trigger, rhythm and on the basis of these correct any possible errors. But not everyone is in a position to use these technical advantages. Thus, the coach has to know the solutions for all the events during shooting and, trying different possibilities with a shooter, to achieve the best scores. Start the Course
ISSF launches e-Learning Platform
Coaching Platform
Members of ISSF Coach Advisory Committee
ISSF Coaches
The Art of Skeet Shooting


After checking out our sites designed for the food industry, PBS was very elated to work with us, and pick our brains to see what cool ideas we would have for their new site. After meeting with the family, touring their offices, and throwing ideas around, we were excited to get back and start building. Yep, we left with some product too – so delish!
Once we had a solid plan down for design, we went back out to their spot for photographs and videos, which you'll notice throughout the site. You'll also see motion throughout, as they did not want to standard, boring food distributor site. One of the coolest families to work with, and they make a delicious product. It's cool when we wear their shirts and people in the food industry stop us because they love the product.


Experienced in installation, testing, calibration and commissioning of various Temperature, Flow, Level & Pressure measuring instruments & Control valves along with all its accessories using various test equipments.
control valves and various control systems such as PLC, DCS & SHUTDOWN SYSTEMS.
Experienced in loop checking and commissioning jobs by using various test instruments such as HART communicator, Temperature Simulator, mA source etc.


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Browse: Home / Television / Stargate SG-1 / Season Four / Divide and Conquer / Review
When a member of the S.G.C. tries to kill a Tok'ra, it is revealed that O'Neill and Carter may be victims of an untraceable form of Goa'uld mind control.
WRITTEN BY: Tor Alexander Valenza
By Debra Kraft
"Divide and Conquer" yields a wealth of surprises. Just as Colonel O'Neill and viewers like me are getting less and less trusting of the Tok'ra, the S.G.C. hosts the signing of a treaty between the Tok'ra High Council and the president of the United States. The plot thickens even further with an acknowledgment that both Sam and Jack care about each other a lot more than they're supposed to, and with the unfortunate demise of Martouf.
Considering all of the above, it might be easy to surmise that Stargate SG-1 is starting to go the route of a sappy soap-opera. However, that is far from true. The writing continues to be exceptional, and these little plot twists are only serving to strengthen the show.
The idea of a Goa'uld brainwashing technique is another good angle to add to the growing list of weapons the System Lords can use in their ongoing attempts to defeat both the Tok'ra and the Tau'ri (Earth). The possibility of Goa'uld influence on unsuspecting SG teams with mere seconds of contact is an intriguing one, and I'll be curious to see what, if any, precautions will be enacted to protect against internal sabotage by affected "za'tarcs."
It is also interesting to see the Tok'ra concealing yet more information from the S.G.C. But most intriguing was the fact that it was Freya, the Tok'ra I have come to trust least, who finally insisted on sharing her theory about za'tarcs, while Martouf, the only Tok'ra besides Sam's father whom I have ever truly come to trust, insisted instead that the theory was pure conjecture and not worth mentioning -- despite Freya's evidence to the contrary. Perhaps this should have prepared me for the discovery that Martouf himself had become a victim of this new Goa'uld threat.
SG-1's writers continue to surprise me. Still, they did leave some apparent "holes." If even the members of the Tok'ra High Council were tested for Goa'uld influence, why would Martouf not have been subjected himself to the test? With the intense levels of security being undertaken by both the S.G.C. and the Tok'ra, this lapse is not logical, and thus doubtful.
Martouf's death, augured by his being on the receiving end of at least a dozen bullets but hastened by Sam Carter firing a second zat blast, was another surprising and touching moment. I will miss this character, as well as the ongoing possibility of romantic involvement between him and Carter. However, it must be noted that this reduces the number of "suitors" interested in Sam, and thus increases Jack's own odds.
Yes, Sam and Jack have finally admitted to having stronger feelings for one another than they should, given their current military status. However, they have not acted upon those feelings, and have even agreed to keeping them under wraps. These considerations are crucial to maintaining the integrity as well as the longevity of the series. A certain contingent of fans will now be eagerly anticipating that first kiss. Still another contingent will be dreading that inevitability. Let's keep 'em all waiting, shall we?
I'm still not quite sure what to make of the Anise/Freya character. There's a definite duality which makes her challenging to interpret. Though I wish she would get rid of the MarvelTM comics wardrobe, I'm growing to like this duality, with Anise as the ultimate Goa'uld scientist, arrogant and secretive, while her human host, Freya, is more forthright and humane, even seeming distraught as the young lieutenant commits suicide after failing her Goa'uld-implanted mission.
This differentiation between symbiote and host is further emphasized when Freya acts on her growing feelings for Jack, yet states that her symbiote, Anise, is more interested in Daniel. Confusing? Absolutely. Entertaining? Well, that part I'm not sure about either. Freya/Anise certainly dresses for the role of someone's love interest, but I don't believe that type of romance is needed in this series.
There are some good Daniel and Jack moments in this episode as well. It was interesting to hear Jack ask Daniel what he would do, given the choices our favorite Colonel was faced with; and it was interesting also to hear Daniel comment about the Jack O'Neill moments he would miss the most, while Jack was utterly absorbed in untangling a yo-yo. But the messages told here go far beyond the words spoken.
These two characters have established a tacit closeness, even a reliance upon one another. Jack is admitting to trusting Daniel's good judgment. Daniel is admitting to a certain degree of frustration in their ongoing inability to communicate at a higher level. Later, when the Tok'ra leader Per'sus commends Daniel's word-smithing of the treaty, Dr. Jackson's mind is obviously elsewhere, presumably with the friends he may never be able to communicate with again, on any level.
My last comments are directed at the treaty itself. The last time a treaty was signed at the S.G.C., it involved the System Lords and the Asgard agreeing to give Earth protected planet status ("Fair Game"). This time, the President of the United States is representing Earth in an agreement with the Tok'ra to fight the Goa'uld. Will this new treaty nullify that first one? Here is another curious thread I will be expecting to see unraveled in the future.
Season Four is coming together nicely, indeed. However, I look forward to a bit more planetary exploration. All this intrigue is well and good. Just throw in some pure adventure now and then and I'll be quite satisfied.
Rating: * * 1/2
VOTE! How would you rate SG-1's "Divide and Conquer?"
The Tok'ra, Part 1
Blasdale
Martouf
Per'sus
Lasarians
P6Y-325
PX9-757
za'tarc detector
Tok'ra High Council


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London venue for the world's largest panoramic photo
Paul Lamkin · 17 November 2010
Best iPhone apps 2020: The ultimate guide
Wow. That's definitely the first word that comes to mind when you look at Jeffrey Martin's incredible panorama of London.
Shot using a SLR camera with a 400mm lens, the 360-degree photo of London is the the largest spherical panoramic photo in the world.
It's 80-gigapixels, that's a resolution of 400,000 x 200,000 pixels, and if you were to print it at 300dpi you'd need a piece of paper measuring 35 x 17 metres.
In total, there are 7886 high-resolution individual photos, all shot from the top of the Centre Point building - that's 36 stories high - over a 3-day period.
The images were put together using a super-powerful Fujitsu Celsius workstation which comprised of dual 6-core CPUs, 192GB of RAM, and a 4GB graphics card.
The level of detail is simply incredible, you can zoom right in to street level and see people's faces and there are a number of nice features on the 360 Cities site, including a landmark locator, a virtual tour, overlapped mapping and a treasure hunt competition.
The effort beats previous world record attempts including a 26-gigapixel image of Paris, a 70-gigapixel image of Budapest, a 26-gigapixel image of Dresden, and Martin's previous record, an 18-gigapixel spherical image of Prague.
The photo is free to view over at www.360cities.net. Hold on to your socks.
Sections Gadgets Cameras Apps


While the Thunder's Russell Westbrook roars after his game-winning three, fans in Denver are struck with disbelief behind him.
Russell Westbrook has been on a tear all season long, doing anything and everything to lead his Thunder to victory. With his amazing athleticism, skill, and hustle comes amazing stats. Stats that have inked his 2016-2017 season in the history books. Westbrook broke Oscar Robertson's single season triple-double record Sunday night against the Denver Nuggets. He recorded 50 points, 16 rebounds, 10 assists, and hit the game-winning shot.
The Oklahoma City Thunder traveled to Denver to face the Nuggets last night. The Nuggets needed a win to keep themselves in playoff contention. While Denver was playing for a spot in the postseason, Oklahoma City was playing to get Westbrook in the history books.
Westbrook needed a triple-double to surpass the 55-year-old record of 41 triple-doubles in one season. With an assist early in the fourth quarter, his tally for the game jumped to 10 and Westbrook made history. It was triple-double number 42 for him.
While he and his teammates did celebrate a little during the next timeout, Westbrook knew there was unfinished business.
With under 10 seconds left in the game, the Thunder found themselves with the ball down two. Everybody in the arena and everybody watching on their televisions, phones, and tablets knew who was going to take the last shot.
A scramble for the ball broke out and inevitably ended up in Westbrook's hands. Westbrook skied for a deep three just a few feet ahead of the half court line. He nailed it just as the final buzzer went off, giving his team the 106-105 victory.
Not only did Westbrook make history with his amazing 50/16/10 game, he also wiped out the Nuggets' playoff hopes with a final second dagger.
Westbrook's 50 points, 16 rebounds, and 10 assists was just one of the many incredible stat lines he has put up this season. This game, with the game-winning shot and all, may have earned him his first Most Valuable Player award.
No matter what happens in the Thunder's final two games, Westbrook will have averaged a triple-double for a full season. A feat no one thought they'd see ever again. Westbrook just stuck to his "why not?" attitude and may have turned in the best single season a player has ever had.


