text:
Chevron's Sham Remediation in Ecuador: Toxic Oil Pits Continue to Contaminate
Reposted from The Huffington Post
Chevron, Chevron Quite Contrary, How Does Your Garden Grow
With Polluted Soil & Toxic Water
And Wealthy Lawyers All In A Row
During the historic contamination trial against Chevron in Ecuador, the company often took journalists to its so-called "remediated" oil pits to prove that its predecessor Texaco cleaned its "share" of one of the world's worst environmental disasters, if not the worst.
Chevron's well-heeled lawyers would sometimes arrange for a nice picnic near the pits to show reporters how green its gardens had grown in the Amazon rainforest since Texaco signed a 1995 agreement with the Government of Ecuador to remediate toxic pits.
But lurking beneath the vegetation was and is pure crude mixed into the soil and underground drinking water and laced with carcinogens, such as benzene and cadmium.
Six different sets of tests have shown that Texaco only dumped dirt on top of the pits to hide the contamination, not clean it.
And, eight Ecuador judges and two U.S. judges who've heard evidence related to the 22-year-old lawsuit have either ignored the remediation agreement, thrown it out or stated it had no merit in Chevron's defense.
Ignoring the evidence, the oil giant continues to tout the agreement as its "get-out-of-jail-free" card, and U.S. reporters continue to use it in their stories as a legitimate response to the Ecuadorians' charges, while the "remediated" pits continue to leech dangerous toxins into the soil and water that indigenous peoples and rainforest villagers depend on for sustenance.
The contamination of indigenous' ancestral homelands and the disease and death left behind is unlike anything you have ever seen. And, even though Ecuador's Supreme Court has upheld the $9.5 billion judgment against the oil giant, Chevron refuses to pay, arguing the agreement released it from any liability.
So, let's look a closer look at the agreement and the remediation itself:
Travel to any of the pits that Texaco agreed to clean and dig a few feet under the ground and you will find oil.
How does Chevron explain this? With classic Chevron chutzpah.
The company maintains that in the dead of night rainforest villagers "spike" the jungle floor with oil by digging holes at the pits, pouring fresh oil into them and covering them up with dirt and vegetation so they can return the next day with a visitor to prove Chevron is lying about the remediation.
With a straight face, Chevron spokesperson James Craig peddles this outrageous story to reporters, including this Miami Herald reporter:
"...Moncayo (an Ecuadorian) plunges his auger into the ground. Within a few inches the dirt gives off the pungent odor of petroleum. Within a few feet the dirt glistens with oil residue. When a few handfuls of the soil are dropped into a bucket of water, a thick oil-slick coats the surface.
"'This is their (Chevron's) remediation effort,' Moncayo says. 'They're no better than animals.'
"The (Ecuadorians) say it's proof that Chevron lied about the cleanup and then got compliant government officials to sign-off on its shoddy work.
"Chevron spokesman...James Craig, said it's not surprising to find degraded crude at the site. It might be naturally occurring, Moncayo might have dug outside the boundaries of the remediation area, or the plaintiffs might have spiked the ground with oil (emphasis added) to discredit Chevron, he said.
"'Even if you do find hydrocarbons in the ground, it doesn't mean that they're a risk to people's health or the environment,' Craig said."
(Read similar descriptions in The Telegraph, Associated Press, Bloomberg Markets, Washington Post, NY Times and Rolling Stone, among many others.)
Craig's explanation would be hilarious if the issue of remediation wasn't so pivotal to the outcome of the litigation battle, being fought now in countries where Chevron's assets can be seized as payment for the judgment. (Chevron has few assets in Ecuador.)
For the most part, Chevron doesn't dispute the contamination. One of its local lawyers, Rodrigo Perez Pallares, even admitted the company dumped 15 billion gallons of toxic waste into waterways.
In addition to intentionally dumping toxic water into streams, Texaco (Chevron bought Texaco in 2001) also built over 900 huge, unlined waste pits to permanently store pure crude oil and wastewater laced with carcinogens that are a byproduct of the drilling process.
Instead Chevron's army of lawyers argues that Texaco cut a deal with the Government of Ecuador to clean a small percentage (162 of 900 or so) of the oil pits in exchange for immunity from future lawsuits.
Yet even upon cursory examination, Chevron's so-called "release" is not even close to what the company claims.
The agreement, negotiated after the Ecuadorians filed their original lawsuit in the U.S. in 1993, released Texaco only against government claims of contamination. It expressly carved out any claims held by individuals, such as the Ecuadorians'. A Memorandum of Understanding between Texaco and Ecuador's government, signed in 1994, stated clearly that third-party private claims should not be "prejudiced" by the agreement.
From 1995 to 1998, Texaco conducted its fake cleanup – or cover-up, if you will. During the same time, Texaco's lawyers waved the remediation agreement in front of the U.S. federal court, hearing the contamination case in New York. But the American judge took no note of it, given that not even Texaco argued at the time that it trumped the claims of private citizens that were pending against the company in the lawsuit.
Later, another federal judge also caught onto Chevron's subterfuge, in a related arbitral proceeding that ended up in U.S. federal court.
U.S. Judge Leonard Sand analyzed the "release" agreement and, for all practical purposes, said it had nothing to do with the Ecuadorians' claims.
The learned Judge Sand concluded:
"...it would be extremely difficult for [Chevron] to establish that claims nominally brought by third parties in the Lago Agrio litigation were covered by the 1995 and 1998 Agreements between Texaco and Ecuador: it is highly unlikely that a settlement entered into while (the case) was pending would have neglected to mention the third-party claims being contemporaneously made ... if it had been intended to release those claims or to create an obligation to indemnify against them." (Republic of Ecuador v. ChevronTexaco Corp., 376 F. Supp. 2d 334, 374 (S.D.N.Y. 2005).
Fearful that Judge Sand would expose the release agreement for what it was, Chevron simply pulled its lawsuit back and ended the case.
While Chevron ran for the hills to avoid Judge Sand, it convinced federal Judge Jed Rakoff that the underlying claims case should be tried in Ecuador rather than in the U.S. To get the case transferred to Ecuador, the company filed no fewer than 14 sworn affidavits praising Ecuador's judicial system as "independent" and "fair". In 2003, per Chevron's request and Judge Rakoff's order, the villagers re-filed their lawsuit in Ecuador.
By 2013, after an arduous trial that produced 105 expert reports documenting Chevron's pollution, three layers of Ecuador's courts – trial, appellate, and Supreme Court – had ruled against the company. No fewer than eight appellate judges held Chevron responsible for the contamination and ruled that the 1995 remediation agreement did not apply to the private claims in the case and thus was without merit as a defense.
Even though Chevron had previously promised Judge Rakoff and three U.S. appellate judges that it would accept Ecuador's jurisdiction and abide by its court decisions in exchange for moving the case to Ecuador, Chevron has refused to pay and continues to argue in any court that will hear its complaints that the remediation agreement frees it from all responsibility for the damage it caused.
But, if that's really the case, why doesn't the remediation agreement have words to that effect? Or have the signatures of the villagers who brought the case? Even if a court ruled that the agreement released the claims (none has), the problem with the remediation itself remains. Why?
At best, it was terribly inadequate. At worst, it never happened. In either event, it was a sham.
Most likely, Texaco's contractor dumped dirt over the pits to cover up the oil and called it a day. Over time, some vegetation grew on top of the dirt and that's why Chevron began having picnics to show reporters how green its gardens grew.
Which brings us back to Chevron's James Craig and the band of merry Ecuadorians digging holes under full moons in the jungle to "sabotage" Texaco's so-called remediation.
Six different field tests taken by different parties, including those taken by Chevron, prove the remediation was a fraud. The so-called "cleaned" pits are just as contaminated as those not cleaned. See here for information about the field tests described below.
1) Chevron's own tests taken at Texaco's remediated well sites show illegal levels of total petroleum hydrocarbons (TPH). For example, Chevron found 13,000 parts per million (ppm) of TPH levels at the oil well site, known as Shushufindi 48. Ecuador requires the TPH level to be below 1,000 ppm; the average U.S. standard is even lower, at 100 ppm.
2) Chevron also took additional tests in March 2009, as the trial was coming to a close. Chevron's expert Marcelo Munoz tested eight purportedly "remediated" sites and found illegal levels of contamination at two. Chevron refused to pay Munoz for his report, even though the oil company requested that he conduct the tests.
3) In 2003, five years after the fake cleanup, Ecuador government auditors reported they had discovered pits oozing with oil and concluded the government had "erred in certifying" the cleanup. "Texaco has caused irreversible damage," stated a report by the General Controller, a government agency that audits public contracts. "The environmental remediation and repair agreement goes against the country's interest." The auditors' tests found that over 85% of pits tested had toxic levels higher than 1,000 ppm of TPH. They also found oil seeping out of 41 "remediated" Texaco waste pits and said 59 pits had been left uncovered.
4) In 2009, an Ecuador prosecutor ordered yet another series of tests. Of the 20 tests conducted at nine sites, 16 returned with toxic levels higher than the Ecuadorian standard of 1,000 ppm, and of those, 13 had levels higher than 5,000 ppm.
5) The Ecuadorians also did a series of tests at the "remediated" pits and found TPH levels higher than 30,000 ppm.
6) And, in 2013, a U.S. environmental engineering firm, The Louis Berger Group, did additional tests for the Government of Ecuador and found, once again, high levels of contamination. The American company also reviewed the work of Chevron's experts at the so-called remediated sites and found numerous flaws and incorrect conclusions. See pages 35 to 42.
All of this evidence adds up to one thing: Texaco committed fraud against the Ecuador government. And Chevron has done the same by lying about the remediation to Ecuador and U.S. courts.
Chevron is responsible for what Texaco did. It's also responsible for what Texaco never did – which was cleanup its toxic mess that is literally killing or threatening to kill thousands of people from cancer.
Posted: Friday, November 14, 2014 No comments:
Chevron's Sham Remediation in Ecuador: Toxic Oil P...


