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Home/The Difference
The DifferenceEngenius Team2017-01-27T15:15:09-04:00
At Caldwell Constructors, getting the job done is only the first step. We're also committed to delivering as promised, on time, and on budget.
It is our unparalleled service and value—along with our ability to deliver exceptional, consistent results—that keeps our clients coming back.
The Caldwell difference is made possible by our talented, qualified team and network of trusted construction partners. We are selective in choosing our subcontractors and only work with those who share our commitment and approach to meeting clients' needs. We treat each project like we are the owners and keep that in mind throughout the process.
"Caldwell Constructors is an absolutely wonderful company! They worked with us on a large reconstruction project that we held with great passion. They communicated professionally and frequently keeping us up to date on every aspect of our project. I highly recommend Caldwell Constructors! They are great Christian people who know their profession very well!"
– Denise Holland, Harvest Hope
We're passionate about giving back to our community. That's why when we learned about a family whose home was extensively damaged by a fire that was not covered by insurance, we jumped in to help. Our team pulled together resources from contributing subcontractors and suppliers to help rebuild the house "Habitat style".
We were privileged to be able to spend two weeks removing the damaged structure. Once the demo was completed, the entire Caldwell team had an "all hands on deck" work weekend. We installed all of the donated roof trusses and got the house "dried-in" by the end of the weekend. The homeowner and family enjoyed helping out too!
Kevin Whitaker
Caldwell Constructors was able to build a new Cadillac showroom at Kevin Whitaker Chevrolet Cadillac on Laurens Rd in Greenville. The architectural drawings showed the new building sitting on the location of an active detention basin. However, Caldwell had the idea to build the showroom on an elevated concrete slab to enclose the pond inside a basement structure instead of filling in the pond and moving the detention basin to an underground system below the parking lot used for sales.
This idea lead to a design-build approach where Caldwell Constructors selected a structural and civil design team to help finalize the design of the structure. This creative solution allowed Kevin Whitaker Chevrolet to save over $100,000 in construction cost and also allowed the dealership to retain the 100+ car inventory that would have been displaced by an underground system.
BMW Assembly Line Conversion
Caldwell Constructors was brought in to help build 3,000 linear feet of wide conveying system trenches and related equipment foundations required for the assembly line conversion in the active manufacturing facility. Caldwell served as the concrete contractor in a joint venture with Foundations Unlimited and was instrumental in the successful completion of the project. Caldwell's leadership with scheduling the 24 hours a day/7 days a week work week lead to an early completion of a project scheduled during the holidays.
Tower Place
Caldwell was selected as the design-builder to make significant structural repairs to a partially completed 5-story mixed-use building in downtown Clemson. The previous contractor over-billed the owner by more than $100,000 and did not even come close to completing the building. Even worse, the structure was not built to code and was not safe for occupancy.
Caldwell Constructors hired a structural engineer to help with a solution to the inadequate structure. A 5-story exterior concrete and masonry shear wall was added to stabilize the structure, and steel plates and angles were installed and welded together throughout portions of the building to create a stronger floor system. The result was a structurally sound building that was extremely safe for occupancy.


There's nothing quite so satisfying as a multifunctional tool, appliance or home product when space is in short supply. Particularly when said object manages two unlikely combined tasks. Enter the Hot-Pot BBQ ($124) from Black+Blum, a terracotta pot (14.6 X 10.6 in.) whose top portion is ideal for growing herbs and whose middle conceals a small, stainless steel grill perfect for an intimate BBQ on a small terrace or balcony. Tongs (with hideaway hole) included.
Electrolux is getting serious about its environmental commitments—encouraging people to recycle old appliances through their Swap and Save program, and developing a line of lovely looking Energy Star-rated washing machines. The Energy Star-approved Front-Load Washer with IQ Touch Controls ($1,399) features an 18-minute "Fast Wash Cycle" and LED lighting. It's 75% more energy-efficient and uses 56% less water than top-loading models, according to their site.
Recommended by eco-celeb Ed Begley, Jr. both on his reality show "Living with Ed" and in his Guide to Sustainable Living, the Cool-N-Save ($99.95) employs the same cooling strategy for home air conditioners that commercial buildings use. The flapper valve attaches to the top of most home central air conditioning units and activates misters when the A/C is on. Water (connected by an outdoor spigot via a filter and tubing) is released in a fine mist around the A/C, lowering surrounding air temperatures. Your A/C doesn't have to work as hard to cool your home, saving energy and money (the company claims it can reduce your monthly electricity bills by up to 30%).


Dryer Balls are a must-have for every laundry room! Constructed from PVC plastic, they have specially-designed tips that retain heat and massage the fibers in your clothes -- opening them up and making them soft and fluffy without the use of chemicals. Just add the Dryer Max Dryer Balls in the dryer with your wet clothes and you'll have softer, dryer-fresh clothes in no time! Two per pack.
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Click the button below to add the Tumbling Dryer Balls to your wish list.


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Q: phpword export text by using variable and text this is the statement that im trying to combine.

$section->addText("Order No", 'rStyle', 'pStyle');
$section->addText("$x", 'rStyle', 'pStyle');

can it be something like
$section->addText("Order No.'$x'.", 'rStyle', 'pStyle');

A: Please check PHP String Operators
$section->addText("Order No.".$x, 'rStyle', 'pStyle');

redpajama_set_name: RedPajamaStackExchange


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Paul Koering (born December 17, 1964) is a Minnesota politician who serves on the County Board of Crow Wing County, Minnesota. He is a former member of the Minnesota Senate from Fort Ripley. A Republican, he represented District 12, which includes all or portions of Crow Wing and Morrison counties, including the city of Brainerd. A liquor store owner, funeral car service owner, and small farmer, he served two terms, but was defeated by former Rep. Paul Gazelka in the August 10, 2010, Republican primary election. He was elected to the Crow Wing County Board in 2012 and re-elected unopposed in 2016; he represents the first district which contains the southern portion of Crow Wing County, including Fort Ripley, Roosevelt Township, Oak Lawn Township and the extreme northeast portion of the city of Brainerd.

Koering was first elected to the senate in 2002, defeating longtime senator and Democrat Don Samuelson, who had been the senate president. He was re-elected in 2006, overcoming both primary and general election opponents.

Koering was a member of the senate's Agriculture and Veterans Committee, the Capital Investment Committee, the Health, Housing and Family Security Committee (on which he was the ranking minority party member), and the Higher Education Committee. He also served on the Finance subcommittees for the Agriculture and Veterans Budget and Policy Division, for the Health and Human Services Budget Division, and for the Higher Education Budget and Policy Division.

Koering's positions tended to be conservative, including opposition to tax increases, opposition to abortion, support for tougher criminal sentences, and support for broad gun rights, including support for a general right to carry a concealed firearm. In a notable exception to that conservatism, he has sided with Senate Democrats in opposing restrictions on gay rights. He is believed to be the first openly gay Republican elected official in Minnesota, and was the only openly gay Republican member of the Minnesota Legislature to date.

Koering effectively 'outed' himself by breaking from the Republican Party line on a procedural vote in the Minnesota Senate. The pivotal moment came on April 7, 2005, when then-State Senator Michele Bachmann used procedural tactics that would have forced a vote on her constitutional amendment to ban same-sex marriage in Minnesota. This vote coincided with the gay and lesbian justFair lobby day at the Capitol, as well as the second anniversary of the death of Koering's mother. Koering explicitly stated his sexual orientation a week later. Some public commentary questioned how this disclosure would affect his prospects for re-election in 2006 in a rural, right-leaning district, but he won by over 12 percentage points. However, he disappointed pro-same-sex marriage advocates by voting against the Minnesota Marriage and Family Protection Act, a DFL-backed proposal to legalize same-sex civil unions in the state.

On June 15, 2010, gay news site TheSword.com stated that Koering went on a dinner date in Brainerd with gay pornographic actor Brandon Wilde. He admitted to the date with Wilde and told The Sword, "I don't see anything wrong with going out with him." In light of the story, the Minnesota Republican Party further distanced themselves from Koering. After losing the August 2010 primary election to Tea Party movement-backed candidate Paul Gazelka by a vote of 57 to 43 percent, he announced his withdrawal from the Republican Party, backing DFL Party candidate Taylor Stevenson's bid for the District 12 seat.

Koering drew national criticism for his comments regarding people who have died from drug overdose. He was quoted by the Brainerd Dispatch as saying, "I don't know why we're in such a big hurry to save somebody like this. I guess it sounds kind of harsh, but it kind of gets rid of a problem, in my mind," during the March 19, 2019 Crow Wing County Board meeting.

References

External links

Senator Koering Web Page
Minnesota Public Radio Votetracker: Senator Paul Koering
Paul Koering Campaign Web Site
Koering Not Concerned About Overdose Deaths

1964 births
Living people
People from Brainerd, Minnesota
Republican Party Minnesota state senators
Gay politicians
LGBT Christians
LGBT state legislators in Minnesota
21st-century American politicians

redpajama_set_name: RedPajamaWikipedia


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Heischeid ist eine Ortschaft der Gemeinde Reichshof im Oberbergischen Kreis im nordrhein-westfälischen Regierungsbezirk Köln in Deutschland.

Lage und Beschreibung
Heischeid liegt westlich der Wiehltalsperre, die nächstgelegenen Zentren sind Gummersbach (31 km nordwestlich), Köln (65 km westlich) und Siegen (48 km südöstlich).

Geschichte

Erstnennung
1487 wurde der Ort das erste Mal urkundlich erwähnt: "Der Kremer von Hyschyt wird in der Darlehnsliste für Hz. Wilhelm III. v. Berg genannt."

Die Schreibweise der Erstnennung war Heyschyt.

In Heischeid steht ein über hundert Jahre alter Feuerwehrturm, der heutzutage aber nicht mehr von der Feuerwehr genutzt wird. Außerdem stehen in Heischeid mehrere denkmalgeschützte Fachwerkhäuser.

Vereinswesen
 Freiwillige Feuerwehr Reichshof Löschzug Heischeid (welcher nun Brüchermühle angehört)
 Dorfgemeinschaft Heischeid

Einzelnachweise

Weblinks
 Website der Dorfgemeinschaft Heischeid

Ortsteil von Reichshof
Ersterwähnung 1487


October 23, 2018 5:45 am - Public favor can shift quickly, especially if you have a competitor they can switch to instead. You need to do all you can to nurture and develop a positive reputation and to keep it.
Your reputation is everything in business. That reputation, however, will depend on who you are as a core company. You might find your business can weather the storm of a scandal or two if the product or service you sell is just so vital to your customer's everyday life. Just because people love your product, however, it never means you are impenetrable. Public favor can shift quickly, especially if you have a competitor they can switch to instead. You need to do all you can to nurture and develop a positive reputation and to keep it. It's the only way to stay successful and to keep the doors of opportunity open.
In order to weather the storms of the future, you must build a solid foundation. In business, this foundation will be your selling point. It will be what customers, clients, and even other businesses can come to rely on you for. Perhaps it is your speedy, fast delivery, or your great customer service, or even your budget prices. Whatever you have chosen to set yourself apart from your competition, stick with it and market it every chance you get. That way, if something does happen, your customers can say, "okay, but they're still good at" and continue to use your services once they have been satisfied in the steps you have taken to fix the problem at hand.
News agencies pounce on large-scale security breaches. This can throw a wrench in the trust you have been nurturing for years between you and your clients. If sensitive data was stolen, like credit card information or perhaps their billing address, then you are in even more trouble. You need to invest in UTM firewalls and other anti-virus software now, before a huge breach in trust occurs. Simply visit Sonic Wall today and see what tools and programs are the best fit for your company. You want to protect yourself, and your customers from cybercrime and in order to do that you need professional tools of the trade.
A great way to boost your reputation is to do good work for your community - global or local. It's not only how you can cater to the wants and wishes of younger generations who are more globally conscious, but it is also how you can do your part to bolster the international community and even get a bit of profit back.
No matter what your selling point, product, or service, you have to feel every single one of your clients feel like they are royalty. This doesn't mean caving into every demand, but it does mean doing everything you can to make them feel good about themselves.
Nurturing a positive business reputation takes a lot of time and effort. It can also be ruined in a day. That is why you need to build up a level of consistency that can be used to help appease your customers that your disgrace or security breach was just a fluke, and that you truly do care for them and their security.