Chartboost, the leading mobile gaming audience platform, launches Chartboost Exchange, opening programmatic access to its in-app global gaming inventory. Now for the first time, brand advertisers can reach the highly valuable mobile gaming audience at scale through technology partners Aarki, Index Exchange and Rubicon Project.
With more than 2.6B monthly active users, the growth of gaming continues to dominate engagement in the mobile space worldwide. In the U.S., 69 percent of mobile phone owners play a game once a month. In overall digital ad revenue, mobile ad spend accounted for over half in 2016.
Mobile and gaming are set to overtake the world of digital advertising and the mobile gaming audience is an untapped opportunity for brands. The Chartboost Exchange reaches over 300,000 mobile games worldwide, with over 900 million active players who engage in over 40 billion monthly game sessions through high performing ad units, such as video and interactive ads.
Transparency is a driving force in the Chartboost Exchange with a focus on data accessibility, brand safety, and full control over the user experience with ad creatives all supported by direct SDK-driven access to all publishers on the exchange. Through native in-app and innovative ad formats – like interstitial, vertical video, and interactive ads – creatives are dynamically optimized to 98 percent viewability.
For publishers on the Chartboost Network, a diverse demand means increased eCPMs with higher fill rates. Real-time bidding will bring healthier competition to the Chartboost ecosystem, earning game developers top revenue for quality users.
Chartboost Exchange rolled out in beta last month with DSP partners CrossChannel, CrossInstall, Jampp and PocketMath. Chartboost is currently expanding its partner relationships and focusing on new features to help advertisers reach more scale with full transparency in their campaigns.
Founded in 2011, Chartboost is the largest mobile games-based growth and ad monetization platform. Reaching over 900M unique users every month across more than 300,000 mobile games, Chartboost works with 90% of the top grossing iOS and Android game developers. Through Chartboost Exchange, Network, and Influence, Chartboost empowers game developers to earn top eCPMs while connecting advertisers to highly engaged audiences. The Chartboost SDK is the highest integrated independent mobile ad SDK.


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Christina Aguilera Admits New Album 'Inspired' by The Voice Singers
Posted byBy Taylor Gordon | Published on September 23, 2012 CommentsComments (0)
Christina Aguilera revealed that her latest album "Lotus" was actually "inspired" by The Voice contestants.
In an interview with MTV News, the pop diva admitted that seeing the contestants battle it out on The Voice, helped her regain the fire she had when she was still a rookie herself in the music industry.
"At this part of my life, I feel that I've reached a place where I'm completely embracing everything about who I am," the curvaceous Voice coach told MTV.
Christina took to Twitter to announce that her new album is scheduled to release in November just days after she announced she will be taking a hiatus from the singing reality show for season 4.
The "RealXtina," as she is called on Twitter, explained that the show allowed her to "see through the eyes of aspiring artists at the beginning of their journey, to be a part of the journey, to see the hunger in their eyes and to sort of regain some of that back for myself."
Particularly the contestants who made it unto Christina's team have a special place in the award winning pop crooner's heart.
"This year in particular, season three, I have a very pop-oriented team," the former Mickey Mouse Club performer said. "And they come to me and they're like, 'You know, I remember being in my room trying to dissect and learn all of the little ad libs and your technique and the runs and things like that, hitting your notes.' It inspired me also to want to give more of myself vocally on this record to let the next generation of great singers evolve and be inspired once again to dissect and learn certain lyrics and things."
Ironically, the inspiration that the "Beautiful" crooner received on the show, is only giving her proof that leaving the show for a season is the right thing to do.
The powerhouse Voice coach is taking time off to focus on her album and to go on tour to perform the very same songs that inspire young music hopefuls to follow in her footsteps.
Christina hasn't come out with a new album in two years, and although she enjoys being a mentor on The Voice she also admits that she has to get back to doing what she loves stating that she is "an artist first."
The new album, titled 'Lotus,' is the singer's way to represent her "rebirth."
"The term lotus means to me the unbreakable flower," she explained. "No matter the harshest of weather conditions, or its surroundings, it still survives and it thrives throughout time."
The new album will give her fans a lot of new inspiration while still finding a way to remind them of the music they grew up listening to.
She described one track as being "The Fighter 2.0."
"I want to make a record that speaks to those fans who grew up listening to my music and yet reintroduced new fans… watching me on The Voice at 6 years old who don't know about my first record," the Fighter singer explained.
Christina has been doing a lot to be a part of the community in more ways than just the inspirational exchange between her and her team on The Voice.
The Voice coach received a special achievement award for her amazing music career as well as her extensive humanitarian work at The American Latina Media Arts Awards on Friday.
Remaining ever so sexy, but still classy, Christina took to the ALMA red carpet in a full length black dress with see through lace panels on her back, sides and on her arms.
The Michael Kors dress hugged her new curvaceous figure in a flattering way and prevented her bright purple and pink strands in her bleach blonde hair from clashing with any other colors.
Her new "Lotus" album is set to drop on November 13.
TagsChristina AguileraLotusthe voice
Porsha Williams Gloats About Her Status as One of Nielsen's Top Social Media Stars
Celeb Relationships
Jennifer Hudson and David Otunga's Custody Battle Heats Up as Case Moves to Trial
'Unbelievable:' Viewers Trash 'The Voice' Coach Adam Levine for Making Case to Save Sick Nonperforming Contestant While Ignoring DeAndre Who Did Perform


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Uber Eats allowing marijuana orders in Canada
FILE - (AP Photo/Lynne Sladky, file)
Uber Eats is now allowing people in Ontario, Canada to order marijuana. However, the company won't deliver the product, according to CNN.
Instead, users will have to pick up their order from a Tokyo Smoke store.
Canada legalized recreations marijuana in 2018.
While the marijuana order option is only available in Canada right now, Uber's CEO has previously expressed interest in the U.S. marijuana market.
"When the road is clear for cannabis, when federal laws come into play, we're absolutely going to take a look at it," Uber CEO Dara Khosrowshahi told CNBC in April.
Recreational marijuana is legal in 18 states and the District of Columbia. However, it's still illegal under federal law.
Some lawmakers appear to be open to changing the law.
Republican Rep. Nancy Mace of South Carolina introduced a law this month that would decriminalize marijuana at the federal level.
"We need the federal government just to get out of the way," she said, according to Politico.
Many Democrats have been in favor of decriminalization for years. Mace's bill could lead to a compromise, according to Politico.
A poll from Gallup shows that support for legal marijuana hit a record high of 68% this month.


Looking for a great family activity that incorporates fun and learning for everyone?
How about Paper Circuits? Introducing your family to paper circuits opens up a whole new world to creativity, learning, and down right fun. Be sure to send me your creations and I can post them on the website!
The beauty of this project is it is inexpensive, and most of the materials can be found easily nearby. Materials can be ordered online as well. I am including a paper circuits guide book from Makerspaces.com which is a great, easy to use guide to not only get started but takes you step by step to build upon each activity. Print this guide out, hole punch, (sheet protectors optional) and you will have a great resource for family fun for many nights to come.
Copper tape -can be found at the larger hardware stores such as Home Depot or Lowes. It is often referred to as Slug and Snail Copper Tape. Can be ordered online through such vendors as Amazon. If you search Copper Tape online you will get many hits with options to purchase.
Coin cell battery (3v) I got mine 2 for $1.00 at where else, the dollar store. Best deal in town. Hardware stores and even pharmacies typically carry these, but darn, the Dollar Tree was the best deal. Did you know you can order online from the dollar tree? I don't work for them, but I sure do love them!
So this was the one item I had a hard time finding locally and found easier to order online. If you find a store that sells these locally please let me know, click here and email me. Amazon had several nice options. Order lots. Once you and your kids get going, you will be glad you have lots of lights. Good news, they are relatively inexpensive.