text:
Oxycnemis grandimacula är en fjärilsart som beskrevs av Barnes och Mcdunnough 1910. Oxycnemis grandimacula ingår i släktet Oxycnemis och familjen nattflyn. Inga underarter finns listade i Catalogue of Life.

Källor

Nattflyn
grandimacula

redpajama_set_name: RedPajamaWikipedia


I have listed a new property at 315 380 MARINA DR in Chestermere.
Top floor, two bedroom and two bath condo with a view of the lake! This condo is move in ready! There are granite countertops, a newer stainless steel dishwasher, upgraded fridge and stove. The stackable washer & dryer are also only a few months old.


Parko at Teahupo'o, not this week though.
And to celebrate, Billabong released his most memorable defeat at the formerly Billabong sponsored event. What a send off! This clip, though, is the some of the funnest surf content of the year. It's Joel Parkinson and Mick Fanning talking about their epic final at Teahupo'o in 2012, the one Parko had Mick comboed in about the fist 12 seconds of before Mick fought back and took it from him. A true classic of the sport of surfing. Parko won the World Title that year though, so it's all good.
As said above, Joel Parkinson surfed his final heat at Tahiti this week because Joel Parkinson is retiring at the end of this year and also Tahiti is on right now and he lost today in Round 3 to Wade Carmichael. They're up to the quarters now, and Carmichael is there and so is Owen Wright and so is World No.1 Filipe Toledo and so is World No.3 Gabriel Medina and so is World No.4 Italo Ferreira. So many top guys! Who's missing? Oh, no. No... Julian Wilson is missing! Julian lost in Round 2, bowing out of of the comp in a heat where he only had one wave, and onlyu needing a 1.83. It's a result that indicates just how poor the forecast is for this event, and it's a result that also severely hurts Julian Wilsons World Title chances.
And here are some highlights from Day 1 of the event. What's always funny about Teahupo'o is that even though this is basically the spot and event at its worst... it's still so so so much better looking a wave than what most of us surf on the regular.
P.S. Picking Medina to take this one out.
The second instalment of O'Neills wonderful new docu-series – The O'RIGINALS – is an absolute corker of a short film. We meet Lachie Rombouts, who talks about how he dealt with mental health issues by moving closer to the ocean and working on his own garden. Lachie grew up a two hour bus ride from the ocean, but has since developed into an accomplished charger, a by-product of loving any and every opportunity to get into the water. We could go on and on about the beauty of this part, and the delightful way Lachie delivers his story, but we won't. We'll stop right here and just implore you to click play and watch it.
Not since Offshore Festival at Bells in 1998 (note: 90s year picked at random) have pop-punk music and elite professional surifng made such beautiful bedfellows. In news outta nowhere, Blink 182 have been announced this week as the headliner for the concert that will take place during the WSL's wave pool championship tour event, the Surf Ranch Pro at Kelly Slater's Lemoore wave pool. Blink, of course, are synonymous with surfing through their inclusion in various Taylor Steele surf videos of the early 90s, like "Mutt" on The Show. Absolute classic.
Which Blink 182 song is your favourite? Mine is Lifestyles of the Rich and Famous by Good Charlotte.
These boards are called the Deadly Mondo, and the last time I saw my friend, Vaughan Deadly, he had just been given one. Which made me think that it was his model. But now I'm not so sure. In any case, how good is Kipp Caddy taking at wrangling it through some throaty blue tubes? Really good. Is the answer. To that question.
Are you sick of Nias yet? You are? Ah well, I'm sorry, but I have this incredible clip of that same Nias swell, this time featuring Hawaiian Tyler Newton, and I've already placed it here and I'm not going to move it. So perhaps we should all just watch it and enjoy. It is incredible, pumping Nias after all.
Asher Wales, Otis Carey, Jaleesa Vincent and Jake Vincent rip up some beachies in the latest episode of Misfit's new web series. The real highlight of this episode though is the discovery that a car windshield sunshade can be used as a changing towel. Genius!
You know what's awesome about this clip? How good Noa Beshcen is at surfing, how great his approach fits with the new pool and its multitude of air sections, the intersting and bizarre colours the pool reflects as late afternoon light hits it. You know what's not awesome about this clip? I spilt coffee on my shirt while watching it and now my shirt has a big coffee stain on it, and ah, gee, I'm not sure if I'll ever get it out. Into the bin it goes!
Whether or not you love foils, or hate foils, no one can deny how versatile it is as a material to wrap up a baked potato. Unrelated: Kai Lenny does cool, weird airs on his foil now.