Ticks look similar to spiders, but they feed on blood. To feed, they bite onto an animal or human and hang on with their mouth, they will usually feed for a few days and drop off by themselves when they are full. Ticks can carry and transfer diseases when they bite so it is best they are removed as soon as you notice them on either yourself or your pet.
Once a tick is attached to the skin and feeding, it will look like an odd bump on the skin, it is sometimes easier to notice them by feel, as they can be quite small.
Ticks are most often found in long grassland, marshy areas and woodland, often where there are lots of wildlife or farm animals.
If you pull a tick straight out, you may risk the tick's head staying attached to your pet's skin and this can cause infection. It is best to pull a tick out with a twist action or you can purchase a tick removal device which is also effective. Try not to damage the tick in any way as this will increase the risk of infection. Once the tick has been removed, give the bite area a good wash. To kill the tick, put it in rubbing alcohol or wrap it in sticky tape to smother it. When handling a tick it is best to use gloves and never squash them as this increases the chance of spreading harmful illnesses.
If you are taking your dog for a walk in long grassy or wooded areas, it is best you keep your skin well covered and check your dog for ticks afterwards and give them a good brush too to remove any loose ticks which may have clung onto their fur. You can also use spot on tick treatment, tablets and collars which will repel ticks.
We stock Advantix which is monthly treatment for the prevention and treatment of flea, tick, sand flies, stable flies and mosquitoes infestations. We also sell Seresto which is an innovative flea and tick collar which protects pets from fleas and ticks for up to 8 months – without the need to remember monthly applications. Ask our reception or clinical team for more information on these treatments.
Ticks in this country most commonly transport Lyme disease from host to host. The symptoms of Lyme disease are a circular rash, lameness, joint and muscle pain and tiredness, if left untreated it can progress to more serious conditions. Lyme disease, if caught in its early stages can be treated with antibiotics.
Babesiosis is another disease which can be spread by tick bites. It affects dogs and although quite rare in the UK, can cause death in dogs. The symptoms are depression, a loss of appetite, pale gums, a fever and a swollen abdomen.
For more advice on ticks, pop into The Vet at any time during our opening hours and ask the team!


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New soccer/lacrosse and field hockey stadiums to propel teams to new heights
The university community celebrated the opening of our new field hockey and lacrosse/soccer stadiums with a ribbon-cutting ceremony on September 25.
The soccer and lacrosse complex seats 1,500 fans and uses an infill turf playing surface while the field hockey complex features seating for 500 people as well as an artificial turf field and an irrigation system.
"We are grateful for the commitment that President John L. Lahey has made to Quinnipiac Athletics as we strive to be one of the top athletic departments in the country," Director of Athletics and Recreation Greg Amodio said. "These new fields will provide our varsity teams and student-athletes with premier facilities that rival those of our peer institutions."
Both venues host home and visitor locker rooms, team rooms, training and equipment rooms, first-aid stations, restrooms for spectators as well as broadcast-ready press boxes and seating for professional and student media.
"The two venues work in tandem to create a unified athletic complex that also safeguards the adjacent wetlands," said Centerbrook Partner Jeff Riley, FAIA. "Abundant plantings and low- profile structures will merge harmoniously with the wooded setting."
This new athletic complex joins the celebrated TD Bank Sports Center, now in its 11th season, as the home of the nationally ranked men's and women's ice hockey programs as well as the men's and nationally ranked women's basketball teams.
Quinnipiac accounting students offer free tax help
Quinnipiac student named 2023 National Engineering Intern Student of the Year
Dean Brown on why QU Law will no longer participate actively in US News & World Report rankings
Provost's Spring 2023 Update

redpajama_set_name: RedPajamaCommonCrawl


"McGregor's character paradoxically gets too much and not enough. Swede feels clogged with sentiment for his daughter, with little room for other emotions."
There's an unfortunate whiff Truman Show fakery about Ewan McGregor's first foray into directing, which suffers from many of the similar problems that plagued Meg Ryan's debut Ithaca last year - only here, they are much more acute. The story, based on the novel by Philip Roth, is a sweeping tale of America from the Forties to the Seventies as seen through the eyes of a single family, whose family businessman father watches as his daughter becomes radicalised and then get involved with domestic terrorism.
The idea of children being drawn into violence as a solution is at least as pertinent now as it was then but John Romano's screenplay never gets beyond skimming the surface of the story, gliding over the emotions that it should be delving into in order to reach the next 'event'.
McGregor stars in the central role of Jewish glove maker Seymour 'Swede' Levov, a man who, we learn in a framing high school reunion story, seemed in his youth to have been blessed with all the gifts, including sporting prowess, a (gentile) beauty queen bride and a successful business, run by his father, just waiting for him to be ready for it.That's how his former classmate Nathan Zuckerman (David Strathairn) remembers him anyway, so he is shocked to learn from Swede's brother Jerry (Rupert Evans) that the once golden boy has died.
With stage set, the film spins into flashback to show Swede living the equivalent of the American Dream - which, as can only happen in fiction, encompasses both town manufacturing and countryside farm living. The only vague crimp in the lives of he and his wife Dawn (Jennifer Connelly) is the fact that their daughter Merry (played impressively in childhood by Ocean James and Hannah Nordberg) has a pronounced stutter. As Merry (now played by Dakota Fanning) becomes a young woman, she is increasingly obsessed with the Vietnam War and, finding companionship with a cabal of friends in New York City, rushes towards a watershed moment that will see her flee the life she has known, detonating an emotional bomb at the heart of her parents' lives.
McGregor's character paradoxically gets too much and not enough. Swede feels clogged with sentiment for his daughter, with little room for other emotions. Dawn, meanwhile - through no fault of Connelly's - is reduced to histrionics with no backbone, so that we can see the end result of her psychological trauma without ever getting a sense of what lies beneath. Part of the problem is the film's look. In early scenes smoothing is used to give the older cast the appearance of younger people and there is a similar glossiness to the whole feel of the film, as though everything has been newly minted rather than lived in.
This air of unreality only serves to further undermine the emotional eddy and flow, so that as Fanning delivered what should have been a heartfelt speech to the father who has been hunting her for years, several people in the cinema I saw this in got a fit of the giggles. Romano also insists on putting little flags in the script, as though he doesn't trust the audience to understand, so when a borderline laughable conversation Swede has with a young unstable firebrand Rita Cohen (Valorie Curry) comes along, it already carries far too much weight, meaning that when the script loops back to it later, the pay-off falls flat.
The music cues are also of the in-your-face variety, such as Buffalo Springfield's over-used For What Its Worth, over scenes of real-life news footage, which has the feeling of being dumped into the film rather than organically woven in.
What should be a bristling tension between extremism and moderation, classes and races - hinted at in the film's best scenes between Swede and his factory secretary (Uzo Aduba) - is all too often sacrificed in favour of the much less interesting, though simpler to portray, father/daughter issues. McGregor, like many actors, has no problem getting performances from his cast but the canvas here would be a big one to fill even for an experienced director and there is no hiding place for his inexperience in terms of narrative flow and creative framing. He needs to think smaller.
Seymour "Swede" Levov, a once legendary high school athlete, is now a successful businessman married to Dawn, a former beauty queen. But turmoil brews beneath the polished veneer of Swede's life.


On the sixth day of our vacation, we had an important decision to make: should we spend the whole day and night in Maryland and drive into DC in the morning for our return flight home, or should we spend the night near DC which meant leaving Maryland early? It was a three hour drive back to DC, another trip over one of the scariest bridges in the world, we needed to turn in our Dodge Grand Caravan... and what happened if we broke down, hit traffic, or someone's bladder neared its max fill line? Or more likely: what happened if I made another wrong turn in DC that sent us back into a neverending loop of traffic?
We went to an island of wild horses.
The island in question is called Assateague Island, which is a national park. Upon entering, we made a pit stop at the visitor's center where we loaded up on all the necessary supplies, such as a plush horse for Rosie, which she cuddled and snuggled and OMG IT WAS THE CUTEST THING EVER AND I PROMISED TO BUY HER WHATEVER SHE WANTED.
We had planned on just staying in the car and driving around looking at wild horses, but after only seeing a handful of horses in the distance, we parked on the side of the street and walked around for a bit. After walking over a short hill, we found one of the most beautiful beaches I've ever been on.
Now we should have known that there was a beach there. After all, it's called Assateague Island. But we were just too focused on horses, and not on bathing suits or flip flops. So we weren't dressed for the beach, but we stayed for about thirty minutes and let the kids run around and put their feet in the water. (Or in Peter's case, his feet, legs, torso and head.) We watched people surf and go out on kayaks, and we noticed that the beach goers there were in much better shape than the tourists at the Boardwalk beach.
So just to sum this up: this island had wild horses, fit young people in skimpy clothing, and a beautiful beach. We were basically on a cover of a Danielle Steel novel.
After finally convincing the kids that it was time to go, we started heading back towards DC. Google Maps had three routes for us to choose from, but only one went through Delaware (and saved us nine whole minutes!). I had never been to Delaware before, so I made the executive decision to take that route.
Little did I know, but Delaware is very rural, which I thought made it the most Southern of the Northern states - although Betty says that Dover is an actual city, with city stuff like "things to do" and "other people." And it's pretty small. At 2,489 square miles, Delaware is the second smallest US state by total area. It only took us about an hour to drive through the southern half of the state, and most of what we drove through was rural farmland.
I thought that I'd see the same strip malls and fast food joints like we do in every other city, but Delaware was different. We passed by several red barns that are the idyllic barn that you'd find in a children's book. We saw a lot of corn and what I guess were soybean fields, and a lot of linear move irrigation systems. I liked it. And as an added bonus, we didn't hit any traffic.
Eventually we ended up back in Maryland, where we drove back over the Chesapeake Bay Bridge (named one of the scariest bridges in the world), and this time I could stay in the center lane the whole way over since the bridge going back towards DC has three lanes. For me it was a breeze, but Betty said that the view down to the bay was way scarier this time around than the first time. She was genuinely terrified.
From there we went south through DC and into Virginia. Our hotel was in Alexandria, which is one of the oldest cities in the US. Specifically, our hotel was in what's known as Old Town - not to be confused with the fancy new town that the whippersnappers built in the 1800's and later. Old Town was originally a part of Virginia, then ceded to the US government to form part of DC, then given back to Virginia. I had always thought that Alexandria was named after the city in Egypt, but instead it's named after a dude named Philip Alexander that had a lot of land. The main things that we did in Alexandria were eat (at the hotel), swim (at the hotel), and vacuum out all the sand and food from our rental car so that we wouldn't get charged a cleaning fee. It was as if we had taken all the sand from Assateague Island as well as the beach near the Boardwalk, crumbled some Thrasher's fries into the sand, rolled it up with Dumser's ice cream and dumped the remains of a Boog's corndog on it, then rolled around in it in the rental car - over the carpet, up the seats and into the trunk. But after a few dollars worth of a gas station vacuum, we got the van looking like it had only had to withstand an atomic bomb blast while inside a convenience store instead of having to withstand three kids on vacation, which frankly was a big improvement.
So we had started the day in Maryland, drove through Delaware, drove through a few streets of DC and finally made it to Alexandria, Virginia. The kids got to put a checkmark in Delaware and Virginia on their "States I've Been To" map. We saw horses, braved a scary bridge, and never got lost in DC. Not too bad for a day's drive!
Stay tuned for info on our last day!