Jeevan Utsav Resort is a paradise in the foothills of Shivalik Himalayan Range near Rishikesh. The resort is an ideal for Corporate Training, Conferences & Retreat. The resort surrounded by Raja Ji National park and Shivalik Hills entry point for Himalayan Pilgrimages 100 mts away from Ganga near Rishikesh is a place where silence meets the soul, where you can leave the hustle bustle of life way behind.
Corporate Groups can conduct Conferences and Training Workshop for which our spacious and well equipped Conference Hall is ideal. The hotel also conducts Adventure Tours including River Rafting, Jungle Safari, Rock Climbing, Trekking, Nature Walking & Cycling.
The Jeevan Utsav resort is located in the Serene and natural surroundings, just 100 meters from the Holy Ganga and 200 meters from 14 kilometer long Chilla power Canal. Haridwar and and Risikesh are at 15 minutes Drive from the resort.
Rajaji National park, Triveni Ghat (Rishikesh), Ram Jhula (Rishikesh), Laxman Jhula (Rishikesh), Har ki Pauri, Mansa Devi Temple, Chandi Devi Temple, Daksha Mahadev Temple are all within 5 to 20 minutes drives from resort.
There are 40 well-furnished, fully equipped Rooms with landscaped garden in Jeevan Utsav Resort. The Business Centre has Internet facilities, Audio-Visual Aids for conducting Training Programs, Projector, Printer etc.
Day 01: Delhi - Rajaji National Park. ( 230 Km, drive 6 hrs ): Check in Jeevan Utsav Resort at Rajaji National Park. Lunch at Jeevan Utsav. Jungle Safari at Rajaji National Park. Evening tea/soup in the solace of Ganga River Bank. Dinner will be followed by bonfire and dancing activities.
Day 02: After breakfast Activities like Rope Pulling by making Teams, Kite Flying, Cricket Match, Photography etc then River Rafting at Rishikesh. Back to Jeevan Utsav for Lunch. or Trip to Vindhvasini Devi Temple - An adventurous way through deep forest and River water. A very pleasant and peaceful place Top of the Hill. Around 200 steps to be climbed for reaching the Temple. Sitting in the calmness and silence of Temple and having tea and snacks at Hill Shops make to feel a very different Experience and peace of mind.
Day 02: River Rafting at Rishikesh. Back to Jeevan Utsav for Lunch.After lunch then Trip to Vindhvasini Devi Temple - An adventurous way through deep forest and River water. A very pleasant and peaceful place Top of the Hill. Around 200 steps to be climbed for reaching the Temple. Sitting in the calmness and silence of Temple and having tea and snacks at Hill Shops make to feel a very different Experience and peace of mind..
Day 03: Delhi : After breakfast Activities like Rope Pulling by making Teams, Kite Flying, Cricket Match, Photography etc. Surprise Gifts for the Winners. After Lunch proceed towards Haridwar. Visit to Har ki Poudi and ghats of Ganga and other temples like Saptrishi Ashram. Arrival Delhi and tour ends here.
Day 02: River Rafting at Rishikesh. Back to Jeevan Utsav for Lunch.Trip to Vindhvasini Devi Temple - An adventurous way through deep forest and River water. A very pleasant and peaceful place Top of the Hill. Around 200 steps to be climbed for reaching the Temple. Sitting in the calmness and silence of Temple and having tea and snacks at Hill Shops make to feel a very different Experience and peace of mind. Or Sight Seeing like Laxman Jhula, Muni ki Reti, Swargashram, Ganges etc. in Rishikesh. or Rock Climbing for adventure loving. Evening movies in Open Movie Theatre. Dinner in leisure and camping.
From Haridwar: Cross Chandi Devi Bridge Take left to reach Chilla Power House ( 7 Km from Chandi Devi Bridge ) From Chilla Power House take Chilla Barrage Road after 7 Km Jeevan Utsav is situated in Ganga Bhogpur Talla on left hand side of the canal.
From Rishikesh: Rishikesh Degree college (1.Km before Rishikesh)-Take right turn from Degre college on Rishikesh Barrage Road after 2 Km take left turn on barrage bridge then after crossing the bridge take right turn on Chilla barrage Road after 7 Km Jeevan Utsav is situated at Ganga Bhogpur Talla.
Jeevan Utsav Resort is 40 kms from Domestic Dehradun Airport, 20 minutes drive from railway station and 20 minutes drive from Bus stand of Haridwar. Distance from Jeevan Utsav Resort to Haridwar is 17 Km, Rishikesh is 12 Km, Mussoorie is 90 Km, Kunjapuri is 37 Km, Dehradun is 52 kms.


text:
\section{Introduction}

In the present work we introduce
 a new approach
to simulations of field theories, based on wavelet expansions.
{}~\cite{debuch}~\cite{book}
{}~\cite{c-book}
Wavelets form  complete sets of localized, orthonormal states. Elements
of a set of
wavelets differ both in their
locations and in their scales. In fact, complete sets contain wavelets
at all scales, starting from an elementary scale up to the scale of the
system. Wavelets
can be labeled by two integers, $n$ and $k$, characterizing their scale
and their location.
 They can be formed from a function $\psi(x)$ as
 \begin{equation}
 \psi_{k,n}(x)=2^{-n/2}\psi(2^nx+k).
 \label{wave_gen}
 \end{equation}

Wavelets have been applied succcessfully to linear problems, like
signal analysis.
In the continuum, wavelets form a  complete orthonormal system,
allowing the
expansion of $L^2$ integrable functions, in a manner analogous
 to Fourier expansion.
The orthogonal functions of the Fourier expansion are not
localized, consequently they are not normalizable. Wavelets
are localized, albeit on varying scales, from the
elementary scale to the scale of the system. They are themselves
$L^2$ integrable function. As a rule,
they lead to series expansions with convergence considerably faster
then that of
a Fourier expansion.

  The property of wavelets of analysing data at all scales makes them,
  in principle,
 attractive for
the investigation of lattice problems. One can define wavelet
representations,
in which fields are expressed by their wavelet expansion coefficients,
rather then by their values at given spacetime points. On finite lattices,
the range of
integers $k$ and $n$ in (\ref{wave_gen}) is finite. It is not obvious
that wavelet
expansions, designed for investigating linear problems are useful for
investigating
a highly nonlinear problem such as a lattice field theory. The presence
of large scale
wavelets introduces nonlocality in the expression for interaction terms.
The decrese
in autocorrelation time is partially counterbalanced by the increased
computational
requirements. It is then important to give estimates for the growth
of nonlinearity
in terms of the lattice size. The question is the balance:
 whether one gains more by decreasing autocorrelation times
 than one loses by having to deal with a number of nonlocal terms
in the action.  This question will be investigated extensively in
the remainder of
this paper.
 Wavelets have already been used in lattice problems:  as a
 variational basis in the
$XY$ model~\cite{best}, and as a tool to facilitate gauge
fixing~\cite{what}.

Simulations in wavelet representation are somewhat similar to simulations
using collective updating methods, such as Swendsen and Wang's
algorithm~\cite{swendsen} or
the multigrid method~\cite{brandt}.
While the multigrid method is a so called smoothing
filter, averaging a large number of points, the wavelet representation
is, in a way, the opposite. Wavelets are designed to have their first few
moments vanish. Collective updating methods have been designed to
decrease the
dynamical exponent $z$ appearing in the expression of the autocorrelation
time ($\tau$) of physical quantities
\begin{equation}
\tau\simeq c ~\xi^z,
\label{auto}
\end{equation}
where $\xi$ is the spacetime correlation length, the inverse of the
mass gap.
In fact, some of the algorithms are able to reduce $z$ to almost zero.
 Near second order phase transition points the correlation length is
 proportional
to the linear size of the lattice, $L$. Thus, collective updating
algorithms are
particulary useful near critical
points and for large lattices. In fact, for lattices of small or
moderate size
or at some distance away from the critical point,  most collective
updating algorithms
are not much superior to local updating methods.

 In the next section we will introduce the wavelet formalism
 and transform the $\phi^4$ field theory into wavelet representation.
 Then we will count the number of nonlocal terms,
  to get a handle on the increase of
 computational needs as a
 function of lattice size.  In Section 3. we put the wavelet method
 to a direct test, we simulate a 2 dimensional $\phi^4$ theory, both
 using the
 standard Metropolis algorithm and the wavelet method. The last section
 contains our
 conclusions.

\section{The Wavelet Method in Field Theories}
Wavelets form a orthonormal system of variables interpolating between
coordinate and
momentum representations. In fact, wavelet representations (there are many
different choices) unify the advantages of both. They are much more local
and stable
against small perturbations than the momentum representation, and
at the same
time they can describe long range correlations with a small number of terms,
unlike the coordinate representation.