text:
Dell Home, via its Member Purchase Program, offers its Dell XPS Tower Intel Coffee Lake Core i5 2.8GHz 6-Core Gaming Desktop PC in Black for $666.39 with free shipping. That's $134 off list, $34 under last month's mention, and the lowest price we've seen. (It's also $34 cheaper than what Dell charges via its eBay and Walmart third-party stores.) Deal ends October 30 at 8 am ET. Features include:
New Amazon Fire TV Stick With Voice Remote Case SIKAI Amazon Fire TV Stick Remote Silicone Case for Amazon Fire TV Stick Remote Protector Case with Hand Strap Included (With Voice Luminous Blue) Product Features ! NOTICE: All SIKAI Silicone Products have passed the RoHS test (UK) and CPSIA test (US), safety non-toxic, ensure health, conformity with environmental legislations. Perfect Full edge Design providing 360 Degree protection., But still support the operation of all the ports. Made of environmental silicone, shockproof, skin-friendly, durable, washable, durable and comfortable. With Free hand lanyard, and bright colors, easy fo find, never worry about the hide remote. Product Specifications Product Dimensions: 6.5 x 2 x 0.9 inches Item Weight: 0.3 ounces Shipping Weight: 0.3 ounces... Less
This one from Paderno is the best tabletop option. The interchangeable blades let you create varying degrees of noodle thickness and styles, and the open design ensures most any produce you want will fit right in. It's also easy to use and completely dishwasher safe. And when you're done, everything is self contained for easy and safe storage. Right now it's back down to the lowest sale price we've ever seen, a discount we haven't seen since last December.
At the top of Amazon's homepage, click the tab called "Today's Deals" to link to all the deals, coupons and bargain pages. The main page, also called Gold Box Deals, provides links to all the sale items and tabs to all the discount pages. Scrolling down reveals a few examples of sale items offered on each page. At the bottom, you will find links to additional businesses which are owned by or partner with Amazon; such as 6PM for clothes and shoes and MYHABIT for housewares.
Bezos selected the name Amazon by looking through the dictionary; he settled on "Amazon" because it was a place that was "exotic and different", just as he had envisioned for his Internet enterprise. The Amazon River, he noted, was the biggest river in the world, and he planned to make his store the biggest bookstore in the world.[25] Additionally, a name that began with "A" was preferential due to the probability it would occur at the top of an alphabetized list.[25] Bezos placed a premium on his head start in building a brand and told a reporter, "There's nothing about our model that can't be copied over time. But you know, McDonald's got copied. And it's still built a huge, multibillion-dollar company. A lot of it comes down to the brand name. Brand names are more important online than they are in the physical world."[26]
Since its founding, the company has attracted criticism and controversy from multiple sources over its actions. These include: supplying law enforcement with facial recognition surveillance tools;[154] forming cloud computing partnerships with the CIA;[155] luring customers away from the site's brick and mortar competitors;[156] placing a low priority on warehouse conditions for workers; participating in anti-unionization efforts; remotely deleting content purchased by Amazon Kindle users; taking public subsidies; claiming that its 1-Click technology can be patented; engaging in anti-competitive actions and price discrimination;[157] and reclassifying LGBT books as adult content.[158][159] Criticism has also concerned various decisions over whether to censor or publish content such as the WikiLeaks website, works containing libel and material facilitating dogfight, cockfight, or pedophile activities. In December 2011, Amazon faced a backlash from small businesses for running a one-day deal to promote its new Price Check app. Shoppers who used the app to check prices in a brick-and-mortar store were offered a 5% discount to purchase the same item from Amazon.[160] Companies like Groupon, eBay and Taap.it countered Amazon's promotion by offering $10 off from their products.[161][162] The company has also faced accusations of putting undue pressure on suppliers to maintain and extend its profitability. One effort to squeeze the most vulnerable book publishers was known within the company as the Gazelle Project, after Bezos suggested, according to Brad Stone, "that Amazon should approach these small publishers the way a cheetah would pursue a sickly gazelle."[122] In July 2014, the Federal Trade Commission launched a lawsuit against the company alleging it was promoting in-app purchases to children, which were being transacted without parental consent.[163]
Walmart offers the Microsoft Xbox One S 1TB Console bundled with your choice of NBA 2K19 for Xbox One, Playerunknown's Battlegrounds for Xbox One , Minecraft for Xbox One, or Forza Horizon 4 for Xbox One, as well as Red Dead Redemption II for Xbox One, a PowerA Wired Controller for Xbox One, and a $5 Xbox Gift Card for $259 with free shipping. That's $30 under the lowest price we could find for these items purchased separately elsewhere.
On January 22, 2018, Amazon Go, a store that uses cameras and sensors to detect items that a shopper grabs off shelves and automatically charges a shopper's Amazon account, was opened to the general public in Seattle.[54][55] Customers scan their Amazon Go app as they enter, and are required to have an Amazon Go app installed on their smartphone and a linked Amazon account to be able to enter.[54] The technology is meant to eliminate the need for checkout lines.[56][57][58] Amazon Go was initially opened for Amazon employees in December 2016.[59][60][61] In August 2018, the second Amazon Go store opened its doors.[62][63]
Found an item at a good price? Before you purchase, check promotional code sites like our own Clark Deals as a final step to see if you can save a little more, or maybe score some free shipping. (Tip: Read the comments under the codes to get additional saving tips from other shoppers — these can give you valuable clues to getting a better deal with that store or item). See Clark's master list of Deal-a-Day websites and online coupon sites.