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Start page / Entry of category "ACTA"
Information slides
ACTA is Dead!
Help Stop the ACTA!
"RIAA-led mob threatens innovation, Senator…
Cool video on the harmfulness of ACTA
Find out about Our issues and goals!
Become a Pirate Join now!
In a 478-to-39 vote, the European Parliament rejected ACTA. For all intents ACTA is dead. Without EU support and with other countries rejecting it, ACTA is unlikely to go anywhere. No doubt parts of it will reappear in other secret draft treaties, especially the Trans Pacific Partnership (TPP) Agreement. But on this Independence Day, we thank all who voiced their opposition to ACTA, especially the European Pirate and Green Parties!
The Anti-Counterfeiting Trade Agreement (ACTA) is a treaty that the US government worked on in secret with other countries to bring the US' draconian copyright laws to other countries. It will: lock us into obsolete copyright and patent laws; criminalize harmless remixes by ordinary users if they achieve 'a commercial scale' (art 2.14.1) which many amateur videos do on sites like Youtube; criminalize legitimate websites by making them responsible for user behavior ('aiding and abetting'...
"RIAA-led mob threatens innovation, Senator warns"
"Web 2.0 Summit Attempts by the content industry to pass legislation like the Protect IP Act are the greatest threat to technology innovation, a senior US Senator told delegates at the Web 2.0 summit in San Francisco." The previous quotes were taken from The Register: A UK based technology news site. A direct link to the full article can be found here: RIAA-led mob threatens innovation, Senator warns
A cool video explaining why the Anti-Counterfeiting Trade Agreement (ACTA) would be harmful to us all. Please forward widely. You can find the video at: http://youtu.be/qlFyoEKV0dE


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Former General Electric Chief Jack Welch Dies at 84
NEXT:ABC Chief Medical Correspondent Dr. Jennifer Ashton Explains Why On-Air Experience Is So Vital at a Time Like This
PREVIOUS:Networks Announce Super Tuesday Coverage Plans
By A.J. Katz on Mar. 2, 2020 - 11:34 AM
Former General Electric chairman and chief executive Jack Welch died late Sunday at the age of 84. The cause of death was renal failure, his wife said this morning.
Welch was GE CEO from 1981-2001 when the conglomerate owned NBC, and launched CNBC in 1989.
During Welch's 20-year run overseeing GE, the company's market value went from $14 billion in 1981 to $400 billion in 2001.
In 1999, Fortune referred to Welch as "manager of the century." However, he also was known as "Neutron Jack" for slashing roughly 100,000 jobs during his tenure.
"Today is a sad day for the entire GE family," GE chairman and CEO H. Lawrence Culp Jr. said in a statement this morning. "Jack was larger than life and the heart of GE for half a century. He reshaped the face of our company and the business world."
Welch was known as a dynamic leader and often made surprise stops at the CNBC newsroom. He would also make countless appearances on TV news over the years, even guest anchoring MSNBC and CNBC programming after he left their parent company just days before Sept. 11.
CNBC-turned-FBN anchor Maria Bartiromo told TVNewser in Jan. 2019 that she considers Welch a mentor. "I learned a lot from Jack Welch in terms of leadership. I remember taking leadership classes at GE, which at the time owned CNBC. I remember one class building essential leadership skills. It was really valuable."
Bartiromo wrote a Jack Welch obit, posted on FoxBusiness.com not long ago.
Another CNBC-turned-FBN anchor Neil Cavuto also considers Welch a mentor, and spoke about his passing during an appearance this morning on FNC's America's Newsroom
On his mid-day FBN show, Cavuto remembers Welch:
Watch the latest video at foxnews.com
Welch was also a friend of Donald Trump's. The president tweeted about his passing this morning:
Jack Welch, former Chairman and CEO of GE, a business legend, has died. There was no corporate leader like "neutron" Jack. He was my friend and supporter. We made wonderful deals together. He will never be forgotten. My warmest sympathies to his wonderful wife & family!
— Donald J. Trump (@realDonaldTrump) March 2, 2020


Description Take advantage of this rare opportunity. Just certified by a local BMW dealership, passes all inspections. BMW cleared the vehicle as having minor repairs and a clean bill of health. Well equipped with the highly coveted In-line 6 cyl TwinPower turbo engine, xDrive, Premium package with Napa Leather, Lumbar support, and Keyless entry, plus Navigation, and Drivers assistant package with Rearview Camera. Very clean inside and out.


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\section{Introduction}
\label{sec:intro}
The real world contains large amounts of complex human-centric activities, which are mainly composed of various human-object interactions (HOIs). In order for machines to better understand these complex activities, we need to detect all these HOIs accurately. To be specific, HOI detection can be defined as detecting the human-object pair and their corresponding interactions in an image. It can be divided into two sub-tasks, instance detection, and interaction understanding. Only if these two sub-tasks are completed can we build a good HOI detector.

\begin{figure}[t]
\begin{center}
\includegraphics[width=.48\textwidth]{fig1.png}
\end{center}
   \caption{The attention fields for two different level predictors in our PR-Net. The first column shows these input images. The second column exhibits the attention fields of instance-level predictor, in which the model concentrates on the extremity region of human and object. The third column exhibits the attention fields of interaction-level predictor, in which the model spreads its scope of attention to the relation-level region.}
\label{fig1}
\end{figure}

Previously, different methods were taken to process these two sub-tasks.  Traditional methods like~\cite{hicodet,qi2018learning,no-frills,li2019transferable} first locates all instances and then extracts their corresponding features with an off-the-shelf object detector like~\cite{ren2017faster,he2017mask}. After that, instance matching and feature fusing approaches are used to construct human-object pairs which are more likely to have interactive relations. These pairs are then sent into the intention parsing network as inputs, and HOI is classified and outpus, so as to obtain the humain-object position and corresponding interactive relation category.  In summary, these traditional two-stage approaches suffer from the isolated training process of instance localization and interaction understanding, so they cannot localize interactive human-object pairs and understand those complex HOI instances.

To alleviate the above problems, multitask learning manners~\cite{liao2020ppdm,Wang2020IPNet,ggnet21,uniondet20,zou2021_hoitrans,chen_2021_asnet,tamura2021qpic,Kim_2021_CVPR} are proposed to complete these two sub-tasks simultaneously. Among these approaches, they~\cite{liao2020ppdm,Wang2020IPNet,ggnet21,chen_2021_asnet,Kim_2021_CVPR} process these two sub-tasks concurrently. Whereas they need an additional complex group composition procedure to match the predictions of these two sub-tasks, which
reduces the computation efficiency. In addition, other one-stage methods~\cite{zou2021_hoitrans,tamura2021qpic} predict human-object pairs and corresponding interactions using one shared prediction head, without needing matching or gathering processes. However, they accomplish instance localization and interaction understanding in a mixed and tied manner. This naive mixed prediction manner can cause inconsistent focus in attentive fields between the instance-level and the relation-level prediction.
This inconsistent focus has caused limited interaction understanding for those hard-negative HOIs, which leads to dissatisfactory HOI detection performance.

To sum up, we propose a new transformer-based approach named Parallel Reasoning Network (PR-Net) to alleviate inconsistent focus of attentive fields for different level prediction. Specificly, two parallel predictos, instance-level predictor and relation-level predictor,are concluded in PR-Net. The former focuses on instance-level localization, and the latter keeps a watchful eye on relation-level semantic understanding. As can be seen from the two examples in the second columns of Figure~\ref{fig1}, PR-Net's attention to instances is focused on the endpoints of human skeleton and the particular edge regions of objects, indicating that the instance-level predictor can accurately locate the localization of human and objects by focusing on these critical extremity regions of instances. From the two examples in the third column of Figure~\ref{fig1}, it can be seen that PR-Net's attention to relational areas is focused on the interaction contact areas between human and objects and some contextual areas containing helpful understanding of the interaction, which indicates that the relational level predictor spreads its vision to relation areas to better understand the subtle relationships between human and objects. In addition, the instance-level queries of our instance-level predictor strictly correspond to the relation-level queries of our relationship-level predictors. So there is no need for any instance-level queries between them, which greatly reduces the computational cost~\cite{tamura2021qpic}.

Our contribution can be concluded in the following three aspects:
\begin{itemize}
    \item[$\bullet$] We propose PR-Net, which leverages a parallel reasoning architecture to effectively alleviate the problem of inconsistent focus in attention fields between instance-level and relation-level prediction. PR-Net achieves a better trade-off between two contradictory sub-tasks of HOI detection. The former needs more local information from the extremity region of instances, the latter is eager for more context information from the relation-level area.
    \item[$\bullet$] With  a decoupled prediction manner, PR-Net can detect various HOIs simultaneously without any matching or recomposition process to link the instance-level prediction and relation-level prediction.
    \item[$\bullet$] Equipped with additional techniques, including Consistency Loss for better training and Trident-NMS for better post-processing, PR-Net achieves competitive results on both HICO-DET and V-COCO benchmark datasets in HOI detection.
\end{itemize}

\section{Related Works}

\subsection{Two-stage Approaches in HOI Detection}
Most two-stage HOI detectors firstly detect all the human and object instances with a modern object detection framework such as Faster R-CNN, Mask R-CNN~\cite{ren2017faster,he2017mask}. After instance-level feature extraction and contextual information collection, these approaches pair the human and object instances for interaction recognition. In the process of interaction recognition, various contextual features are aggregated to acquire a better relation-level semantic representation. InteractNet~\cite{gkioxari2018detecting} introduces an additional branch for interaction prediction,  iCAN~\cite{gao2018ican} captures contextual information using attention mechanisms for interaction prediction. TIN~\cite{li2019transferable} further extends HOI detection models with a transferable knowledge learner.
In-GraphNet~\cite{in_GraphNet_ijcai2020} presents a novel graph-based interactive reasoning model to infer HOIs.
VSGNet~\cite{vsgnet} utilizes relative spatial reasoning and structual connections to analyze HOIs.
IDN~\cite{li2020hoi} represents the implicit interaction in the transformation function space to learn a better HOI semantic.
Hou proposes fabricating object representations in feature space for few-shot learning~\cite{fcl} and learning to transfer object affordance for HOI detection~\cite{atl}. Zhang~\cite{scg} proposes to merge multi-modal features using a graphical model to generate a more discriminative feature.