The most widely used wavelet filters were discovered by Daubechies
{}~\cite{debuch}.
Daubechies wavelets on discrete sets are defined as orthogonal matrix
transforms. 2$p$ of $2^n$ spatial
components, $x_1,...,x_{2^n}$ are combined together in two different ways:
with coefficients
 $c_1x_1+c_2x_2+...+c_{2p}x_{2p}$ (smoothed combinations)
 and with different ordering and signs of the same
 coefficients $-c_{2p}x_1+c_{2p-1}x_2-...+c_1x_{2p}$ (wavelets). The
 series is required
to have $p$ vanishing moments, i.e. $\sum_k (-k)^lc_{2p-k}=0,~
l=0,1,...,p-1$. Similarly,
one forms such linear combination from subsequent components $x_i$,
shifted by two
lattice
units an arbitrary number of times. Then requiring the orthogonality
of the
transformation makes the coefficients
essentially unique. The wavelet transform consists of $n-p$ subsequent
orthogonal
transformations
of the above described type, applied to the smoothed combinations obtained
in the previous orthogonal transformation. The coefficients
$c_1,...,c_{2p}$
 are called the Daubechies wavelet
filter coefficients.

For $p=1$  $c_0=c_1=1/\sqrt{2}$, and the wavelets are called
Haar-wavelets~\cite{book}.
The $r$th Haar wavelet of length $2^k$ on a one dimensional
lattice is
formed as
\begin{equation}
\chi_{k,r}=2^{-k/2}\sum_{i=1}^{2^{k-1}}[\phi(i+r 2^k)-\phi(i+
2^{k-1}+r 2^k)],
\label{wavelet}
\end{equation}
where $\phi(j)$ denotes the field at the $n$th site. The range
of $k$ and $r$ is
$k=1,2,...,n$, and $r=0,...,2^{n-k}-1$, respectively, where $L=2^n$,
is the size
of the lattice.
The orthogonal system is formed from the wavelets $\chi(k,r)$,
and one "smoothed" combination
\begin{equation}
\chi=\frac{1}{\sqrt{L}}\sum_{i=1}^L \phi(i),
\label{magn}
\end{equation}
which is the normalized total magnetization.

 The structure of the wavelet coefficients for general $p$ is
 similar to
 that of (\ref{wavelet}). Thus, the first $2^{n-1}$ wavelets are
 combinations
 of $2p$ neighboring data points shifted by multiples of 2.
 Then the next $2^{n-2}$ wavelets (each shifted from the next by 4
 data points)
  are of length $l_2=1+(2^2-1)(2p-1)$, etc. The $2^{n-k-1}$ $k$th
  type of wavelets are
  of length $l_k=1+(2^k-1)(2p-1)$. They are shifted from each other
  by $2^k$ points.
  The last $p$ combinations are not wavelets, but maximally smoothed
  combinations
  of the original data points.

 In an application to lattice field theory one has to use wavelets in
 more
 then one dimension.  In fact, wavelets can easily be defined in
 any number of dimensions.
In each dimension the wavelets are labeled by their scale,
$k_i$, and by their location, {\bf r}. Thus, a wavelet coefficient
$\chi(k_1,r_1;k_2,r_2;...;
k_d,r_d)$ corresponds to a  wavelet box of length $2^{k_i}$ in the
$i$th lattice dimension.
$d$ is the number
of dimensions.
 There are $2^{nd-k_1-k_2-...-k_d}$
wavelets labeled by a given scale vector ${\bf k}=\{k_1,k_2,...,k_d\}
$. The lattice field has a linear expansion in terms of the coefficients
$\chi(k_1,r_1;k_2,r_2;...;
k_d,r_d)$. We will call these coefficients the wavelet representation.
It is on an equal
footing with the momentum and coordinate representations.

Wavelets are well suited to analyzing linear problems. Consequently
a Gaussian
model is just as simple in wavelet representation as in coordinate
representation.
Orthonormality implies that the form of the mass term
 is unchanged in wavelet representation
\begin{equation}
S=\frac{m^2}{2}\sum_{j,r}2|\chi(j,r)|^2
\label{newaction}
\end{equation}
where for the sake of simplicity we have dropped the limits of
the summations.
The kinetic term is slightly more complicated, and its explicit form is not
very enlightening.
 It has a moderate number of nonlocal terms.

The propagator in wavelet space is quite
analogous to the one in coordinate space. Thus, it has the same
asympotic behavior
and it also becomes singular at the critical point, $m^2=0$. Critical
phenomena can be
investigated in wavelet representation just as well as in coordinate
representation. Alternatively, one can easily transform correlation
functions
back to coordinate representation, using the wavelet transformation.

The question arises, however, how well the wavelet representation
is suited to
investigate nonlinear problems, like any nontrivial field theory.
In the current
paper we will
investigate a typical example
of nonlinear field theories, the $\phi^4$ theory. We need to
express the
interaction term in terms of wavelets. Using the orthogonality
of the wavelet
transformation an explicit
expression for  the interaction  term of the Lagrangian $g\sum
\phi^4$ is very
complicated.  It has many
non-local terms, some of them correspond to `long-range' interactions. The
success of the wavelet representation depends on the average number of
 these long range interaction terms per wavelet.  If this average number
increases slowly with size we have a chance that simulations in
wavelet representation will be more efficient then those in coordinate
representation.

First, we will calculate the average number of interaction terms per
wavelet
coefficient on a $d$-dimensional lattice. It is sufficient to do the
calculation in
one dimension. If the number of interaction terms per wavelet is $N$ in
one dimension then it is $N^d$ in $d$ dimensions. The interaction term
is a quartic combination of the wavelet coefficients. For the sake of
simplicity
we will do the counting for the Haar-wavelet representation. Then it
is easy to
see that in every term the coefficient with the lowest value of $j$
must be squared.
Let that coefficient be $\chi(j,m)$. Then the combinations of other
 wavelets multiplying $\chi(j,m)^2$ can be found as follows: for
 each $j$
there is only one wavelet  overlaping $\chi(j,m)$. Then the bilinear
multiplier
has $(n-j)(n-j+1)/2$ different types of terms. The number of wavelets
with scale $j$
is $L/2^j$. Then the total number of types of non-local interaction
terms is
\begin{equation}
LN=\sum_{j=1}^{n-1}\frac{L}{2^j}\ \frac{(n-j)(n-j+1)}{2}.
\label{number}
\end{equation}
In other words, the average number of non-local interaction terms
per wavelet is
\begin{equation}
N\simeq \frac{n^2}{2}=\frac{(\log L)^2}{2(\log2)^2}.
\label{Nest}
\end{equation}
This number should be compared with 1, the average number of terms per
site in the coordinate representation. In $d$ dimension the
appropriate factor is
\begin{equation}
N_d=\frac{(\log L)^{2d}}{2^d(\log2)^{2d}}.
 \label{Nd}
 \end{equation}

 In the next section, before discussing our simulations, we will perform
 a more precise analysis of computational needs.  It will turn out that
  the number of computations  per lattice site
 in a $d$ dimensional model increases only as  $(\log L)^d$ and not as
 $(\log L)^{2d}$. The application of multiple hits at each wavelet
 coefficient
 in the Monte Carlo simulation further decreases the ratio of computational
 needs.

 \section{Simulations}

 The difference in the number of cycles needed between local and
 wavelet simulations
 is due to the calculation of the change of the action.
 The largest computational needs arise from the calculation of the
 interaction term.
 The action has the form
 \begin{equation}
 S=\frac{1}{2}\sum_{\bf r}\left[m^2\phi_{\bf r}^2+
 \sum_j^d(\phi_{\bf r}-\phi_{\bf r-\hat
 {\bf e}_j})^2+\frac{g}{12} \phi_{\bf r}^4\right]
 \label{inter}
 \end{equation}
 This expression is very complicated in terms of the wavelet
 coefficients, even
 for the simplest, Haar wavelets. For that reason it is not
 conducive to the
 calculations to express (\ref{inter}) in terms of $\chi(k_1,r_1,
 ..., k_d,r_d)$.
 It is more efficient to store both the coordinate and the wavelet
 representation
 coefficients. This doubles storage needs, but accelerates and
 simplifies the code considerably.