redpajama_set_name: RedPajamaCommonCrawl


text:
MTU Selects Altair as its Strategic Partner for CAE Pre- and Post-processing and HPC Workload Management Solutions
Evelyn Gebhardt
Blue Gecko Marketing GmbH
gebhardt@bluegecko-marketing.de
Jean-Jacques Appleby
Altair Engineering
Tel.: +44 (0)1926 468 600
jean-jacques.appleby@uk.altair.com
Aerospace company will consolidate software tools for all development departments worldwide with HyperWorks and PBS Professional
TROY, Mich., Feb. 14, 2012 – Altair Engineering, Inc., announced today that MTU Aero Engines, a leading provider of aero engines for the civil and military aircraft industry, has selected HyperWorks as its primary strategic solution for CAE pre- and post-processing and PBS Professional® for high-performance computing (HPC) tasks.
HyperWorks is Altair's comprehensive simulation platform for rapid design exploration and decision-making. MTU selected HyperWorks following a year-long enterprise benchmark that deeply investigated all major CAE commercial software packages. As a result, MTU will deploy the HyperWorks modules HyperMesh and HyperView across the bigger part of its development groups worldwide, entirely replacing its former commercial pre- and post-processing solution.
PBS Professional, Altair's commercial-grade workload management and job submission solution, provides a flexible, on-demand cloud computing environment that allows enterprises to easily share distributed computing resources. PBS Professional will serve as MTU's strategic workload management solution, handling job distribution and scheduling of high-performance enterprise computing resources.
"Selecting Altair has been a strategic decision for MTU," said Dr. Hans-Peter Hackenberg, MTU's manager of structural mechanics, thermal analysis, air and oil systems. "We were looking for a long-term partner able to provide us with the best tools on the market as well as with sound technical know-how in the aero engines domain and continuous support to integrate the software into our processes. HyperWorks has demonstrated market leadership in modeling and visualization technology, which will help us to increase productivity and quality in product development. Moreover, best-in-class existing multi-solver interfaces to third-party solvers and customized interfaces to in-house tools will allow us to harmonize processes and tools in the structural and thermal analysis environments."
"In addition to HyperWorks, we chose PBS Professional for our high-performance computing needs," said Dr. Hartmut Scheitle, from MTU's IT department for CAE. "As the number of cluster CPUs continued to rapidly increase, we saw the necessity to find a workload management software able to provide the needed functionalities and robustness, and at the same time, minimize licensing costs. Altair's licensing system has allowed us to achieve this goal."
Erwin A. Pignitter, senior vice president and CIO of MTU Aero Engines, outlined, "MTU's high technology products require an optimal integration of IT-tools, processes and IT-infrastructure. Powerful CAE-tools like HyperWorks help us to follow that strategic direction."
"We are very pleased with MTU's decision and are looking forward to working with the company to integrate our tools into its development process," said Dr. Uwe Schramm, country manager for Altair Germany. "A growing number of aerospace manufacturers and suppliers turn to HyperWorks; and with our offerings in engineering services, our support and cloud-computing capabilities, I am sure we will be able to satisfy their needs, including the required customization, training, interfaces and support. Being an engineering company ourselves, we speak their language, understand their needs, and are able to provide them with the tools and support they ask for."
About MTU
MTU Aero Engines is Germany's leading engine manufacturer and an established global player in the industry. It engages in the development, manufacture, marketing and support of commercial and military aircraft engines in all thrust and power categories and industrial gas turbines. The German manufacturer employs approximately 8,200 people overall and with its various affiliates has a presence in all significant regions and markets worldwide. In the years ahead, MTU will focus its resources on its core business, seek stakes in emerging engine programs and expand its service offerings. For more information, please visit: www.mtu.de.
HyperWorks, a platform for innovation, is a comprehensive simulation solution for rapid design exploration and decision-making. HyperWorks provides a tightly integrated suite of best-in-class tools for all facets of the simulation process: modeling, analysis, optimization, visualization, reporting and collaborative knowledge management. Leveraging a revolutionary pay-per-usage licensing model, HyperWorks delivers maximum value and flexibility for customers worldwide. For more information, please visit: www.altairhyperworks.com.
About PBS Works
PBS Works™ is a suite of on-demand cloud computing technologies that allows enterprises to maximize ROI on computing infrastructure assets. PBS Works is the most widely implemented software environment to optimize grid, cloud, cluster and on-demand computing worldwide. The suite's flagship product, PBS Professional®, provides a flexible, on-demand computing environment that allows enterprises to easily share distributed computing resources to create and sustain competitive advantages – whether shortened time to market or improved product quality. Leveraging a revolutionary "pay-for-use" unit-based business model, PBS Works delivers increased value and flexibility over conventional software-licensing models. Visit http://www.pbsworks.com to learn more about how PBS Works makes high-performance computing faster, smarter and more productive.
About Altair
Altair Engineering, Inc., empowers client innovation and decision-making through technology that optimizes the analysis, management and visualization of business and engineering information. Privately held, with more than 1,500 employees, Altair has offices throughout North America, South America, Europe and Asia/Pacific. With a 26-year track record for high-end software and consulting services for engineering, computing and enterprise analytics, Altair consistently delivers a competitive advantage to customers in a broad range of industries. To learn more, please visit www.altair.com and www.simulatetoinnovate.com.


text:
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>com.eharmony.matching</groupId>
  <artifactId>vw-webservice</artifactId>
  <version>0.1.0-SNAPSHOT</version>
  <packaging>pom</packaging>
  <name>VW Web Service.</name>
  <description>The parent project of all the other vw web service projects.</description>

  <!-- the list of modules being aggregated by this project -->
  <modules>
	<module>vw-webservice-common</module>
	<module>vw-webservice-core</module>
	<module>vw-webservice-jersey</module>
  </modules>

  <properties>
  	<vw.webservice.version>0.1.0-SNAPSHOT</vw.webservice.version>
  	<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
  </properties>

  <dependencyManagement>
  	<dependencies>
  	 	<!-- dependencies for testing -->
        <dependency>
        	<groupId>junit</groupId>
        	<artifactId>junit</artifactId>
        	<version>4.8.2</version>
        	<scope>test</scope>
        </dependency>

        <dependency>
			<groupId>org.mockito</groupId>
			<artifactId>mockito-all</artifactId>
			<version>1.9.5</version>
			<scope>test</scope>
		</dependency>

      	<!-- end dependencies for testing -->

  		<!-- Spring dependencies. -->
 		<dependency>
 			<groupId>org.springframework</groupId>
 			<artifactId>spring-core</artifactId>
 			<version>3.1.3.RELEASE</version>
 		</dependency>

 		<dependency>
 			<groupId>org.springframework</groupId>
 			<artifactId>spring-beans</artifactId>
 			<version>3.1.3.RELEASE</version>
 		</dependency>

 		<dependency>
 			<groupId>org.springframework</groupId>
 			<artifactId>spring-context</artifactId>
 			<version>3.1.3.RELEASE</version>
 		</dependency>

 		<dependency>
 			<groupId>org.springframework</groupId>
 			<artifactId>spring-context-support</artifactId>
 			<version>3.1.3.RELEASE</version>
 		</dependency>

 		<dependency>
 			<groupId>org.springframework</groupId>
 			<artifactId>spring-expression</artifactId>
 			<version>3.1.3.RELEASE</version>
 		</dependency>