\subsection{One-stage Approaches in HOI Detection}

One-stage approaches directly detect Human-Object Interactions without complicated coarse-to-fine bounding box regression~\cite{liao2020ppdm,Wang2020IPNet,ggnet21,uniondet20,zou2021_hoitrans,chen_2021_asnet,tamura2021qpic,Kim_2021_CVPR}. Among these approaches, ~\cite{liao2020ppdm,wang2020learning} introduced a keypoint-style interaction detection method which performs inference at each interaction key point. ~\cite{uniondet20} introduced a real-time method to predict the interactions for each human-object union box. Recently, transformer-based detection approach was proposed to handle HOI detection as a sparse set prediction problem~\cite{zou2021_hoitrans,chen_2021_asnet,tamura2021qpic}. Specifically, ~\cite{tamura2021qpic} designed a transformer encoder-decoder architecture to predict Human-Object Interactions in an end-to-end manner directly and introduced additional cost terms for interaction prediction. On the other hand, Kim \etal~\cite{hotr} and Chen \etal~\cite{asnet} propose an interaction decoder to be used alongside the DETR instance decoder. It is equally important for predicting interactions and matching related human-object pairs. These aforementioned one-stage approaches have enormously boosted the performance of Human-Object Interaction Detectors.

\begin{figure*}[htb]
\begin{center}
   \includegraphics[width=.7\linewidth]{fig2.pdf}
\end{center}
\vspace{-1mm}
   \caption{The framework of our PR-Net. It is comprised of four components:\emph{Image Feature Extractor}, \emph{Pairwise Instance Predictor}, \emph{Relation-level Predictor}, \emph{Training and  Post-processing Techniques}.}
  \vspace{-2mm}
\label{fig:2}
\end{figure*}

\section{Proposed Method}
In this section, we present our Parallel Reasoning Network(PR-Net) for HOI detection, which is illustrated in the Figure~\ref{fig:2}. We can know that our PR-Net includes an Image Feature Extractor(CNN backbone and transformer encoder) and two parallel predictors (i.e., Instance-level Predictor and Relation-level Predictor). The two parallel predictors are designed to decode instance information(i.e. human-box, object-box, object-class) and relation information(i.e. relation-box, relation-class) respectively. Next, we introduce the proposed instance-level and relation-level loss functions to learn the location of instances and the interactions within each human-object pair. At last, we introduce the proposed Trident-NMS which is utilized to filter those duplicated HOI predictions effectively.

\subsection{Image Feature Extractor}
\label{img_extractor}
The overall Image Feature Extractor architecture consists of a standard CNN backbone $f_{c}$ and transformer encoder $f_{e}$. The conventional CNN backbone is used to process the input image $x \epsilon  \mathbb{R}^{3\times H \times W}$ to a global context feature map $z\epsilon  \mathbb{R}^{c \times H' \times W'}$, in which typically images are downsampled to $(H', W')$ spatial shape with a dimension of $c$. Then, the global context feature map is serialized as tokens, in which the spatial dimensions of the feature map are collapsed into one dimension, resulting in $H'\times W'$ tokens. Then, the tokens are linearly mapped to $\mathbf{T}=\{ t_i | t_i \epsilon  \mathbb{R}^{c'} \}_{i=1}^{N_q} $, where $N_q=H' \times W'$. Afterward, these tokens are shaped as a sequence to feed into the transformer encoder.

For the transformer encoder, each encoder layer follows standard architecture of transformer, which consists of a multi-head self-attention module and a feed forward network (FFN). Additional position embedding $q_e \epsilon \mathbb{R}^{c' \times H' \times W' } $ is also added to the serialized token to supplement the positional information.  With the mechanism of self-attention, the encoder can map the former global context feature map from CNN to richer contextual information. Finally, the set of encoded image features $\{ d_i | d_i \epsilon  \mathbb{R}^{c'} \}_{i=1}^{N_q} $ can be formulated as visual memory $\mathbf{E}= f_{e}(\mathbf{T},q_e)$. The visual memory $\mathbf{E}$ contains richer contextual information.

\subsection{Instance-level Predictor}
\label{IP}
The Instance-level Predictor includes a standard transformer decoder $f_{ip}$ with just three layers. The decoder response for above visual memory $\mathbf{E}$, according to a set of learnable instance query vectors $\mathbf{Q_p}=\{ q_i | q_i \epsilon  \mathbb{R}^{c'} \}_{i=1}^{N_q} $ which is added with position embedding $p_l \epsilon \mathbb{R}^{c' \times H' \times W'} $. The instance-level queries vectors are trained to learn a more precise location of instances, which focuses more on those local information about location of instances.
The independent predictors are composed of three feed-forward networks (FFNs), including human-bounding-box FFN $\phi_{hb}$, object-bounding-box FFN $\phi_{ob}$, and object-class FFN $\phi_{oc}$, each of which response for decoding instance feature to human-box $\hat{b}^h$, object-box $\hat{b}^o$ and object-class $\hat{c}^o$  respectively. The formulation can be denoted as:

\begin{equation}
	\begin{aligned}
		\hat{b}^h &= \phi_{hb}(f_{ip}(\mathbf{Q_p}, p_l, \mathbf{E})), \\
		\hat{b}^o &= \phi_{ob}(f_{ip}(\mathbf{Q_p}, p_l,  \mathbf{E})), \\
		\hat{c}^o &= \phi_{oc}(f_{ip}(\mathbf{Q_p}, p_l, \mathbf{E})).
		\label{equ:ffn}
	\end{aligned}
\end{equation}

\subsection{Relation-level Predictor}
\label{RP}
We decouple the relation problems from HOI and use a Relation-level Predictor to reason relationships from larger-scale semantics. We propose a relation box to guide the predictor to percept the human-object relationship in the Relation-level Predictor.

The Relation-level Predictor consists of a standard transformer decoder $f_{rd}$ and two independent predictors(FFNs). Another relation-level queries $\mathbf{Q_r}$ and position embedding $p_r$ are randomly initialed and fed into the Relation-level Predictor. One of the predictors $\phi_{ub}$ predicts relation boxes $\hat{b}^u$, the other predictor $\phi_{ac}$ decodes the relation class information $\hat{c}^a$. The relation boxes $\hat{b}^u$ and the relation class information $\hat{c}^a$ can be formulated as Eq.~\ref{equ:ffn2}.

\begin{equation}
	\begin{aligned}
		\hat{b}^u &= \phi_{ub}(f_{dr}(\mathbf{Q_r}, p_r, \mathbf{E})), \\
		\hat{c}^a &= \phi_{ac}(f_{dr}(\mathbf{Q_r}, p_r, \mathbf{E})).
		\label{equ:ffn2}
	\end{aligned}
\end{equation}

\noindent Attributed to the relation boxes, the decoder of Interaction-level Predictor is guided to enlarge the receptive field (as shown in Figure~\ref{fig1}). The relation queries $\mathbf{Q_r}$ can pay attention to the entire area where human and object interact. Thus, the predictor $\phi_{ac}$  can predict a more accurate relation class.

In addiction, to match the relation class information $\hat{c}^a$ with the aforementioned human-box $\hat{b}^h$, object-box $\hat{b}^o$ and object-class $\hat{c}^o$ from the Instance-level Predictor, we ditch the complex matching method like HO pointer in HOTR. Instead, we just match the relation class information $\hat{c}^a$ and the instances information $\hat{b}^h$ \etc one by one in order.
Specifically, for a pair of instances $\{\hat{b}^h_i,\hat{b}^o_,\hat{c}^o_i, i \epsilon N_q\}$, $\hat{c}^a_i$ is the corresponding relation class. In this way, the instance-level query vectors $\mathbf{Q_p}$ and the relation-level query vectors $\mathbf{Q_r}$ represent the same human-object interaction, but have the ability to focus on different receptive field.

\subsection{Loss Functions}
\label{loss_func}
The overall loss functions consist of the instance-level loss and relation-level loss, applied to Instance-level Predictor and Relation-level Predictor, respectively. The instance-level loss supervises the Instance-level Predictor to predict instance-level target, i.e., human-box, object-box, and object-class. The relation-level loss assists the Relation-level Predictor to predict relation-class and relation-box from the larger receptive field.

\subsubsection{The Instance-level loss function} $\mathcal{L}_{IL}$ supervises the instance information, including human-box $\hat{b}^h$, object-box $\hat{b}^o$ and object-class $\hat{c}^o$. The instance-level loss function consists of human-box regression $\mathcal{L}_{hr}$, object-box regression $\mathcal{L}_{or}$ and object-class classification $\mathcal{L}_{oc}$. $\mathcal{L}_{hr}$ and $\mathcal{L}_{or}$ are standard bounding-box regression loss, i.e. L1 loss, to locate the position of human and object.  $\mathcal{L}_{oc}$ is a classification loss to classify the categories of the object. The loss functions can be defined as Eq.~\ref{equ:bbox}.

\begin{equation}
	\begin{aligned}
		\mathcal{L}_{hr} &= \frac{1}{N} \sum_i^N {|| \hat{b}_i^h - b_i^h ||}, \\
		\mathcal{L}_{or} &= \frac{1}{N} \sum_i^N {|| \hat{b}_i^o - b_i^o ||}, \\
		\mathcal{L}_{oc} &= \frac{1}{N} \sum_i^N {\rm{CE}(\hat{c}^o_i, c^o_i)},
		\label{equ:bbox}
	\end{aligned}
\end{equation}

\noindent where CE is cross entropy loss, $c^o_i$ is the ground truth of object class.