 Suppose that during a sweep of the lattice we update the coefficient
 $\chi=\chi(k_1,r_1,..., k_d,r_d)$.
 Then
 the action has the following dependence on $\chi$:
 \begin{eqnarray}
 S&=&\frac{m^2\chi^2}{2}+\sum_{\bf r}\sum_j\left\{
 \chi[\phi_{\bf r}-\phi_{{\bf r}-\hat
 {\bf e}_j}]\left[
 \frac{\partial \phi_{\bf r}}{\partial \chi}
 -\frac{\partial \phi_{\bf r+\hat {\bf e}_j}}{\partial
 \chi}\right]+\frac{\chi^2}{2}\left[
 \frac{\partial \phi_{\bf r}}{\partial \chi}
 -\frac{\partial \phi_{\bf r+\hat {\bf e}_j}}{\partial
 \chi}\right]^2\right\}
 \nonumber\\&+&
 \frac{\chi^4}{4!}\sum_{\bf r}\left(\frac{\partial \phi_{\bf r}}
 {\partial \chi}\right)^4+\frac{\chi^3}{3!}\sum_{\bf r}\left(
 \frac{\partial \phi_{\bf r}}
 {\partial \chi}\right)^3\phi_{\bf r}+
\frac{\chi^2}{4}\sum_{\bf r}\left(\frac{\partial \phi_{\bf r}}
 {\partial \chi}\right)^2\phi^2_{\bf r}\nonumber\\&+&
 \frac{\chi}{6}\sum_{\bf r}\left(\frac{\partial \phi_{\bf r}}
 {\partial \chi}\right)\phi^3_{\bf r}+{\rm terms~independent~of~\chi},
 \label{action}
 \end{eqnarray}
  The
 coefficients
  $\partial \phi_{\bf r}/\partial\chi$ depend only on the
  relative position of
  the lattice points. They are given by products of coefficients
  $c_i^{(k)}$, for $k=
  k_1,k_2,...,k_d.$
These coefficients can be easily tabulated with minimal storage
requirements, even
for general $p$.  The
coefficient of $\chi^4$, and that of the quadratic part of the
kinetic term
 depend on ${\bf k}$ only. For Haar wavelets the coefficient of the
 fourth order
 term is
$2^{(k_1+k_2+...+k_d-dn)/2}$

The action defines the probability distribution of $\chi$. It must
be evaluated
repeatedly during simulations.The
calculation of the interaction part requires 8 floating point
operations (5 for Haar
wavelets) for every individual
coordinate point, ${\bf r}$. There are
$\prod l_{k_i}\simeq (2p-1)^d 2^{k_1+...+k_d}$ points
inside the wavelet. Now, for a complete sweep one has to update
all $2^{nd-k_1-
...-k_d}$ coefficients of the same kind, giving the number of
floating point operations
as $8(2p-1)^d2^{nd}$. Finally, one has to update the coefficients
for all values of
$k_1,...,k_d$, bringing in an additional coefficient of $n^d$,
where $n=\log L/\log 2$,
where $L$ is the length of an edge of the lattice. Then the
average number of
floating point operations per lattice site is
$N_d=8(2p-1)^dn^d$. The calculation of the kinetic term requires further
$4(2p-1)^dn^d$ operations. For Haar wavelets the calculation of the
kinetic term requires only  $O(n^{d-1})$
floating point operations.

There is a further requirement in the updating algorithm. After every
change of a
variable $\chi$ one has to recalculate the affected fields in
coordinate representation.
It is easy to get a similar estimate for the average number of
floating point operations
needed for such an updating. It just changes the coefficient of
$N_d$ from 8+4$d$ to 10+
4$d$.
  The ratio to the average number of floating point operations per site
   in a straightforward
  simulation in local simulation (coordinate representation) (6+2$d$)
  is then
  \begin{equation}
  \frac{t_w}{t_l}=\frac{10+4d}{6+2d}[n(2p-1)]^d[1+O(1/n)].
  \label{ratio}
  \end{equation}
  where $t_l$ and $t_w$ are the average times a sweep of the lattice
  takes in local
  and
  wavelet simulations, respectively.
  In particular, for Haar wavelets and two dimensions, $R_d\simeq
  (n^2/2)[1+O(1/n)]$.

  In fact, one can obtain a substantially smaller ratio as follows.
    Notice that the factor $(\log L)^d$ appears in (\ref{ratio})
  due to the computation of
  the coefficients of $\chi$ in action (\ref{action}). If one
  performs the
  Metropolis simulation in such a way that there are several
  hits at every
  wavelet $\chi$, then the same coefficients of (\ref{action})
  can be used and the extra calculation becomes
  not more costly then that of a hit in coordinate representation
  (local simulation).
   At the same time,
  having several hits at the same field component does not lead to
  any substantial
  savings in the local updating algorithm. Thus, in the limit of
  large number of hits
  the average sweeptimes for the two types of simulations converge.
  Of course,
  after a certain number of hits, the return in decreasing statistical
  errors
  diminishes. As usual, one has to find the optimal number of hits,
  so that the
  statistical errors were minimized using a fixed amount of
  computational time.
  Figure 1. shows the dependence of autocorrelation times on
  the number of hits.
  The autocorrelation times have been calculated using two
  different techniques.
  One, by direct measurement of the autocorrelation of the
  total magnetization,
  and the other by calculating the square of the relative
  error of the same
  physical quantity. They provide very similar information.
  When choosing the
  number of hits in the simulation, we had to keep in mind
  that the requirements
  on computing computing time slowly increase with the number
  of hits. The product
  of $\tau_w$ with the average time a sweep, $t_w$, should be
  optimized. We chose
  the optimum value of 5 in all of our simulations. For 5 hits
  we find the following
  values for $t_w/t_l$: 1.2, 1.3, 1.54, 1.82, on lattices of
  sizes $L=8,16,32,$
  and 64, respectively.

  The quality of an algorithm is determined by its improvement
  factor,
  which is defined as
  \begin{equation}
  I=\frac{t_w\tau_w}{t_l\tau_l},
  \label{improv}
  \end{equation}
  where $\tau_l$ and $\tau_w$ refer to real time autocorrelation
  lengths. Having
  determined (\ref{ratio}) in the rest
  of this paper we will concentrate on the determination of
  autocorrelation times
  $\tau_w$ and $\tau_l$.

  It is important to emphasize a substantial difference between
  a simulation using
  the standard, local (coordinate representation) algorithm and
  a simulation
  in wavelet representation. A hidden parameter of all simulations
  is the
  size of the window, $\Delta$, in which a new field value is
  picked during the
  Metropolis algorithm. In other words, if the value of the
  field component is
  $\phi$, then we choose a random new value for $\phi$, $\phi'$,
  in the interval $\phi-\Delta/2<\phi'
  <\phi+\Delta/2$. While in a local  simulation there is only one
  possible parameter
  $\Delta$, in the wavelet representation there is the possibility,
  and indeed the
  necessity, of choosing different values $\Delta_{ij}$,
  $i,j=1,...,n+1$,
  for different sizes of wavelets. The
  effect of this freedom of choice of the window sizes on
   autocorrelation times will be discussed later.

  The evaluation of the improvement factor $I$ of (\ref{improv})
  requires the determination
  of autocorrelation times.  We have performed extensive simulations
  on lattices of
  sizes $L=$8,16,32, and 64.
  In wavelet simulation, after a warmup period of $O(10^4)$ sweeps
  we read out
  the relevant physical variables in the next $O(10^5)$ sweeps.
  Using the local
  updating algorithm we had to have much longer runs, $O(10^6)$
  sweeps to be
  able to determine autocorrelation lengths. We compared the
  values of various
  physical quantities, such as $\langle\phi^2\rangle$,
  $\langle H\rangle$,
  $\langle |M|\rangle$, $\langle c_v\rangle$, and
  $\langle\chi\rangle$, where
  $M$ is the magnetization, $c_v$ is the specific heat, and
  $\chi$ is the
  magnetic susceptibility. All the physical quantities agreed within
  statistical errors in the two simulations. The simulations were
  performed at fixed $g=1$ and varying $m^2$ between the limits of
  -0.31 and -0.25, a range which includes the critical point.

  The purpose of the simulations was to calculate autocorrelation
  times, obtained
  from the $t$ dependence of autocorrelation functions
  \begin{equation}
  \Gamma(t)=\langle\ X(t')X(t'-t)\rangle_{t'},
  \label{gamma}
  \end{equation}
  where $X$ is a physical quantity, $t$ and $t'$ label real time during
  the simulation, measured in units of sweeps. The average of
  (\ref{gamma}) is
   over time $t'$. For moderate values of $t$, $\Gamma(t)$ is
   expected to
   have an exponential dependence on $t$,
   $\Gamma(t)\simeq \Gamma(0)\ e^{-t/\tau}$, where $\tau$ is
   the autocorrelation time.
   In fact, the integrated autocorrelation function,
   \begin{equation}
   \Gamma^I(t)=\frac{1}{\Gamma(0)}\sum_{t'=0}^t\Gamma(t')\simeq
    \frac{1}{1-e^{-1/\tau}}.
   \label{int}
   \end{equation}
   serves as a better measure of  the autocorrelation time
   ~\cite{sokal}~\cite{wolff}
   The integrated autocorrelation function goes into saturation
   at large $t$.
   The saturation value determines the autocorrelation time, $\tau$.

  We calculated autocorrelation
  times (measured in units of sweeps)
  for three physical quantities: Total magnetization, $M$,
  average value of $\phi(x)^2$, and the average value of the action.
    The dependence of autocorrelation times on the mass parameter of
  the Lagrangian, near the critical point is shown in Figure 2.
  Typical errors
  are about 5-10\%. The point of Fig. 2. represent data on
  lattice size $L=32$.