  		<!-- logback dependencies -->
		<dependency>
 			<groupId>org.slf4j</groupId>
 			<artifactId>slf4j-api</artifactId>
 			<version>1.7.5</version>
 		</dependency>

 		<dependency>
 			<groupId>ch.qos.logback</groupId>
 			<artifactId>logback-classic</artifactId>
 			<version>1.0.13</version>
 			<scope>runtime</scope>
 		</dependency>

 		<dependency>
 			<groupId>ch.qos.logback</groupId>
 			<artifactId>logback-core</artifactId>
 			<version>1.0.13</version>
 			<scope>runtime</scope>
 		</dependency>

 		<!-- google guava -->
 		<dependency>
		    <groupId>com.google.guava</groupId>
		    <artifactId>guava</artifactId>
		    <version>15.0</version>
		</dependency>

		<!-- google gson for reading json examples, used in the jsonexamplesmessagebodyreader package -->
		<dependency>
			<groupId>com.google.code.gson</groupId>
			<artifactId>gson</artifactId>
			<version>2.2.4</version>
		</dependency>

		<!-- jackson for json debug writer -->
		<dependency>
		  <groupId>com.fasterxml.jackson.core</groupId>
		  <artifactId>jackson-core</artifactId>
		  <version>2.3.1</version>
		</dependency>

		<!--  apache commons collections -->
 		<dependency>
 			<groupId>commons-collections</groupId>
 			<artifactId>commons-collections</artifactId>
 			<version>3.2.1</version>
 		</dependency>

 		<!-- apache commons lang, used for some utilities -->
		<dependency>
			<groupId>org.apache.commons</groupId>
			<artifactId>commons-lang3</artifactId>
			<version>3.2.1</version>
		</dependency>

  	</dependencies>

  </dependencyManagement>

  <build>
  	<pluginManagement>
  		<plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>2.5.1</version>
                <inherited>true</inherited>
                <configuration>
                    <source>1.7</source>
                    <target>1.7</target>
                    <fork>true</fork>
				    <meminitial>1024m</meminitial>
				    <maxmem>2048m</maxmem>
                </configuration>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-surefire-plugin</artifactId>
                <version>2.13</version>
                <executions>
                    <execution>
                        <id>surefire-test</id>
                        <phase>test</phase>
                        <goals>
                            <goal>test</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <redirectTestOutputToFile>false</redirectTestOutputToFile>
                    <includes>
                        <include>**/*Test.java</include>
                    </includes>
                    <forkMode>once</forkMode>
                </configuration>
            </plugin>

             <!-- <plugin>
                <groupId>com.google.protobuf.tools</groupId>
                <artifactId>maven-protoc-plugin</artifactId>
                0.1.10 on Maven 2.X 0.3.1 on Maven 3.X
                <version>0.1.10</version>
                <configuration>
                	<checkStaleness>true</checkStaleness>
                </configuration>
                <executions>
                    <execution>
                        <phase>generate-sources</phase>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin> -->

  		</plugins>
  	</pluginManagement>

  </build>

</project>

redpajama_set_name: RedPajamaGithub


While he's completely recovered now, cravings for honey hit me hard. I've even had DREAMS of this sumptuous spread paired with fromage on freshly baked artisan bread – it's my summer obsession, and I can't get enough of it!
So what to do then? Prepare a summer picnic (obviously) starring this unpasteurized raw artisan honey I found in Putney Market, handmade in Hungary. Specifically, unpasteurized honey is an antioxidant and in general is packed with a ton of nutrients so you need not feel guilty for having it, like everything else, within moderation! I like to drizzle it over my morning granola, and lately, I've topped off my brie on bread with it. The forest flowers used by this small producer are said to also help with insomnia so it's a nice honey to take with your bedtime tea too.
For me, the simplicity of brie on bread with honey is the perfect way to taste each of these flavors and if you're as crazy about them as I am, it's an absolute textural delight. It pairs nicely with Champagne or Prosecco with a splash of honeysuckle or elderflower cordial – whatever you fancy for your aperitif!
Brie cheese – I prefer a smooth and soft brie with an edible rind. More cheese that way!
Slice your bread and spread with butter. Top with the brie, honey, salt and pepper. Heat up in toaster oven for about 5 minutes for melt-in-your-mouth deliciousness!


What differentiates one skilled nursing & rehabilitation center from another? The answer is... the people who work and reside there! The people set the tone, the atmosphere, and the expectations. At The Laurels of Blanchester, we take great pride in ensuring that everyone feels like part of our family and that they are treated as special "guests" in our home.
The Laurels of Blanchester employs a team of highly qualified medical professionals, including a Medical Director, Registered Nurses, Restorative Care Nurses, a Wound Care Nurse, state tested Certified Nursing Assistants, Physical Therapists, Occupational Therapists, and a Speech Therapist. Our on-site Rehab, Dietary, Social Work, and Activities departments provide personalized and compassionate care to each guest. From the moment you walk through the front doors, the warmth and caring of the staff will begin to gain your trust and confidence, as they strive to exceed your expectations.
Unlike other facilities that use "contracted" staff members, each member of the team at The Laurels of Blanchester is directly employed, not "contracted". Each Team Member takes great pride in portraying "The Laurel Way of Caring", as they strive for excellence in providing only the highest standard of care and services to every guest, and to every family member and visitor. Come on in! Visit a while! Let us show you our very best... let us show you The Laurel Way.
Makinna has a passion for caring for older adults. This passion was solidified at a young age when she cared for her grandfather at home with her mother and sisters. She has always been very involved in volunteer work through her church and schools by going on mission trips in the US and overseas, and being the Student Ambassador at Lakota West High School, to highlight just a few. Knowing that's where she has been gifted, she pursued a Bachelor's degree in Gerontology and Management & Leadership from Miami University while working as a Dietary Server at the local Continuing Care Retirement Community in Oxford, OH. Determined to start her career in the field of aging, she graduated in just 3 years to begin her AIT at Otterbein SeniorLife and then transitioned into the Assistant Administrative role there, where she worked for a year and a half. Makinna joined the Laurels of Blanchester in January of 2019 as the Administrator. Makinna continues to expand her knowledge and skills in the industry by seeking opportunities for hands-on experience and continuing education as she believes she is here to serve others.
John is a native of Wilmington, Ohio and received his Associate's Degree RN from Southern State Community College. He began his career as a Staff RN on the Surgical Pediatrics Unit for Clinton Memorial Hospital. John also has experience as a Charge Nurse, a Phlebotomist, and as an Endoscopy Technician. John left Clinton Memorial in 2009 to join Community Care Hospice as a Case Manager. He then left that position to become the Assistant Director of Nursing at The Laurels of Blanchester in April of 2010. John was promoted to his current position as the Director of Nursing in September 2010. John has been in the healthcare field since 1992.
Mandi Hill COTA/L, is the Rahab Services Director at the Laurels of Blanchester. Mandi came to the Laurels in November 2015 as a PRN COTA/L and began working as the Rehab Services Director in May of 2016. Mandi was born and raised in Cincinnati, Ohio. She graduated from Cincinnati State Technical and Community college in 2012, where she earned her Associates of Applied Science as and occupational therapist assistant. Mandi has worked in a SNF since graduating in 2012. Mandi finds her career very rewarding and enjoys making a difference in the lives of many of our guests as well as in the lives of their families.
Prior to pursuing a career in skilled nursing care, Donna had a 20 year career in Crime Victim Services. She assisted crime victims within the judicial system, as well as assisted law enforcement by providing crisis response. Throughout her 20 year career, she gained valuable experience as an Advocate, Administrator, Volunteer Coordinator, Grant Writer & Community Relations Manager. Most importantly, she gained empathy for those who are going through difficult life situations. In 2015, Donna was recruited to join the Admissions & Marketing team at a Skilled Nursing & Rehabilitation Center in Montgomery. She later became their Community Relations Coordinator. She joined The Laurels of Blanchester in August of 2018 as Director of Marketing. She is a Clinton County native and resides in Blanchester with her husband Mark. They are blessed with four sons, a daughter in law and four grandchildren.