The instance-level loss function $\mathcal{L}_{IL}$  can be defined as:

\begin{equation}
	\begin{aligned}
		\mathcal{L}_{IL} = \mathcal{W}_{hr} *\mathcal{L}_{hr} + \mathcal{W}_{or} *\mathcal{L}_{or} + \mathcal{W}_{oc} *\mathcal{L}_{oc}.
		\label{equ:IL}
	\end{aligned}
\end{equation}

\subsubsection{The Relation-level loss function} $\mathcal{L}_{RL}$ supervises the relationship information, i.e., the relation class $\hat{c}^a$, primarily. In addition, auxiliary relation boxes are also supervised to pay attention to the entire area where the interaction happens. Thus, the Relation-level loss function consists of relation-box regression $\mathcal{L}_{ur}$, relation-box consistency loss $\mathcal{L}_{uc}$ and relation-class loss $\mathcal{L}_{ac}$. The $\mathcal{L}_{ac}$ is a classification loss to classify the categories of the interaction.
The relation-box regression loss function $\mathcal{L}_{ur}$ is a L1 loss to resemble the predicted relation boxes and its grounding truth. The grounding truth of relation boxes is the outer bounding box of human and object boxes. The relation-box regression loss function helps the Relation-level Predictor to be aware of the relation feature of human and object.
The consistency loss $\mathcal{L}_{uc}$  are used to keep the consistency of $\hat{b}^h$, $\hat{b}^o$ and $\hat{b}^u$. Specifically, a pseudo relation box $\hat{b}^{ho}$ is generated by taking the outer bounding box of $\hat{b}^{h}$ and $\hat{b}^{o}$. Then, an L1 loss resemble $\hat{b}^u$ and $\hat{b}^{ho}$.
With the relation box, the relation-class loss can supervise better relation semantics.

\begin{equation}
	\begin{aligned}
		\mathcal{L}_{ur} &= \frac{1}{N} \sum_i^N {|| \hat{b}_i^u - b_i^u ||}, \\
		\mathcal{L}_{uc} &= \frac{1}{N} \sum_i^N {|| \hat{b}_i^u - \hat{b}_i^{ho} ||} , \\
		\mathcal{L}_{ac} &= \frac{1}{N} \sum_i^N {\rm{SigmoidCE}(\hat{c}^a_i, c^a_i)}.
		\label{equ:bbox}
	\end{aligned}
\end{equation}

The relation-level loss function $\mathcal{L}_{RL}$  can be defined as:

\begin{equation}
	\begin{aligned}
		\mathcal{L}_{RL} = \mathcal{W}_{ur} * \mathcal{L}_{ur} + \mathcal{W}_{uc} *\mathcal{L}_{uc} + \mathcal{W}_{ac} *\mathcal{L}_{ac}.
		\label{equ:RL}
	\end{aligned}
\end{equation}

In all, the overall loss fucntion $\mathcal{L}$ can be denoted as:

\begin{equation}
	\begin{aligned}
		\mathcal{L} = \mathcal{L}_{IL} + \mathcal{L}_{RL}.
		\label{equ:all}
	\end{aligned}
\end{equation}

\subsection{Inference for HOI Detection}
\label{infer}
The inference process of our PR-Net can be divided into two parts: the calculation of the HOI predictions and the Trident-NMS post-processing technique. \\
\textbf{HOI Prediction} To acquire the final HOI detection results, we need to predict human bounding box, object bounding box, and object class using both instance-level predictions and relation class and relation box using relation-level prediction. Based on the above predictions, we can calculate the final HOI prediction score as below:
\begin{equation}
s^{hoi}_{i} = \{max_ks^o_{i}(k)\} * s^{rel}_{i}
\label{hoi_score}
\end{equation}
Where $max_ks^o_{i}(k)$ means the most probable class score of the $i$-th output object from instance-level predictor; $s^{rel}_{i}$ means the multi-class scores of the $i$-th output interaction from relation-level predictor. Note that each human-object pair can only have one object with certain class, but there maybe exist multiple human-object interactions within one pair. \\
\textbf{Trident-NMS} For each predicted HOI class in one image, we choose to filter its duplicated predictions according to the above calculated HOI prediction scores with our proposed Trident Non Maximal Suppression(Trident-NMS). In detail, if the $TriIoU(i, j)$ between the $i$-th and the $j$-th HOI prediction is higher than the threshold $Thres_{nms}$, we will filter the prediction which has a lower HOI score. And  the calculation of $TriIoU(i, j)$ is as below:

\begin{equation}
\begin{aligned}
     TriIoU(i, j) = & IoU(b^h_i, b^h_j) ^{W_h} \\
                    & \times IoU(b^o_i, b^o_j) ^{W_o} \\
                    & \times IoU(b^{rel}_i, b^{rel}_j) ^{W_{rel}}
\end{aligned}
\label{tnms}
\end{equation}

Where $IoU(b^h_i, b^h_j)$, $IoU(b^o_i, b^o_j)$, $IoU(b^{rel}_i, b^{rel}_j)$ represent the Interaction over Union between the $i$-th and the $j$-th human boxes, object boxes and relation boxes; $W_h$, $W_o$, $W_{rel}$ represent the weights of Human IoU, Object IoU and Relation IoU.

\section{Experiment}

\subsection{Datasets and Evaluation Metrics}
\label{sec:dataset_metrics}
We evaluate our method on two large-scale benchmarks, including V-COCO \cite{gupta2015visual} and HICO-DET \cite{chao2018learning} datasets. V-COCO includes 10,346 images, which contains 16,199 human instances in total and provides 26 common verb categories. HICO-DET contains 47,776 images, where 80 object categories and 117 verb categories compose of 600 HOI categories. There are three different HOI category sets in HICO-DET, which are: (a) all 600 HOI categories (Full), (b) 138 HOI categories with less than 10 training instances (Rare), and (c) 462 HOI categories with 10 or more training instances (Non-Rare).
Following the standard protocols, we use mean average precision $(mAP)$ in HICO-DET~\cite{hicodet} and role average precision $(AP_{role})$ in V-COCO~\cite{gupta2015visual} to report evaluation results.

\subsection{Implementation Details}
\label{sec:imple_detail}
We use ResNet-50 and ResNet-101\cite{resnet} as a backbone feature extractor. The transformer encoder consist of 6 transformer layers with multi-head attention of 8 heads. The number of transformer layers in Instance-level Predictor and Interaction-level Predictor is both set to be 3. The reduced dimension size of visual memory is set to $256$. The number of instance-level and relation-level queries is set to $100$ for both HICO-Det and V-COCO benchmark.
The human, object and relation box FFNs both have $3$ linear layers with ReLU, while the object and relation category FFNs have one linear layer.
During training, we initialize the network with the parameters of DETR~\cite{carion2020endtoend} trained on the MS-COCO dataset.
We set the weight coefficients of bounding box regression, Generalized IoU, object class, relation class and consistency loss to $2.5$, $1$, $1$, $1$ and $0.5$, respectively, which follows QPIC~\cite{tamura2021qpic}. We optimize the network by AdamW~\cite{loshchilov2018decoupled} with the weight decay $10^{-4}$. We train the model for $150$ epochs with a learning rate of $10^{-5}$ for the backbone and $10^{-4}$ for the other parts decreased by $10$ times at the $100$th and the $130$th epoch respectively. All experiments are conducted on the $8$ Tesla A100 GPUs and CUDA11.2, with a batch size of $16$.

We select 100 detection results with the highest scores for validation and then adopt Trident-NMS to filter results further.

\subsection{Overall Performance}
\label{sec:perform}
We summarize the performance comparisons in this subsection.

\textbf{Performance on HICO-DET.}
Table~\ref{tab:hicodet} shows the performance comparison on HICO-DET. Firstly, the detection results of our PR-Net are the best among all approaches under the Full and Non-Rare settings, demonstrating that our method is more competitive than the others in detecting the most common HOIs. It is noted that PR-Net is also preeminent in detecting rare HOIs (HOI categories with less than 10 training instances), because our parallel reasoning network can migrate the non-rare knowledge into a rare domain. Besides, our PR-Net obtains 32.86 mAP on HICO-DET (Default Full), which achieves a relative gain of 9.8\% compared with the baseline. These results quantitatively show the efficacy of our method.

\begin{table}[htbp]
    \centering
    \caption{Results on HICO-DET~\cite{hicodet}. ``COCO'' is the COCO pre-trained detector, ``HICO-DET'' means that the detector is further fine-tuned on HICO-DET.}
    \resizebox{0.45\textwidth}{!}{\setlength{\tabcolsep}{0.8mm}{
    \begin{tabular}{l c c | c c c}
        \hline
                                                 & & & \multicolumn{3}{c}{Default Full}     \\
        Method                                   & Detector & Backbone & Full & Rare & Non-Rare \\
        \hline
        \hline
        \textbf{CNN-based}  & & & & & \\
        VCL~\cite{vcl}                           & COCO     & ResNet-50     & 19.43 & 16.55 & 20.29 \\
        VSGNet~\cite{vsgnet}                     & COCO     & ResNet-152    & 19.80 & 16.05 & 20.91 \\
        DJ-RN~\cite{li2020detailed}                        & COCO     & ResNet-50     & 21.34 & 18.53 & 22.18 \\
        PPDM~\cite{liao2020ppdm}                         & HICO-DET & Hourglass-104 & 21.73 & 13.78 & 24.10 \\
        Bansal~$et~al.$~\cite{bansal2020}        & HICO-DET & ResNet-101 & 21.96 & 16.43 & 23.62 \\
        TIN~\cite{li2019transferable}$^{\rm{DRG}}$       & HICO-DET & ResNet-50      & 23.17 & 15.02 & 25.61 \\
        VCL~\cite{vcl}                           & HICO-DET & ResNet-50      & 23.63 & 17.21 & 25.55 \\
        GG-Net~\cite{ggnet21}	&HICO-DET	&Hourglass-104		&23.47	&16.48&	25.60\\
        IDN$^{\rm{DRG}}$~\cite{li2020hoi}                     & HICO-DET & ResNet-50      & 26.29 & 22.61 & 27.39  \\
        \hline
        \textbf{Transformer-based}  & & & & & \\
        HOI-Trans~\cite{zou2021_hoitrans}	& HICO-DET	&ResNet-50	&23.46& 16.91& 25.41       \\
        HOTR~\cite{Kim_2021_CVPR}	& HICO-DET	&ResNet-50		&25.10& 17.34 &27.42\\
        AS-Net~\cite{chen_2021_asnet}		& HICO-DET			&ResNet-50		&28.87	&24.25	&30.25   \\
        QPIC~\cite{tamura2021qpic}		& HICO-DET		&ResNet-50	&29.07	&21.85	&31.23   \\
        \textbf{PR-Net (Ours)}	& HICO-DET & \textbf{ResNet-50} & \textbf{31.17} & \textbf{25.66} & \textbf{32.82} \\
        \textbf{PR-Net (Ours)}~	& HICO-DET  & \textbf{ResNet-101} & \textbf{32.86} & \textbf{28.03} & \textbf{34.30} \\
        \hline
      \end{tabular}}}
        \label{tab:hicodet}
\end{table}

\textbf{Performance on V-COCO.}
Comparison results on V-COCO in terms of \emph{$mAP_{role}$} are shown in Table~\ref{vcoco}. It can be seen that our proposed PR-Net has a {mAP(\%)} of 62.4, obtaining the best performance among all approaches. Although we do not adopt previous region-based feature learning (e.g., RPNN \cite{zhou2019relation}, Contextual Att \cite{wang2019deep}), or employ additional human pose (e.g., PMFNet \cite{wan2019pose}, TIN \cite{li2019transferable}), our method outperforms these approaches with sizable gains. Besides, our method achieves an absolute gain of 3.6 points, a relative improvement of 6.1\% compared with the baseline, validating its efficacy in the HOI detection task.
\begin{table}[htbp]
\centering
\caption{Performance comparison on V-COCO dataset.}