  It is important to determine the dependence of autocorrelation
  times on the
  size of the lattice.  Let us define an exponent $\zeta$ in a
  manner, somewhat
  analogous to (\ref{auto})
  \begin{equation}
  \tau=c L^\zeta .
  \label{auto2}
  \end{equation}
  At the critical point $\zeta$ coincides with $z$. Away from
  the critical point
  $\zeta$ is smaller then $z$ because $L>\xi$. The difference
  of $z$ and $\zeta$
  measures the finite size effect on the correlation length.
  The exponent $\zeta$,
  plotted in Fig. 3. in the critical region was calculated using
 all four lattice sizes we studied.
  Near the critical point, $m^2\simeq-0.285$, the exponent is
  almost 2. In fact,
  if the smallest lattice, $L=8$, is omitted from the fit the
  value exceeds 2. This
  shows that simulations in wavelet representation do not circumvent
  critical
  slowing down. In fact, a plot of exponent $\zeta$ in local simulations
  is almost identical to Fig. 3. In other words, the possible gain in
  autcorrelation times
  (\ref{auto2})
  in local and wavelet simulations. Indeed, the ratio of
  autocorrelation
  times in local and wavelet representation simulations has a
  large and fairly
  constant value for all lattice sizes considered. Fig. 4. shows
  these ratios in the
  critical region of $m^2$. A multiplier 5 corresponding to
  the number
of hits per wavelet coefficient
has been included in $\tau_w$.
 The ratio has only a moderate variation with lattice size
  or $m^2$. It is in the range of 10-15. Then the improvement
  factor, $I$,
   of (\ref{improv})
  at the critical point varies between 7 on the largest lattice to
  a value over 10 on the
  smaller lattices. There is a slight tendency to an increase of $I$
  when one moves
  away from critical point toward the disordered phase.

\section{Discussion}

The general expectation of substantially decreased autocorrelation times in
a simulation in wavelet representation was borne out by our simulations.
One can demonstrate quite dramatically the effectiveness of our method on
the free bosonic theory ($g=0$). Consider the autocorrelation of the total
magnetization. As we mentioned earlier, the magnetization is
proportional to one
of the wavelet expansion coefficients, the `non-wavelet' component. Let us
denote this component by $\chi$.
 Since the
kinetic term is  independent of $\chi$, $\chi$ completely decouples.
The $\chi$ dependence of the action
is
\begin{equation}
S=\frac{1}{2}m^2\chi^2.
\label{actionm}
\end{equation}
In other words, the action is a Gaussian function of $\chi$.
 Then the autocorrelation length for magnetization, can only depend
 on the dimensionless
 product $m\Delta$, where $\Delta$ is the range of change of $\chi$ in
 the simulation.
The dynamical critical exponent is 2. This can be seen by the
following heuristic
argument. Suppose $m\Delta<<1$. Then starting from an average value,
$\chi\sim 1/m$,
after $n$ sweeps the value of $\chi$ wanders away by an average value of
$\delta\chi\sim\sqrt{n}\Delta$ (random walk).
Complete decorrelation requires $\delta\chi\sim
\chi\sim1/m$. Then we obtain the following estimate for the
autocorrelation time:
\begin{equation}
\tau=n\simeq \frac{1}{(m\Delta)^2}=\frac{\lambda^2}{\Delta^2},
\label{auto4}
\end{equation}
where $\lambda$ is the spatial correlation length on the lattice.
(\ref{auto4})
shows not only that the critical exponent, $z=2$, but also
shows that the
numerical value of the autocorrelation length is inversely
proportional to
$\Delta^2$. In other words, if one chooses $\Delta$ for the
non-wavelet coefficient
too small one can get very long autocorrelation times. In a
wavelet simulation one
can control $\Delta$ independently for different types of
coefficients. Indeed,
in our simulation we have chosen the window $\Delta$ for
$\chi$ in such a  way
that the acceptance was approximately 0.5.

In a local, coordinate representation
simulation one has no control over the allowed range of change
of the total
magnetization. In fact, it is expected to change by a very
small amount in every
sweep. Since $\chi=\sum\phi/\sqrt{M}$, thus,
$\delta\chi=\sum\delta\phi/\sqrt{M}$,
roughly speaking $\delta\chi\sim\sqrt{M}\delta\phi/\sqrt{M}=\delta\phi$.
We performed some simulations at $g=0$ as well (free bosonic theory),
and in those simulations the optimal window $\Delta$ was independent of the
mass, $m$. Since the autocorrelation can only depend on the
product $m\Delta$, at small $m$ and constant $\Delta$ one can use
the asymptotic behavior
which should be the same as (\ref{auto4}). Indeed we obtained
the following
autocorrelation times for the total magnetization: 865 at
$m^2=.005$, 310 at
$m^2=.01$, 228 at $m^2=.015$, and 179 at $m^2=.02$. All of these
have about 10\%
error. These autocorrelation times give a good fit to (\ref{auto4}). In
other words, the effective value of $\Delta$ for the magnetization
was indeed  constant,
 as we assumed from the outset. Notice, however, what happens in a
simulation in wavelet representation. The window $\Delta$ is
adjusted for each type
of wavelet separately. In particular, one adjusts $\Delta$ for
the magnetization
as well. If one requires constant acceptance, then $\Delta m$ and so the
autocorrelation time is kept constant. The critical slowing down, at least for
free theories, is completely eliminated.

In the interacting case there is substantial mass renormalization.
Still, for moderate
values of the $m\Delta$ one
 expects a general dependence like (\ref{auto4}) on $\Delta$ where one
 should use the renormalized mass. Unfortunately, in interacting
 theories in $D=2$
 there is another dimensional quantity, $g$. The autocorrelation
 time also  depends
 on the dimensionless quantity $g/m^2$. The dependence on this
 quantity seems
 to dominate the behavior of exponent $\zeta$. The constant $c$ is,
 however, affected
 very strongly by the value of $m\Delta $, leading to a dramatic
 decrease of
 autocorrelation times in simulations in wavelet representation.

 To check the above ideas, we ran a series of simulations in
 wavelet representation
 on an $L=32$ lattice, at the same value of the physical parameters,
 set at the
 approximate location
 of the critical point, $g=1$ and $\mu^2=-.285$, but varying the
 window size for
 the wavelet component, that is proportional to the total
 magnetization. Fig. 5.
 shows
autocorrelation times for magnetization as a function of the
window size, $\Delta$,
for the appropriate wavelet component, $\chi=\sum\phi/\sqrt{M}$,
where $M$ is
the total number of lattice sites. The curve has, for these values of
$m^2$ and $g$,
 a broad minimum around an optimal
window size.

The  optimal value of window size for the
change of $\phi$ in local simulations is about $\Delta=3$. Due to
the orthogonality
of the transformation from local variables, $\phi$, to wavelet
components, $\chi$,
a local simulation is in some sense equivalent to a wavelet
simulation in which
every window $\Delta$ is set equal to the value of $\Delta$ in
the local simulation.
For this reason we ran a simulation on a 32$\times$32 lattice
at $m^2=-.285$,
setting all windows equal to $\Delta=3.0$. We obtained an
autocorrelation time of
$\tau_w=226$, comparable to $\tau_l\simeq436$. At the same point,
if we optimize all the windows, such that all acceptances are
between 0.4 and 0.5,
then $\tau_w=39$. This result supports the idea that a
major part of the decrease in autocorrelation time
is not the result of
relaxing the system at different scales simultaneously. It is rather
the consequence of the extra freedom of setting the windows for every
scale independently.

In the present paper we have used Haar wavelets. It would be of
some iterest to
investigate simulations with other examples of the Daubechies
wavelet series.
Because the wavelet expansion coefficients would be all
different, the calculation
of the action would take a longer time. It is still
possible that the improved
convergence properties of the wavelet expansion would
make the comparision with
the local simulation even more favorable.

Finally, we would like to point out that wavelet representations
can be used for
theories with more complicated order parameters as well. In such
simulations
the ratio of sweeptimes should be roughly the same as has been
obtained in the
current paper. As an example, for compact  Abelian gauge theories
wavelets should
be formed from the components of the vector potential.
The calculation of the
change of the action requires the calculation of trigonometric function in
both representations. The estimate we have given for computational
requirements in Sec. 2. would still stand. Unfortunately, since the action
is nonpolynomial, the ratio of simulation times may not be
substantially improved by repeated
hits at individual wavelet coefficients.