In a March lawsuit, Hertz claimed that the former executives involved pressured employees to inflate income and earnings.
Hertz Global Holdings is pushing for the return of at least $70 million from ex-CEO Mark Frissora and other ex-senior managers, Bloomberg reports.
In a March lawsuit, Hertz claimed that the former executives involved pressured employees to inflate income and earnings. The alleged scheme resulted in a federal investigation and forced Hertz to redo several years of financial reports, which cost the company more than $200 million.
An internal Hertz investigation concluded that Frissora forced Hertz employees to come up with "non-traditional accounting approaches" to meet financial targets in a "pressure-cooker" work environment created by Frissora. Through his lawyer, Frissora denied the charges.


Captive-bred (F1) adult male specimen displaying neutral behaviour patterning.
Young F1 specimen in the aquarium.
Currently known only from the type locality in the Ka Dat Chaung river system, Mon State, south-eastern Myanmar. This is part of the larger Sittaung River drainage.
In the description the type locality is described as a slow-flowing small river around 50 metres in width with very shallow (20-30 cm deep) water. The substrate was composed of boulders, small stones and sand and no aquatic plants are mentioned although there were patches of biofilm in some areas. The only sympatric species was the loach Acanthocobitis zonalternans.
The collection was made during the dry season; Mon has a tropical climate and there is a pronounced rainy season between June and November. During this period rivers swell with a marked increase in flow rate and turbidity.
Unknown. The largest specimen in the type series measured 34.6 mm but the first aquarium specimens have already exceeded 50 mm.
B. juergenschmidti will thrive in a well-structured set-up with a sand or gravel substrate plus plenty of water-worn rocks and pebbles to provide cover. Plant species that can be grown attached to the decor such as Microsorum, Taxiphyllum or Anubias species can be added if you wish but aren't essential.
Temperature: A figure of 80.4?°F/26.9?°C was recorded at the type locality in the month of March. Mon has relatively stable air temperatures with an annual average of 79.9?°F/26.6?°.
pH: 6.0 – 7.0 with 6.4 recorded at the type locality.
Hardness: Should prefer soft water within the range 18 – 90 ppm.
If you do intend to house it in a community tankmates must be chosen with care. It is slow-moving with a retiring nature and may be intimidated or outcompeted for food by larger/more boisterous tankmates. Peaceful cyprinids such as Trigonostigma or smaller Rasbora species are likely to make good choices as are gouramis and other surface-dwelling species. Accommodating it in a biotope-style community of ? fishes from Myanmar ? is trickier but a couple of suitable species known from the Sittaung basin are Danio nigrofasciatus and Acanthocobitis zonalternans.
B. juergenschmidti has been bred in captivity on at least once occasion since it was first collected in March 2010. Members of this genus are cave spawners that form temporary pair bonds and are not usually too difficult to breed provided the tank is arranged correctly (see 'tank set-up'). Other species are best omitted if you want to raise good numbers of fry although in a mature, well-furnished community a few may survive to adulthood. Either a single pair or a group of adults can be used but if using multiple males be sure to provide each with a cave to defend. Water parameters should be within the values suggested above. Feed the fish with plenty of live and frozen foods and spawning should not present too many problems.
This species is essentially unknown in the hobby at time of writing. It was discovered by German aquarist Horst Linke in early 2010 and before official description was known as B. sp. East Myanmar (Ost Myanmar in Germany). It can be differentiated from other members of the genus by a combination of characters as follows: absence of a blotch on the posterodorsal corner of its opercle; no cleithral blotch; bar 1 (on caudal fin base) in adult males broad and solid rather than reduced to a single blotch on centre of caudal peduncle or split into three separate blotches; bar 2 without a blotch on dorsolateral aspect of caudal peduncle; caudal fin of adult males with a white margin posterodorsally and posteroventrally. A more detailed synopsis can be found in Comparative notes of the original description.
Badis dibruensis, a new species (Teleostei: Badidaae) from northeastern India.
From "Species Profiles," I clicked the Cichlidae link under Perciformes, and was startled to see Badis juergenschmidti listed on page 2 of the cichlids. Maybe a wrong tag somewhere?


text:
Home Blog One Killed in Collision with 18-Wheeler on Interstate 88 in Kane County, IL
One Killed in Collision with 18-Wheeler on Interstate 88 in Kane County, IL
Kane County, IL — January 18, 2023, a 27-year-old woman died in a collision with a tractor-trailer on Interstate 88 in Kane County.
Authorities say the incident happened around 4:00 a.m. on I-88 near mile marker 118 and Mitchell Road. Preliminary investigation suggests only that the victim was driving a passenger vehicle on the highway when she somehow crashed into the back of an 18-wheeler. After the impact the car reportedly ran into the grass on the roadside.
The car's driver was transported to a local hospital where she was pronounced dead.
Folks sometimes think the fault for a rear-end collision like this lies with the striking driver basically by default, but jumping straight to that conclusion means ignoring all the ways such a crash could actually be out of that person's control.
That's why it's important to investigate more carefully and learn all the facts after just about any kind of crash—especially one with a commercial truck, which often has unique complications and hurdles. That woman's loved ones deserve no less than the whole story, and right now they may not feel like they have it. I just hope authorities will take the time and care needed to help them learn the truth.
People Often Lose Unlosable Truck Accident Cases
The 4 Most Shocking Truck Accident Scams We've Seen
Blaming the Victim — How Trucking Company Defense Attorneys Make Their Living
Police Reports Are a Joke — Don't Count on Them