\resizebox{0.45\textwidth}{!}{

\begin{tabular}{lccc}
\toprule
Method & Backbone Network & $\operatorname{AP}^{S1}_{role}$ & $\operatorname{AP}^{S2}_{role}$  \\ \hline
\textbf{CNN-based}   & & & \\
  VSGNet~\cite{vsgnet}  & ResNet-152  &51.8  &57.0\\
  PMFNet~\cite{wan2019pose}	  & ResNet-50-FPN  &52.0  &-\\
  PD-Net~\cite{zhong2020polysemy}   & ResNet-152-FPN  &52.6  &-\\
  CHGNet~\cite{wang2020contextual}	 & ResNet-50-FPN &52.7  &-\\
  FCMNet~\cite{fcm20}	 & ResNet-50  &53.1  &-\\
  ACP~\cite{kim2020detecting} & ResNet-152	&53.23  &-\\
  IDN~\cite{li2020hoi}	 & ResNet-50   &53.3  &60.3\\
  GG-Net~\cite{ggnet21}  & Hourglass-104 &54.7  &-\\
  DIRV~\cite{fang2020dirv}		 &  EfficientDet-d3  &56.1  &-\\
\midrule
\textbf{Transformer-based}  & & & \\
  HOI-Trans~\cite{zou2021_hoitrans}		 &  ResNet-101  &52.9  &-\\
  AS-Net~\cite{chen_2021_asnet}	 & ResNet-50  &53.9  &-\\
  HOTR~\cite{Kim_2021_CVPR} 	 & ResNet-50  &55.2  & 64.4\\
  QPIC~\cite{tamura2021qpic}  	 & ResNet-50 &58.8  &61.0 \\
\textbf{PR-Net (Ours)}~ & \textbf{ResNet-50} & \textbf{61.4} & \textbf{62.5} \\
\textbf{PR-Net (Ours)}~ & \textbf{ResNet-101} & \textbf{62.9} & \textbf{64.2}  \\
\bottomrule
\end{tabular}}

\label{vcoco}
\end{table}

\subsection{Ablation Analysis}
\label{sec:ablation}
To evaluate the contribution of different components in our PR-Net, we first conduct a comprehensive ablation analysis on the HICO-DET dataset. Next, we analyze the impact of the number of different-level predictors. At last, we analyze the effects of different post-processing manners.\\

\setlength{\tabcolsep}{4pt}
\begin{table}[htbp]
\begin{center}
  \caption{Ablation analysis of the proposed PR-Net with the backbone of ResNet-101 on HICO-DET test set. Parallel Predictor means we parallelly predict instance-level locations and relation-level semantics. Consistency Loss means we constrain the union box of the human-object pair and the relation box to be consistent. Trident-NMS means duplicate filtering through human, object, and relation bounding boxes.

   }
\small
\resizebox{0.45\textwidth}{!}{
\begin{tabular}{@{}ccccccc@{}}
\hline
\multirow{2}{*}{Parallel Predictor} & \multirow{2}{*}{Consistency Loss} & \multirow{2}{*}{Trident-NMS} &  \multicolumn{3}{c}{HICO-DET}\cr\cline{4-6}
&&&Full  &Rare &NonRare \cr
\hline\hline
- & - & - & 29.90 & 23.92 & 31.69 \\
\checkmark & - & - & 31.62 & 25.43 & 33.47 \\
\checkmark & \checkmark & - & 31.87 & 27.59 & 33.14 \\
\checkmark & \checkmark & \checkmark & 32.86 & 28.03 & 34.30 \\
\hline
\end{tabular}}

  \label{pr_3compo}
\end{center}
\end{table}
\setlength{\tabcolsep}{1.4pt}

\textbf{Contribution of different components.} Compared with our baseline~\cite{tamura2021qpic}, the performance improvements of our PR-Net are from three components: Parallel Predictor, Consistency Loss, and Trident-NMS. From Table~\ref{pr_3compo}, we can know the contribution of different components. Among these components, Parallel Predictor is our core approach. With that, we can observe a noticeable gain of mAP in HICO-DET by 1.72. It proves that the parallel reasoning structure can significantly improve instance localization and interaction understanding for an HOI detection model. Additionally, we design a consistency loss between the union box of the human-object pair and the relation box, which can contribute about 0.25 mAP gain in the HICO-DET test set. It shows that it is meaningful and helpful to constrain the union region of instance-level predictions and the relation region of relation-level predictions. At last, we design a more effective post-processing technique named Trident-NMS, which brings about 1.0 mAP gain in the HICO-DET test set. It reveals that the set-prediction method can also benefit from duplicate filtering technique and post-processing technique like NMS is essential for HOI detection.\\

\textbf{Impacts of different numbers of parallel predictors.} In our PR-Net, two parallel predictors are significant for HOI detection, and we detailedly analyze the impact of different numbers of parallel predictors. From Table~\ref{dec_num}, we can know that equipped with three layers of instance-level predictor and relation-level predictor, our PR-Net can acquire the best mAP performance in the HICO-DET test set. It reveals that our PR-Net can significantly outperform the baseline QPIC~\cite{tamura2021qpic} without additional computational cost. Interestingly, we can also observe that even with only one layer of parallel predictors, our PR-Net can also outperform the baseline equipped with a six-layer predictor.\\

\begin{table}[htbp]
\centering
\caption{ Ablation analysis of the number of instance-level predictor $N_{dec}$ and the number of relation-level predictor $N_{reldec}$.}
\resizebox{0.45\textwidth}{!}{
\begin{tabular}{lcccccc}
\toprule
approaches & Backbone    &   $N_{dec}$ &  $N_{reldec}$    & Full & Rare & Non-Rare \\ \hline
QPIC(Baseline)~\cite{tamura2021qpic}   & ResNet50     &   6   & -   & 29.07 &
21.85 & 31.23 \\
PR-Net(Ours) & ResNet50     &   1   & 1   & 29.64 & 24.18 & 31.27 \\
PR-Net(Ours) & ResNet50     &   3   & 3   & \textbf{31.17} & \textbf{25.66} & 32.82 \\
PR-Net(Ours) & ResNet50     &   6   & 6   & 31.04 & 24.87 & \textbf{32.89} \\
\hline
QPIC(Baseline)~\cite{tamura2021qpic} & ResNet101    &   6   & -   & 29.90 & 23.92 & 31.69 \\
PR-Net(Ours) & ResNet101    &   1   & 1   & 30.26 & 23.27 & 32.34 \\
PR-Net(Ours) & ResNet101    &   3   & 3   & \textbf{32.86} & \textbf{28.03} & \textbf{34.30} \\
PR-Net(Ours) & ResNet101    &   6   & 6   & 32.52 & 27.04 & 34.16 \\
\bottomrule
\end{tabular}}
\label{dec_num}
\vspace{-0.3cm}
\end{table}

\textbf{Effects of different implements of Trident-NMS.}
In Table~\ref{tnms_table}, we analyze the effects of different implements of Trident-NMS. We find that Product-based Trident-NMS performs better than Sum-based Trident-NMS. Additionally, we can also observe that when the weight of Human-IoU in $TriIoU$ increases, the HOI detection performance will be better. This reveals that human box duplication is more frequent than that of object box or relation box. In summary, with either the Product-based or Sum-based $TriIoU$ calculation, we should pay more attention to the non-maximal suppression of the human box.\\

\setlength{\tabcolsep}{4pt}
\begin{table}[h]
\begin{center}
\caption{Ablation analysis of the Trident-NMS module on HICO-DET test set.
Product means we calculate $TriIoU$ by multiplying these weighted Human-IoU, Object-IoU, and Relation-IoU.
Sum means we calculate $TriIoU$ by adding all these weighted Human-IoU, Object-IoU, and Relation-IoU.
$W_{h}$, $W_{o}$, $W_{rel}$ represent the weights of Human-IoU, Object-IoU and Relation-IoU respectively.
$Thres_{nms}$ means the threshold of non-maximum suppression.}
\small
\resizebox{0.45\textwidth}{!}{
\begin{tabular}{@{}ccccccccc@{}}
\hline
\multirow{2}{*}{Product} &
\multirow{2}{*}{Sum} &
\multirow{2}{*}{$W_{h}$}&
\multirow{2}{*}{$W_{o}$}&
\multirow{2}{*}{$W_{rel}$}&
\multirow{2}{*}{$Thres_{nms}$}&
\multicolumn{3}{c}{HICO-DET}\cr\cline{7-9}
&&&&&&Full  &Rare &NonRare \cr

\hline\hline
- & -          & -   & -    & -   & -   & 31.87 & 27.59 & 33.14  \\
- & \checkmark & 0.33 & 0.33  & 0.33 & 0.5 & 30.61 & 27.00 & 31.69 \\
- & \checkmark & 0.33 & 0.33  & 0.33 & 0.7 & 32.53 & 27.88 & 33.91 \\
- & \checkmark & 0.4 & 0.4  & 0.2 & 0.7 & 32.63 & 27.96 & 34.02 \\
- & \checkmark & 0.5 & 0.4  & 0.1 & 0.7 & 32.66 & 27.91 & 34.00 \\
- & \checkmark & 0.6 & 0.3  & 0.1 & 0.7 & 32.56 & 27.70 & 34.01 \\
\hline
\checkmark & - & 1.0 & 1.0  & 1.0 & 0.5 & 32.77 & 27.98 & 34.20 \\
\checkmark & - & 1.0 & 1.0  & 0.5 & 0.5 & 32.81 & 28.02 & 34.25 \\
\checkmark & - & 0.5 & 0.5  & 0.5 & 0.5 & 32.61 & 27.65 & 34.08 \\
\checkmark & - & 0.5 & 1.0  & 0.5 & 0.5 & 32.61 & 27.67 & 34.09 \\
\checkmark & - & 1.0 & 0.5  &  0.5 & 0.5 & {\bf 32.86} & {\bf 28.03} & {\bf 34.30}  \\

\hline
\end{tabular}}
\label{tnms_table}
\end{center}
\end{table}
\setlength{\tabcolsep}{1.4pt}

\subsection{Visualization of features}
\label{sec:t_sne_sec}
Using the t-SNE visualization technique~\cite{maaten2008visualizing}, we visualize 20000 samples of output feature. These object and interaction features are extracted from the last layer of Instance-level Predictor and Relation-level Predictor in our PR-Net, respectively. From the Figure~\ref{fig:t_sne}, we can observe that our PR-Net can obviously distinguish different class of objects and interactions. Interestingly, from this visualization of features, our PR-Net can even learn better the complex interaction representations then the object representations which benefits from our advantageous parallel reasoning architecture.
\begin{figure}[h]
\begin{center}
\includegraphics[width=0.45\textwidth]{t_sne.png}
\end{center}
\caption{Visualization of object features and relation features on HICO-DET dataset via t-SNE technique. Left is object features and right is relation features.}
\label{fig:t_sne}
\end{figure}

\subsection{Qualitative Examples}
\label{sec:quality}
From Figure~\ref{fig:visual_pics}, we can observe that our PR-Net can accurately detect both human box, object box, and relation box as well as their corresponding interactions. From the first row and second column of Figure~\ref{fig:visual_pics}, we can know that our PR-Net can precisely distinguish which man is riding the horse in the image. From the second row and third column of Figure~\ref{fig:visual_pics}, our PR-Net can precisely detect those subtle and indiscernible HOIs. In summary, our PR-Net can correctly detect those complex and hard HOIs.
\begin{figure}[h]
\begin{center}
\includegraphics[width=0.4\textwidth]{quality_analysis.png}
\end{center}
\caption{Visualization of some HOI detection examples (Top 1 result) detected by the proposed Parallel Reasoning Network on the HICO-DET test set.}
\label{fig:visual_pics}
\end{figure}

\section{Conclusion}

In this paper, we propose a new Human-Object Interaction Detector named Parallel Reasoning Network(PR-Net), which consists of an instance-level predictor and a relation-level predictor, to alleviate the problem of inconsistent focus in attentive fields between instance-level and interaction-level predictions. In addition, our PR-Net achieves a better trade-off between instance localization and interaction understanding. Furthermore, equipped with Consistency Loss and Trident-NMS, our PR-Net has achieved competitive results on two main HOI benchmarks, validating its efficacy in detecting Human-Object Interactions.