\section*{ACKNOWLEDGEMENTS}

The work of P. S. is supported by funds from Research Committee of the
Higher Education Funding Council for Wales (HEFCWR).
  He is also indebted for the partial support of
the United States Department of Energy under
grant no.  DE-FG02-84ER40153.

redpajama_set_name: RedPajamaArXiv


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text:
Q: Update a global variable from a function I have 2 variables which are concatenated into another variable.  On the click of a button the values of the variables should update and also the concatenated variable, but the global variable is keeping the original value.
<button class="filter period" data-sort-value="number" data-period="ltd">LTD</button>
<button class="filter period" data-sort-value="number" data-period="r3">R+3</button>
<button class="filter period" data-sort-value="number" data-period="r12">R+12</button>
<button class="filter period" data-sort-value="number" data-period="rtodec">RTODEC</button>
<script>

    var region = "ww";
    var period = "ltd";

    var finalFilter = "data-" + region + "-" + period;

    $('button.filter').on('click', function () {

        if ( $(this).hasClass("period") ) {

            period = $(this).attr('data-period');
            console.log(finalFilter);
            console.log(period);
            updatedFinalFilter();
        }

    });
</script>

A:
Yes, i want that finalFilter to be update automatically when one of period or region change value

The only way to make that happen is to actually update it.  Variables in JavaScript don't update automatically based on the expression you used to set them the first time.  After:
var finalFilter = "data-" + region + "-" + period;

has run, finalFilter is purely set to "data-ww-ltd" - it has no knowledge of or link to region or period.
So before you call updatedFinalFilter(), you'd have to re-evaluate the expression:
var region = "ww";
var period = "ltd";

var finalFilter = "data-" + region + "-" + period;

$('button.filter').on('click', function () {

    if ( $(this).hasClass("period") ) {

        period = $(this).attr('data-period');

        finalFilter = "data-" + region + "-" + period;

        console.log(finalFilter);
        console.log(period);
        updatedFinalFilter();
    }

});

Note the lack of var when we update it from in the function - you don't want to redeclare it there otherwise it will become a different finalFilter locally scoped to that function.

redpajama_set_name: RedPajamaStackExchange


text:
A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations
Sabah Abdullah Al-Somali, Roya Gholami, Ben Clegg*
Operations & Information Management
Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.
Journal of Manufacturing Technology Management
https://doi.org/10.1108/JMTM-03-2013-0019
This article is © Emerald Group Publishing and permission has been granted for this version to appear here http://www.emeraldinsight.com/doi/full/10.1108/JMTM-03-2013-0019. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.
technology implementation
10.1108/JMTM-03-2013-0019
Stage-oriented model (SOM) for e-commerce adoption
Accepted author manuscript, 906 KB
http://www.emeraldinsight.com/doi/full/10.1108/JMTM-03-2013-0019
Dive into the research topics of 'A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations'. Together they form a unique fingerprint.
E-commerce Adoption Business & Economics 100%
Saudi Arabia Business & Economics 62%
Electronic Commerce Business & Economics 39%
Middle East Business & Economics 22%
Innovation Adoption Business & Economics 15%
Inhibitor Business & Economics 14%
Innovation Model Business & Economics 14%
Western Countries Business & Economics 13%
Abdullah Al-Somali, S., Gholami, R., & Clegg, B. (2015). A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations. Journal of Manufacturing Technology Management, 26(1), 2-35. https://doi.org/10.1108/JMTM-03-2013-0019
Abdullah Al-Somali, Sabah ; Gholami, Roya ; Clegg, Ben. / A stage-oriented model (SOM) for e-commerce adoption : a study of Saudi Arabian organisations. In: Journal of Manufacturing Technology Management. 2015 ; Vol. 26, No. 1. pp. 2-35.
@article{8498876035e640fdbef34f3804820540,
title = "A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations",
abstract = "Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.",
keywords = "e-commerce, information systems, technological innovation, technology implementation",
author = "{Abdullah Al-Somali}, Sabah and Roya Gholami and Ben Clegg",
note = "This article is {\textcopyright} Emerald Group Publishing and permission has been granted for this version to appear here http://www.emeraldinsight.com/doi/full/10.1108/JMTM-03-2013-0019. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.",
doi = "10.1108/JMTM-03-2013-0019",
journal = "Journal of Manufacturing Technology Management",
Abdullah Al-Somali, S, Gholami, R & Clegg, B 2015, 'A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations', Journal of Manufacturing Technology Management, vol. 26, no. 1, pp. 2-35. https://doi.org/10.1108/JMTM-03-2013-0019
A stage-oriented model (SOM) for e-commerce adoption : a study of Saudi Arabian organisations. / Abdullah Al-Somali, Sabah; Gholami, Roya; Clegg, Ben.
In: Journal of Manufacturing Technology Management, Vol. 26, No. 1, 2015, p. 2-35.
T1 - A stage-oriented model (SOM) for e-commerce adoption
T2 - a study of Saudi Arabian organisations
AU - Abdullah Al-Somali, Sabah
AU - Gholami, Roya
AU - Clegg, Ben
N1 - This article is © Emerald Group Publishing and permission has been granted for this version to appear here http://www.emeraldinsight.com/doi/full/10.1108/JMTM-03-2013-0019. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.
N2 - Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.
AB - Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.
KW - e-commerce
KW - information systems
KW - technological innovation
KW - technology implementation
U2 - 10.1108/JMTM-03-2013-0019
DO - 10.1108/JMTM-03-2013-0019
JO - Journal of Manufacturing Technology Management
JF - Journal of Manufacturing Technology Management
Abdullah Al-Somali S, Gholami R, Clegg B. A stage-oriented model (SOM) for e-commerce adoption: a study of Saudi Arabian organisations. Journal of Manufacturing Technology Management. 2015;26(1):2-35. https://doi.org/10.1108/JMTM-03-2013-0019


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Time 24 are also a major supplier of contract labour for specialist wiring and assembly with over seventy staff currently working at customers premises.
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Blinding EmbersBlinding Embers: Blinds on a confirmed vorpal hit. Duration is about 20 seconds. DC35 reflex save negates the blindness.
Fire VulnerabilityFire Vulnerability: On Hit: Applies a stack of Vulnerable (1% more damage for 3 seconds. This effect stacks up to 20 times, and loses one stack on expiration.). This effect may only occur on-hit once every second.
Turbulent BurstTurbulent Burst: This weapon is enchanted with wild, unpredictable energy. It will do 1 to 8 damage of a random energy type (fire/cold/electric/acid) on a successful hit and 3 to 24 damage of a random energy type on critical hits.
Fiery 4Fiery 4: This effect causes the edges of this weapon to burn with enchanted flames, dealing 4d6 fire damage on each hit.
SmitingSmiting: On Hit: 4 to 24 Bane damage to Constructs.
On Vorpal Hit: If a construct struck by this weapon has fewer than 1000 Hit Points, it is instantly slain. If the construct has above 1000 Hit Points, it takes 100 damage.
AxiomaticAxiomatic: An axiomatic weapon is lawfully aligned and infused with the power of law. It makes the weapon law-aligned and thus bypasses the corresponding damage reduction. It deals an extra 2 to 12 damage against all of chaotic alignment.
Heartseeker IIIHeartseeker III: On Critical Hit: 7 to 42 Piercing damage from weapons with a x2 Critical Multiplier, 7 to 56 damage from weapons with a x3 Critical Multiplier, and 7 to 70 damage from weapons with a x4 or Greater Multiplier.
Heartseeker IVHeartseeker IV: On Critical Hit: 9 to 54 Piercing damage from weapons with a x2 Critical Multiplier, 9 to 72 damage from weapons with a x3 Critical Multiplier, and 9 to 90 damage from weapons with a x4 or Greater Multiplier.
BodyfeederBodyfeeder: Whenever a bodyfeeder weapon you wield scores a critical hit, you gain 15 temporary hitpoints that last for up to 1 minute.
FracturingFracturing: This weapon is ideal for breaking bones and does 2 to 12 damage to targets that have skeletons or are made of bone.
Felling the OakFelling the Oak: On a natural 20 that is confirmed as a critical hit, this weapon will trip your opponent, forcing them to fall prone. There is no save against this effect.
Immunity to Slippery SurfacesImmunity to Slippery Surfaces: The wearer of this item is not affected when walking on slippery surfaces.
20 Bound to Character on AcquireBound to Character on Acquire: This item is Bound to Character on Acquire Eveningstar, Turn in 15 Commendations: Villagers of EveningstarCommendation: Villagers of Eveningstar: This is a valuable item that can be exchanged for goods if brought to a Challenge Trader. This is a token of favor earned by helping the Villagers of Eveningstar. You can exchange it in Eveningstar for powerful equipment.
Heartseeker VHeartseeker V: On Critical Hit: 11 to 66 Piercing damage from weapons with a x2 Critical Multiplier, 11 to 88 damage from weapons with a x3 Critical Multiplier, and 11 to 110 damage from weapons with a x4 or Greater Multiplier.
Supreme LawSupreme Law: This weapon is infused with the supreme power of law. It does an additional 3 to 18 damage to non-lawful targets and can only be wielded by lawful-aligned characters.
PhlebotomizingPhlebotomizing: This weapon is wickedly sharp and will do an additional 3 to 24 damage to targets that are vulnerable to bleeding.
Heartseeker VIHeartseeker VI: On Critical Hit: 13 to 78 Piercing damage from weapons with a x2 Critical Multiplier, 13 to 104 damage from weapons with a x3 Critical Multiplier, and 13 to 130 damage from weapons with a x4 or Greater Multiplier.
+10 Enhancement Bonus+10 Enhancement Bonus: +10 enhancement bonus to attack and damage rolls.
Knee CrackerKnee Cracker: On Hit: 15% Chance to slow 25% (No Save) for 5 sec (non-bosses only).
ThunderbaneThunderbane: This weapon was crafted in the great Thunderforge before Dragons came. Against constructs and the undead, this weapon's effective enhancement bonus is +8 better than its normal enhancement bonus. It deals an extra 7 to 42 points of damage against the foes.
Forged LightningForged Lightning: On Hit: 2% Chance to do 300 to 500 damage in a blast radius.
Legendary Blinding EmbersLegendary Blinding Embers: This weapon sheds tiny embers that can impair a creatures sight. If you roll a 20 when attacking and confirm the critical hit, the target will become blinded by a burst of fiery sparks.
Pages in category "Aligned items"
This page was last modified 14:59, April 4, 2017 (Update 35.2) by The Sneaky One. Based on work by DDO wiki user Bladedge.