text:
Import AI 149: China's AI principles call for international collaboration; what it takes to fit a neural net onto a microcontroller; and solving Sudoko with a hybrid AI system
China publishes its own set of AI principles – and they emphasize international collaboration:
…Principles for education, impacts of AI, cooperation, and AGI…
A coalition of influential Chinese groups have published a set of ethical standards for AI research, called the Beijing AI Principles. These principles are meant to govern how developers research AI, how they use it, and how society should manage AI. The principles heavily emphasize international cooperation at a time of rising tension between nations over the strategic implications of rapidly advancing digital technologies.
The principles were revealed last week by a coalition that included the Beijing Academy of Artificial Intelligence (BAAI), Tsinghua University, and a league of companies including Baidu, Alibaba, and Tencent. "The Beijing Principles reflect our position, vision and our willingness to create a dialogue with the international society," said the director of BAAI, Zeng Yi, according to Xinhua. "Only through coordination on a global scale can we build AI that is beneficial to both humanity and nature".
Highlights of the Beijing AI principles: Some of the notable principles include establishing open systems "to avoid data/platform monopolies", that people should receive education and training "to help them adapt to the impact of AI development in psychological, emotional and technical aspects", and that people should approach the technology with an emphasis on long-term planning, including anticipating the need for research focused on "the potential risks of Augmented Intelligence, Artificial General Intelligence (AGI) and Superintelligence should be encouraged".
Why this matters: Principles are ones of the ways that large policy institutions develop norms to govern technology, so Beijing's AI principles should be seen as a prism via which the Chinese government will seek to regulate aspects of AI. These principles will sit alongside multi-national principles like those developed by the OECD, as well as those developed by individual entities (eg: Google, OpenAI). The United States government is yet to outline the principles with which it will approach the development and deployment of AI technology, though it has participated in and supported the creation of the OECD AI principles.
Read more: Beijing AI Principles (Official Site).
Read more: Beijing publishes AI ethical standards, calls for int'l cooperation (Xinhua).
Faster, smaller, cheaper, better! Google trains SOTA-exceeding 'EfficientNets':
…What's better than scaling up by width? Depth? Resolution? How about all three in harmony?…
Google has developed a way to scale up neural networks more efficiently and has used this technique to find a new family of neural network models called EfficientNets. EfficientNets outperform existing state-of-the-art image recognition systems, while being up to ten times as efficient (in terms of memory footprint).
How EfficientNets work: Compound Scaling: Typically, when scaling up a neural network, people fool around with things like width (how wide are the layers in the network), depth (how many layers are stacked on top of eachother), and resolution (what resolution are inputs being processed it). For this project, Google performed a large-scale study of the ways in which it could scale networks and discovered an effective approach it calls 'compound scaling', based on the idea that "in order to pursue better accuracy and efficiency, it is critical to balance all dimensions of network width, depth, and resolution during ConvNet scaling". EfficientNets are trained using a compound scaling method that scales width, depth, and resolution in an optimal way.
Results: Faster, cheaper, lighter, better! Google shows that it can train existing networks (eg, ResNet, MobileNet) with good performance properties by scaling them up using its compound training technique. The company also develops new EfficientNet models on the ImageNet dataset – widely considered to be a gold-standard for evaluating new systems – setting a new state-of-the-art score on image identification (both top-1 and top-5) accuracy, while achieving this with around 10X fewer parameters than other systems.
Why this matters: As part of the industrialization of AI, we're seeing organizations dump resources into learning how to train large-scale networks more efficiently, while preserving the performance of resource-hungry ones. To me, this is analogous to going from the expensive prototype phase of production of an invention, to the beginnings of mass production.
Read more: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (Arxiv).
Read more: EfficientNet: Improving Accuracy and Efficiency through AutoML and Model Scaling (Google AI Blog).
Pairing deep learning systems with symbolic systems, for SAT solving:
…Using neural nets for logical reasoning gets a bit easier…
Researchers with Carnegie Mellon University and the University of Southern California have paired deep learning systems with symbolic AI by creating MAXSAT, a differentiable satisfiability solver that can be knitted into larger deep learning systems. This means it is now easier to integrate logical structures into systems that use deep learning components.
Sudoko results: The SATNet model does well against a basic ConvNet model, as well as a model fed with a binary mask which indicates which bits need to be learned. SATNet outperforms these systems, scoring 98.3% on an original sudoko set when given the numeric inputs. More impressively, it obtains a score of 63.2% on 'visual sudoko' (traditional convnet: 0%), which is where they replace the digits with handwritten MNIST digits and feed it in. Specifically, they use a convnet to parse the figures in the Sudoko image, then pass this
Why this matters: Hybrid AI systems which fuse the general utility-class capabilities of deep learning components with more specific systems seems like a way to bridge traditional and symbolic AI, and making such systems be easy to add into larger systems. "Our hope is that by wrapping a powerful yet generic primitive such as MAXSAT solving within a differentiable framework, our solver can enable "implicit" logical reasoning to occur where needed within larger frameworks, even if the precise structure of the domain is unknown and must be learned from data".
Read more: SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver (Arxiv).
Squeezing neural nets onto microcontrollers via neural architecture search:
…Get ready for billions of things to gain deep learning-based sense&respond capacity…
Researchers with ARM ML Research and Princeton University want to make it easier for people to deploy advanced artificial intelligence capabilities onto microcontrollers (MCUs) – something that has been difficult to do so far because today's neural networks techniques are too computationally expensive and memory-intensive to be easily deployed onto MCUs.
MCUs and why they matter: Microcontrollers are the sorts of ultra-tiny lumps of computation embedded in things like fridges, microwaves, very small drones, small cameras, and other electronic widgets. To put this in perspective, in the developed world a typical person will have around four distinct desktop-class chips (eg, their phone, a laptop, etc), while having somewhere on the order of three dozen MCUs; a typical mid-range car might pack as many as 30 MCUs inside itself.
MCUs shipped in 2019 (projection): 50 billion
GPUs shipped in 2018: 100 million
"The severe memory constraints for inference on MCUs have pushed research away from CNNs and toward simpler classifiers based on decision trees and nearest neighbors", the researchers write. Therefore, it's intrinsically valuable to be able to figure out how to train neural networks so they can fit into the small computational budget of an MCU (2k of RAM versus 1GB for a Raspberry Pi or 11GB for an NVIDIA 1080Ti GPU). To do this, the ARM and Princeton researchers have used multi-objective neural architecture search to jointly train networks that can fit inside the tight computational specifications of an average MCU.
Sparse Architecture Search (SpArSe): Their technique combines neural architecture search with network pruning, letting them jointly train a network against multiple objectives while continuously zeroing out some of its parameters during training. This makes it both easier to perform the (computationally expensive) NAS procedure, and creates better networks once training is finished. "Pruning enables SpArSe to quickly evaluate many sub-networks of a given network, thereby expanding the scope of the overall search. While previous NAS approaches have automated the discovery of performant models with reduced parameterizations, we are the first to simultaneously consider performance, parameter memory constraints, and inference-time working memory constraints". SpArSe considers regular, depthwise, separable, and downsampled convolutions, and uses a Multi-Objective Bayesian Optimizer (MOBO!) for training.