\clearpage

{\small
\bibliographystyle{ieee_fullname}

redpajama_set_name: RedPajamaArXiv


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text:
using System;
using System.Collections.ObjectModel;
using System.Windows.Input;

namespace Wrox.ProCSharp.Composition
{
    public class CalculatorViewModel : BindableBase
    {
        public CalculatorViewModel()
        {
            _calculatorManager = new CalculatorManager();
            _calculatorManager.ImportsSatisfied += (sender, e) =>
            {
                Status += $"{e.StatusMessage}\n";
            };

            CalculateCommand = new DelegateCommand(OnCalculate);
        }

        public void Init(params Type[] parts)
        {
            _calculatorManager.InitializeContainer(parts);
            var operators = _calculatorManager.GetOperators();
            CalcAddInOperators.Clear();
            foreach (var op in operators)
            {
                CalcAddInOperators.Add(op);
            }

        }

        private CalculatorManager _calculatorManager;

        public ICommand CalculateCommand { get; set; }

        public void OnClearLog()
        {
            Status = string.Empty;
        }

        public void OnCalculate()
        {
            if (_currentOperands.Length == 2)
            {
                string[] input = Input.Split(' ');
                _currentOperands[1] = double.Parse(input[2]);
                Result = _calculatorManager.InvokeCalculator(_currentOperation, _currentOperands);
            }

        }

        private string _status;

        public string Status
        {
            get { return _status; }
            set { SetProperty(ref _status, value); }
        }

        private string _input;
        public string Input
        {
            get { return _input; }
            set { SetProperty(ref _input, value); }
        }

        private double _result;
        public double Result
        {
            get { return _result; }
            set { SetProperty(ref _result, value); }
        }

        private string _fullInputText;

        public string FullInputText
        {
            get { return _fullInputText; }
            set { _fullInputText = value; }
        }

        private IOperation _currentOperation;

        public IOperation CurrentOperation
        {
            get { return _currentOperation; }
            set
            {
                SetCurrentOperation(value);
            }
        }

        private double[] _currentOperands;

        private void SetCurrentOperation(IOperation op)
        {
            try
            {
                _currentOperands = new double[op.NumberOperands];
                _currentOperands[0] = double.Parse(Input);
                Input += $" {op.Name} ";

                SetProperty(ref _currentOperation, op, nameof(CurrentOperation));
            }
            catch (FormatException ex)
            {
                Status = ex.Message;
            }
        }
        public ObservableCollection<IOperation> CalcAddInOperators { get; } = new ObservableCollection<IOperation>();
    }
}

redpajama_set_name: RedPajamaGithub


text:
Man shot dead in apparent attempted robbery at Boost Mobile on Metcalf
Mike Frizzell Jun 11, 2019 - Crime
Crime scene investigators were inside the store hours after the shooting took place. Photos credit Mike Frizzell.
A man is dead after police say he attempted to rob a Boost Mobile store on Monday evening.
Overland Park Police say they were called to the store at 7620 Metcalf Avenue about 7:45 p.m. after receiving a report of shots being fired inside the store.
The shooting took place around 7:45 p.m. after a man allegedly entered the Boost Mobile store with a gun and demanded phones.
"Right now, we're looking at an attempted robbery," Officer John Lacy told media at the scene.
Lacy says the suspect apparently entered the store armed with a gun and demanded phones. When the suspect jumped the counter, the store manager pulled his gun and fired a single shot, hitting the suspect, Lacy said.
"We're going to review the videotape," Lacy said. "The cameras don't lie."
Detectives were also questioning a woman police say was in the area with the male suspect, according to Lacy. She allegedly approached the store after the store manager had shot the male, locked the business door, and called 911.
"We're speaking with her right now," Lacy said. "We're trying to get her side of the story, and what did she know about this incident?"
Overland Park Police Chief Frank Donchez was on the scene of the investigation Monday night.
Police cordoned off the rear parking lot of the nearby Nadeau furniture store, 7600 Metcalf Avenue, where a Chevrolet Tahoe was parked. Police have not said how that vehicle may be related to their investigation.
Crime scene technicians from the Johnson County Sheriff's Office Criminalistics Laboratory were inside the store until shortly after 1 a.m. Tuesday.
"We are talking to him [the store manager], and we are trying to find out what occurred here at this location, and we will send our report out to the District Attorney's Office for their review," Lacy said.
Police have not released the suspect's identity.
Police investigate after woman says man robbed her after taking her from Merriam IKEA
Stolen goods recovered from Shawnee home linked to investigations in 3 metro counties
'Large quantity' of stolen goods found during search at Shawnee home
Three men arrested following crime spree that began in OP, continued through Shawnee and the Plaza
Two suspects remain on the loose after another armed carjacking, this time in Shawnee


Purpose: The Be the Peace Institute is a community-based, non-profit organization dedicated to promoting gender equity, healthy relationships and safe, peaceful communities and systems in Nova Scotia. Working in close partnership with community organizations, government bodies, survivors and citizens, it promotes positive social change by addressing violence against women, children and youth, and altering the social and systemic forces that deny women and girls full equality, security, opportunity and justice. Through innovative, collaborative initiatives, BTPI advances knowledge, research and best practice evidence to improve violence prevention while informing policy development, decision making, system change and service provision related to gender-based violence.
Who We Serve: The citizens and communities of Lunenburg County and beyond. While our work is primarily on behalf of survivors of intimate partner, domestic and sexualized violence, it benefits their families, friends, co-workers, communities and networks. The impact will be felt by all the young people in our county who face the challenges of growing up in a world of gender-based stereotypes, myths and oppression that affect the integrity, dignity and productivity of our entire community and people of all genders.
Vision: Under a framework of peace-building that is restorative at its core, BTPI courageously promotes and engages community for justice, gender equality and social change, from the individual to systemic. We are a 'centre of excellence' in research, education, data and tools to prevent, address and end violence against women in all forms, making Lunenburg County the most safe, equitable place for people of all genders to live, work and thrive.
Explore different views and listen for common ground.
Uncover all assumptions and agree on expectations.
Share leadership, responsibilities and information generously.
Treat everyone as a respected, trusted, cooperative partner.
Take purposeful action when there is a clear path and energy.
Invite all voices and perspectives to create safe spaces where everyone can belong.
Ask even the hard questions.
At its core, Be The Peace is a peace-building project.We wanted the project to take an "appreciative" approach - focusing on what we want, rather than what we don't want. When we considered what would be the opposite of violence, we decided it was peace. The name, "Be the Peace . . . Make a Change" is a play on the well-known phrase of Ghandi. ("Be the change you wish to see in the world.") While we aim to build peaceful relationships, peaceful families, peaceful schools and communities, we recognize that peace, first and foremost, is an inside job. It starts within each of us "waging peace" in our own hearts and minds. As we let go of judgments and blame, we can actually be and create the peace we wish to see in our lives.
Helen is a retired elementary school principal and an activist. She was the Administrative Coordinator of Second Story Women's Centre for more than two years. During that time, she worked closely with staff and members of the Social Action Committee on the Making Change initiative. She has served as a member of the Board of Directors and is one of the lead organizers of the One Billion Rising events.
Helen believes that if we are to end violence in our communities, we must challenge the systems that perpetuate it and be innovative in collaborating with others to address it.
She is also active in other community organizations. She is a member of the South Shore Housing Action Coalition, a member of the Board of Directors of the Affordable Housing Association of Nova Scotia, and a member of the South Shore Chapter of the Council of Canadians.
Stacey Godsoe is the project officer for our Status of Women project, "Pathways to Justice for Women Affected by Gendered Violence." Stacey co-coordinated the "Power of Our Voices" project funded through Justice Canada and is the former co-coordinator of SASLQ (Sexual Assault Services Lunenburg Queens).


Need more information about booking Home 219992 ?
Tucked away in east Galway, Lakeview House is nestled in the foothills of the Slieve Aughty Mountains with the lake literally on its doorstep. This family run enterprise has the highest star rating that Failte Ireland can award. Bicycles are available for those who wish to racket up the tempo and for the adrenaline junkies kayaks are provided, all free of charge.
Not only do you get access to a private river and lake you also have access to the private mooring. Fishing rods and all the necessary safety gear is provided free of charge. Not only is there ample private grounds to explore, the locality is a haven for hill walkers who can directly access the flora and fauna of Lough Derg, take to the Brian Boru Trail or the East Clare Way. Part of the Lakeview House experience is getting up close and personal to a working farm.
You and your family can enjoy karting in nearby Tynagh, pony trekking in Flower Hill Equestrian Centre or horse riding in Slieve Aughty Riding Centre or Lough Hill Pony Trekking Centre.Trigger your children's imagination with the famous telescope in Birr Castle and the extensive monastic settlement on Holy Island. For those wishing to trace family roots, Woodford Genealogy centre is a five minute drive. Lakeview House is an ideal location for touring the West of Ireland, Connemara and the Shannon region. You are just 40 minutes from Galway, Ennis and Limerick.
This House has 4 bedrooms, 3 bathrooms and sleeps 9. It's been listed on Holiday Lettings since 13 Apr 2012. Located in County Galway, it has 34 reviews with an overall rating of 4.5. The average weekly rate is £695.
The house is located 18 km from Portumna, directly at Lough Derg. It is well equipped, has four bedrooms, three washrooms and toilets, a big kitchen, a very nice dining room and a leather-interieur-equipped saloon. Located in the middle of a green landscape and showing the near lake, it gives the best opportunity to cool down from day to day business life. Bed linen, towels, knives, forks, spoons etc are provided. Some of the chairs might wait for a repair and some kitchen inventories might be upgraded, but to put it in a nutshell: It is nice staying there for a week or two. Bycicles and kayaks are provided, cold and hot water is perfect, wash-machine and dryer do their jobs. Wifi is available at the very warm athmosphere giving landlord's pub (2km, Gorteeny). The owner, Garry Gorman, provides help wherever needed and is a chap to have a beer with. For runners: Perfect running tracks, starting directly at the house (just follow the road to the south for 700 meters and then take one of the loops to the left or to the right). For sightseeing: This ais a good start for tours to Tullamore, Birr Castle, Galway, Kilcolgan, Cliffs of Moher, Limerick, Portumna Castle. Shopping is best done in Portumna.
This was our first trip to Ireland and will not be the last. The house was everything we wanted it to be and more, cozy bedrooms great living room very comfortable. Unfortunatly we were not able to take advange of the boats just not enough time. But we were able to pick fresh black berries for breakfast every morning. The locls in the bar in town are nice and very freindly. Gary and his mom are great. We were able to spend some time chatting with her in at the bar. Lots of great plaes to see.. Can't wait to come back.
You can get in touch with Gerard (the owner) through the contact form on this page.
Send Gerard (the owner) an email through the contact form on this page. Alternatively, if there's a phone number on this page, you can call them.
How do I contact Gerard (the owner)?
If you've already booked, go to Manage your holiday booking to view Gerard the owner's contact details or send them a message.
Or send Gerard (the owner) an enquiry through the Contact the owner/manager form if you'd like a quote or more info first.
When you pay online through the Book your stay form, a booking request is sent to Gerard (the owner). You'll find out within 24 hours whether they've accepted - no money will leave your account before then.
You can also request a quote from Gerard (the owner) through the contact form. The owner will email you the total cost for your dates and a link to book and pay online.
Use the Book your stay form to pay provisionally online. You can pay by credit/debit card or PayPal. Gerard (the owner) will have 24 hours to accept the booking and no money will leave your account before then.
Why can't I call Gerard (the owner) before booking?
You'll need to contact Gerard (the owner) to do this. Send them a message in Manage your holiday booking or through the contact form on this page.
You can request to change the dates or number of people on your booking via the Manage your holiday booking page. To change your holiday dates use the Edit booking button. If you need to change the number of guests staying then send Gerard (the owner) a message.
If Gerard (the owner) agrees, they'll send you a revised quote outlining the changes. You can review and accept/decline this from the Manage your holiday booking page. You'll have 48 hours to take action before the revised quote expires.