text:
package org.wildfly.swarm.microprofile.metrics.deployment;

import java.lang.annotation.Annotation;
import java.lang.reflect.Type;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Map;
import java.util.Set;

import javax.enterprise.event.Observes;
import javax.enterprise.inject.Default;
import javax.enterprise.inject.spi.AfterDeploymentValidation;
import javax.enterprise.inject.spi.AnnotatedMember;
import javax.enterprise.inject.spi.AnnotatedMethod;
import javax.enterprise.inject.spi.AnnotatedParameter;
import javax.enterprise.inject.spi.AnnotatedType;
import javax.enterprise.inject.spi.Bean;
import javax.enterprise.inject.spi.BeanManager;
import javax.enterprise.inject.spi.BeforeBeanDiscovery;
import javax.enterprise.inject.spi.Extension;
import javax.enterprise.inject.spi.InjectionPoint;
import javax.enterprise.inject.spi.ProcessAnnotatedType;
import javax.enterprise.inject.spi.ProcessProducerField;
import javax.enterprise.inject.spi.ProcessProducerMethod;
import javax.enterprise.inject.spi.WithAnnotations;
import javax.enterprise.util.AnnotationLiteral;
import javax.enterprise.util.Nonbinding;
import javax.inject.Inject;
import javax.interceptor.InterceptorBinding;

import org.eclipse.microprofile.metrics.Metric;
import org.eclipse.microprofile.metrics.MetricRegistry;
import org.eclipse.microprofile.metrics.annotation.Counted;
import org.eclipse.microprofile.metrics.annotation.Gauge;
import org.eclipse.microprofile.metrics.annotation.Metered;
import org.eclipse.microprofile.metrics.annotation.Timed;
import org.jboss.logging.Logger;

/**
 * @author hrupp
 */
public class MetricCdiInjectionExtension implements Extension {

    private static final Logger LOGGER = Logger.getLogger("org.wildfly.swarm.microprofile.metrics");

    private static final AnnotationLiteral<InterceptorBinding> INTERCEPTOR_BINDING = new AnnotationLiteral<InterceptorBinding>() {
    };
    private static final AnnotationLiteral<Nonbinding> NON_BINDING = new AnnotationLiteral<Nonbinding>() {
    };
    private static final AnnotationLiteral<MetricsBinding> METRICS_BINDING = new AnnotationLiteral<MetricsBinding>() {
    };

    private static final AnnotationLiteral<Default> DEFAULT = new AnnotationLiteral<Default>() {
    };

    private final Map<Bean<?>, AnnotatedMember<?>> metrics = new HashMap<>();

    @Inject
    MetricRegistry registry;

    public MetricCdiInjectionExtension() {
        LOGGER.infof("MetricCdiInjectionExtension");
    }

    private void addInterceptorBindings(@Observes BeforeBeanDiscovery bbd, BeanManager manager) {
        LOGGER.info("MicroProfile: Metrics activated");

        declareAsInterceptorBinding(Counted.class, manager, bbd);
        declareAsInterceptorBinding(Gauge.class, manager, bbd);
        declareAsInterceptorBinding(Timed.class, manager, bbd);
        declareAsInterceptorBinding(Metered.class, manager, bbd);

        // It seems that fraction deployment module cannot be picked up as a CDI bean archive - see also SWARM-1725
        bbd.addAnnotatedType(manager.createAnnotatedType(AMetricRegistryFactory.class));
        bbd.addAnnotatedType(manager.createAnnotatedType(MetricNameFactory.class));

        bbd.addAnnotatedType(manager.createAnnotatedType(MeteredInterceptor.class));
        bbd.addAnnotatedType(manager.createAnnotatedType(CountedInterceptor.class));
        bbd.addAnnotatedType(manager.createAnnotatedType(TimedInterceptor.class));
        bbd.addAnnotatedType(manager.createAnnotatedType(MetricsInterceptor.class));
    }

    private <X> void metricsAnnotations(@Observes @WithAnnotations({ Counted.class, Gauge.class, Metered.class, Timed.class }) ProcessAnnotatedType<X> pat) {
        AnnotatedTypeDecorator newPAT = new AnnotatedTypeDecorator<>(pat.getAnnotatedType(), METRICS_BINDING);
        LOGGER.debugf("annotations: %s", newPAT.getAnnotations());
        LOGGER.debugf("methods: %s", newPAT.getMethods());
        pat.setAnnotatedType(newPAT);
    }

    private void metricProducerField(@Observes ProcessProducerField<? extends Metric, ?> ppf) {
        LOGGER.infof("Metrics producer field discovered: %s", ppf.getAnnotatedProducerField());
        metrics.put(ppf.getBean(), ppf.getAnnotatedProducerField());
    }

    private void metricProducerMethod(@Observes ProcessProducerMethod<? extends Metric, ?> ppm) {
        if (!ppm.getBean().getBeanClass().equals(AMetricRegistryFactory.class)) {
            LOGGER.infof("Metrics producer method discovered: %s", ppm.getAnnotatedProducerMethod());
            metrics.put(ppm.getBean(), ppm.getAnnotatedProducerMethod());
        }
    }

    void registerMetrics(@Observes AfterDeploymentValidation adv, BeanManager manager) {

        // Produce and register custom metrics
        MetricRegistry registry = getReference(manager, MetricRegistry.class);
        MetricName name = getReference(manager, MetricName.class);
        for (Map.Entry<Bean<?>, AnnotatedMember<?>> bean : metrics.entrySet()) {
            if (// skip non @Default beans
            !bean.getKey().getQualifiers().contains(DEFAULT)
                    // skip producer methods with injection point metadata
                    || hasInjectionPointMetadata(bean.getValue())) {
                continue;
            }

            String metricName = name.of(bean.getValue());
            registry.register(metricName, getReference(manager, bean.getValue().getBaseType(), bean.getKey()));
        }

        // Let's clear the collected metric producers
        metrics.clear();
    }

    private static <T extends Annotation> void declareAsInterceptorBinding(Class<T> annotation, BeanManager manager, BeforeBeanDiscovery bbd) {
        AnnotatedType<T> annotated = manager.createAnnotatedType(annotation);
        Set<AnnotatedMethod<? super T>> methods = new HashSet<>();
        for (AnnotatedMethod<? super T> method : annotated.getMethods()) {
            methods.add(new AnnotatedMethodDecorator<>(method, NON_BINDING));
        }
        bbd.addInterceptorBinding(new AnnotatedTypeDecorator<>(annotated, INTERCEPTOR_BINDING, methods));
    }

    private static boolean hasInjectionPointMetadata(AnnotatedMember<?> member) {
        if (!(member instanceof AnnotatedMethod)) {
            return false;
        }
        AnnotatedMethod<?> method = (AnnotatedMethod<?>) member;
        for (AnnotatedParameter<?> parameter : method.getParameters()) {
            if (parameter.getBaseType().equals(InjectionPoint.class)) {
                return true;
            }
        }
        return false;
    }

    private static <T> T getReference(BeanManager manager, Class<T> type) {
        return getReference(manager, type, manager.resolve(manager.getBeans(type)));
    }

    @SuppressWarnings("unchecked")
    private static <T> T getReference(BeanManager manager, Type type, Bean<?> bean) {
        return (T) manager.getReference(bean, type, manager.createCreationalContext(bean));
    }
}

redpajama_set_name: RedPajamaGithub