My recent journal page was recycled for this design, which I needed to finish quickly for September's exchange. Although I deviated from the techniques, this was inspired by Danny Gregory's Fast and Slow drawing techniques, as well as Andrea Joseph's journal lettering.
This is my second attempt for Sketchbook Skool's Fast-and-Slow exercise. Danny Gregory has now made it clear he expects us to outline, rather than fill in. Nevertheless, I wanted to make fast, solid blobs for this particular sketch. I'll do something later that draws only the outlines. I'm so thrilled that our access to the course was extended--ever since Sprint took over our internet service, it's been so bad that, most of the time, I can barely watch the HD videos. I certainly didn't finish the assignments. Of course, each time I take another stab at an assignment, my effort is more pleasing than the last.
My friend, Emily, treated me to a day at the Festival of the Arts and the Sawdust Festival in Laguna Beach. A highlight, was drawing a quick sketch onto a sheet of styrofoam, then printing it with a roller press. I can imagine all kinds of possibilities. Once home, hubby reminded me that I have a Gocco printer that I've never quite figured out how to use. SO, Emily and I will spend next Friday playing with that printer.
I've been taking an Uncial calligraphy class with John Rafter, through Mount San Antonio College.He's a very thorough instructor and I've learned quite a bit about refining this hand (style) which I've studied off-and-on for years.
For all my ATCs, I'm determined to use mainly on-hand materials. The background here is scrapbook paper, purchased years ago, glued to stock cut from an old rolodex card. The strip of text is snipped from a Japanese novel, layered on top of green and gold pieces cut from scraps of paper. The embellishments are from a package of little self-stick "gems".
The Society for Calligraphy has an exhibit, Beyond Words, at Muzeo, in Anaheim, right now. In the past, I've submitted pieces that I had created, but this is the first time I've created a piece specifically for an exhibit.There are a couple things that I want to change/improve, I'm considering this a draft and this fall, I'll create a Final version. I named this Imperfect Pear.
Version One of my Japanese Pear ATCs. I only had time to make enough for the current exchange. I'll soon make a variation to give to friends, tentatively creating a background of bouncing Romans with a broad-edged pen.
The pear was cut from a Japanese detective novel that I found at a thrift shop. Yes, I believe I have the text in this one upside down, since the Japanese write from top to bottom. For the red "skin", I painted a page with a mix of WN Scarlet Lake and WN Alisarin Crimson watercolor. The small seeds and stem are cut from scrap paper--that took awhile!
I'm very happy with the bright, cheerful color contrasted with the black and white background.
Playing around with techniques for decorating envelopes. This color, added with watercolor pencils, is a variation on a piece done by Jane Shibata--she used Uncial lettering. The color here isn't really true--it looks better "in person". I'll blend better on the next try--fun, but time-consuming.
Spring's ATC. I'm clearing out and reorganizing my sewing/art room and my goal is to use the materials I already have--I shouldn't need to purchase another art supply for the rest of my life! (Ha!) Re-used watercolor paper on which I had practiced painting trees. I coated that with gesso, to tone it down, so the copperplate lettering would not be obscured. Sketched the tulips and lettered "Tulips" with sumi ink. Scanned and printed the design on tracing paper, then pasted over the card. Painted with watercolor. Pasted a "rhinestone" to dot the i.
I don't think I like this card as much as the last. It was done in a hurry. Next: experiment with variations in a sketchbook.
Should be a fun class . . .
Shown here is one of the ATCs I created as part of a series. The initial design was sketched on a journal page, which can be viewed in a recent post.
In order to add more color, I stitched two bright red border-lines. That color is picked up by the Love label. I also stitched a perpendicular blue line to pick up the blue from the dress form on the left.
It seems I'm VERY slow to update this blog.This picture is from October 30 of last year, when D and I went to Catalina. He had childhood memories and wanted to stay there in a place overlooking the harbor.
We had eaten at this location on a prior trip, but the food is much better now that Bluewater has taken it over. I loved going at this time of year, for a change--our view of the restaurant was of the lights from the houses on the side of the hill. The next day, we had lunch here, outside, overlooking the water.
One highlight of this trip was watching the childrens' Halloween costume parade. Even the dogs had costumes, with lobsters being their favorite theme.
I'm really behind on posting! I'll plan to add some more scans over the next few days. On this hastily-done journal page, I was playing around, designing my next ATC--I'll make a batch this week. I plan to add a small contrasting element and I'll update this picture when I do.


I'm half Korean and I had no clue how to say "Take Good Care" in my mother's language until I Google Translated it. I probably would still butcher the pronunciation if I tried to say it out loud. But that's besides the point. What is the point?
That you can take good care of yourself using the beauty philosophy perpetuated by this one culture. Korea has amassed a cult status for almost all of its beauty products — at least it feels that way. If it hails from the Land of Morning Calm, it immediately has a seal of approval no FDA regulator can refute. That's not to say some brands deserve greater worship than others.
Take Good Care, a newly launched Canadian site specializing in K-beauty, has made it its mission to bring only the best into the country. And I've been lucky enough to test out a selection of the best over the last few weeks (minus my time in Cali because I refused to check luggage). The verdict? Don't sleep on this service.
The starter kit comes with a few amazingly nourishing sheet masks, but my favorite had to be an additional one I requested: The Cremorlab Perfection Hydrating Mask. Not only is the packaging beautifully designed, it does exactly what it promises. I love sheet masks in general because they're so easy to use and are pretty versatile. How so? Lifehack: There's usually a lot of product on each mask, which can be used on other parts of the body is massaged through.
Also an additional request, this duo has made my night routine a lot more sophisticated. Now that I'm in my 30s, I'm very conscious about my skin care regimen. I knew the usual cleanser and lotion pairing needed an update and with these serums, I got just that.
Talk about a holy grail. My skin has never felt so smooth after using this specific mask. It leaves me feeling not only fresh, but glowing. Made with Brazilian black sugar, macadamia oil and lanolin, if there's anything you take away from the starter kit, it's definitely this product.


The XYX-3 trailer mounted water well drilling rigs for sale in Yugong Machinery is a kind of self-propelled drilling rig which is very portable to move. The machine can be used as both water well drilling rig and core drilling rig machine. It is an updated model of XY-3 spindle type core drilling rig that our engineers install the wheeled walking device on the basis of the original equipment which don't need to be loaded and unloaded from the truck and can save the workers' labor, improves the working efficiency.
The model is equipped with wheeled travelling mechanism and hydraulic cylinder stanchion, which makes the whole machine convenient to move and facilitate the horizontal adjustment of the drilling rig machine.
Rising and falling tower is hydraulic operation which is more convenient and reliable.
Diesel Engine adopts electric start which can help reduce the labor intensity of workers.
The hydraulic automatic feeding mechanism can improve drilling efficiency.
Pressure gauges at the bottom of the bore indicate the pressure for easy inspection of the inside of the bore.
Widely used. Geological exploration, road and high-rise building foundation exploration and various concrete structure inspection, river embankment grouting hole drilling and direct grouting, civil well and foundation central air conditioning hole drilling.


text:
Firsthand
Brand Home Manager Made Keeper of the Quaich
Susan Colville was invited to join the international and select society which recognises those who have shown outstanding commitment to the Scotch whisky industry.
Susan, who was born and raised in Speyside, joined the Forres-based distillery in 2013 to lead a dedicated team of guides who deliver a highly personal and up-close experience to thousands of visitors from all over the world each year.
Throughout 2018, as Benromach celebrates its 20th anniversary since production restarted, Susan has been driving an exciting programme of activity. She began by leading the team that staged the Spirit of Speyside Whisky Festival opening gala dinner in May and is helping to host colleague and trade events throughout the year.
Susan was thrilled to be honoured by the Keepers of the Quaich She said:
"This has been an incredible year at the distillery, and to receive this accolade during our 20th anniversary is particularly special for me."
"As one of only a few distilleries in Scotland where every whisky is handcrafted without any automated equipment, we've worked hard to deliver tours and tastings to our visitors that are truly unique. Since 2013, we've seen a 40% increase in visitor numbers from across the globe."
Susan, who lives in Elgin, Speyside with her husband and daughter, was determined to pursue a career in the Scotch whisky industry from an early age having been inspired by her father who worked for over 30 years as a distiller at Glenrothes Distillery.
Beginning her career as a tour guide at Glenfiddich and Glenfarclas Distilleries over the summer holidays, she then moved to Edinburgh to work for Royal Mile Whiskies. With a natural disposition for customer service and a love of Scotch whisky, Susan relished the opportunity to develop her knowledge and hone her sales skills.
'This has been an incredible year at the distillery, and to receive this accolade during our 20th anniversary is particularly special for me.'
Sales and marketing roles with Douglas Laing, AD Rattray, Wemyss and Glenglassaugh saw Susan travel the world, conducting countless masterclasses and tastings to an audience keen to learn and enjoy Scotch whisky.
Susan was acknowledged by her industry peers in 2012 when she was presented with the Young Ambassador of the Year accolade at the Icons of Whisky Awards. Following this recognition, Susan was named Visitor Centre Manager of the year at the World Whiskies Awards in 2015.
The venue for the Keepers of the Quaich ceremony – Blair Castle – is home to the Atholl Highlanders, Europe's only private army. The banquet is held in the Grand Ballroom of the Castle, famous for its ceiling decorated with 175 deer antlers.
Keith Cruickshank, distillery manager at Benromach, commented:
"Susan's tireless commitment and significant contribution to our wonderful industry makes her an outstanding candidate to become a Keeper of the Quaich.
"She is a terrific ambassador for Scotch malt whisky and is truly deserving of this honour."
Last month, Benromach Distillery, which attracts more than 13,000 visitors per year achieved its Five Star Visitor Attraction status from VisitScotland's Quality Assurance scheme.
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98% cotton 2% elastane.description:Long sleeve stretch denim jacket in light blue. Spread collar. Signature pink topstitching and button closure at front. Patch pockets at bust. Welt pockets at waist. Adjustable buttoned tab at back hem. Single-button barrel cuffs. Logo-engraved silver-tone hardware. Contrast stitching in tan.