Results: powerful performance in a small package: The researchers test their approach by training networks on the MNIST, CIFAR-10, CUReT, and Chars4k datasets. Their system obtains higher accuracies with lower parameters than other methods, typically out-performing them by a wide margin.
Why this matters: Techniques like neural architecture search are part of the broader industrialization of AI, as they make it dramatically easier for people to develop and evaluate new network types, essentially letting people trade off a $/computation cost against the $/AI-researcher-brain cost of having people come up with newer architectures. Though accuracies remain somewhat belower where we'd need for commercial deployment (the highesrt score that SpArSe obtains ia around 84% accuracy on image categorization for CIFAR-109, for instance), techniques like this suggest we'll soon deploy crude sensing and analytical capabilities onto potentially billions to trillions of devices across the planet.
Read more: SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers (Arxiv).
Judging synthetic imagery with the Classification Accuracy Score (CAS):
…Generative models are progressing, but how do we measure that? DeepMind has a suggestion…
How do we know an output from a generative model is, for lack of a better word, good? Mostly, we work this out by studying the output and making a qualitative judgement, eg, we'll look at a hundred images generated by a big generative model and make a judgement call based on how reasonable the generations seem, or we'll listen to the musical outputs of a model and rate it according to how well such outputs conform to our own sense of appropriate rhythm, tone, harmony, and so on. The problem with these evaluative schemes is that they're highly qualitative and don't give us good ways to quantitatively analyze the outputs of such models.
Now, researchers from DeepMind have come up with a new evaluation technique and task, which they call Classification Accuracy Score (CAS), to better assess the capabilities of generative models. CAS works by testing "the gap in performance between networks trained on real and synthetic data", and in particular is designed to surface pathologies in the generative model being used.
CAS works like this: "for any generative model… we learn an inference network using only samples from the conditional generative model, and measure the performance of the inference network on a downstream task". The intuition here is that "if the model captures the data distribution, performance on any downstream task should be similar whether using the original or model data".
$$$: Researchers can expect to pay a few tens of dollars to evaluate any given system using the benchmark. "At the time of writing, one can compute the metric in 10 hours for roughly $15, or in 45 minutes for roughly $85 using TPUs", they write.
Putting models under the microscope with CAS: The researchers use CAS to evaluate three generative models, BigGAN, Hierarchical Autoregressive Models (HAM), and a high-resolution Vector-Quantized Variational Autoencoder (high-res VQ-VAE). The evaluation surfaces a couple of notable things. 1) both the Hierarchical Autoregressive system and the High-Res VQ-VAE significantly outperform BigGAN, despite BigGAN generating some of the qualitatively most intriguing samples. The metric also helps identify which models are better at learning a broad set of distributions over the data, rather than over-fitting to a relatively small set of classes. This method also shows that high CAS scores don't correlate to FID or Inception, highlighting the significant difference in how these metrics work.
CAS, versus other measures: There are other tools available to assess the outputs of generative models, including metrics like Inception Score (IS) and Frechet Inception Distance (FID). These techniques try to give a quantitative measure of the quality of the generations of the model, but have certain drawbacks. "Inception Score does not penalize a lack of intra-class diversity, and certain out-of-distribution samples to produce Inception Scores three times higher than that of the data. Frechet Inception Distance, on the other hand, suffers from a high degree of bias.
Why this matters: One of the challenges of working in artificial intelligence is working out what progress represents a real improvement, and what progress may in fact be illusory. Key to this is the development of more advanced measurement and assessment techniques. Approaches like CAS show us:
a) how surprisingly difficult it is to evaluate the capabilities of increasingly powerful generative models
b) how (unintentionally) misleading metrics can be about the true underlying performance of a system
c) how as we develop more advanced systems, we'll likely need to develop more sophisticated assessment schemes.
All of this feels like a further sign of the advancing sophistication and deployment of AI systems – I'm wondering at what point AI evaluation becomes its own full-fledged sub-field of research.
Read more: Classification Accuracy Score for Conditional Generative Models (Arxiv).
Drones learn in simulators, fly in reality:
…Domain randomization + drones = robust flight policies that cross the reality gap…
Researchers with the University of Zurich and the Intelligence Systems Lab at Intel have developed techniques to train drones to fly purely in simulation, then transferring to reality. This kind of 'sim2real' behavior is highly desirable for AI researchers, because it means systems can be rapidly developed and iterated on in software simulators, then executed and validated in the real world. Here, we can see how these techniques can be applied to let researchers train the perception component of a drone exclusively in simulation, then transfer it to reality.
How it works: domain randomization: This project relies on domain randomization, a technique some AI researchers use to generate additional training data. For this work, the researchers use a software-based simulator to generate various permutations of the environments that they want the drone to fly in, randomizing things like the visual properties of a scene, the shape of a gate for the drone to fly through, the background of the scene, and so on. They then generate globally optimal trajectories through these simulated courses, and the simulated drones are trained via imitation learning to mimic these policies. Because this is reinforcement learning, the drones are initially absolutely terrible at this, crashing frequently and generally bugging out. The authors solve the data collection task here by, charmingly, carrying the quadrotor through the track – they refer to this as "handheld mode".
Testing: In tests, the researchers show that "more comprehensive randomization increases the robustness of the learned policy to unseen scenarios at different speeds". They also show that network capacity has a big impact on performance, so running extremely small (and therefore computationally cheap) networks comes with an accuracy loss. They show that they can train networks which can generalize to different track layouts than onces they've been exposed to, as well as radically different real-world lighting conditions (which have frequently been a confounding factor for research in the past). In real world tests, the method does is able to perform on-par with human professional pilots at successfully navigating through various hoops in the track, though takes substantially longer (best human lap time: around 5 seconds; best drone lap time: between 12 and 16 seconds). They also show that systems trained with a mixture of simulated and real data can outperform systems trained purely with real world data alone.
Conclusion: Work like this gives us a sense of how rapidly drone systems are advancing in complexity and capability, and highlights how it's going to be increasingly simple for people to use software-based tools to train drones either entirely or significantly in simulation, then transfer them to reality. This will likely speed up the prace of AI R&D progress in the drone sector (by making it less critical to test on real-world hardware), and makes them likely to be used as a destination for certain hard robotics benchmarks in the future.
Read more: Deep Drone Racing: From Simulation to Reality with Domain Randomization (Arxiv).
Watch a video of the work here (official YouTube video).
Racing Brains
"Hey, Mark! This car thinks it's a drone!" he shouted, right before the car accelerated up the ramp and became airborne: it stayed in the air for maybe three seconds, and we watched its wheels turn pointless in the air; the car's drone-brain thought it was reasonable to try and control it mid-air, and it wouldn't learn that reality thought otherwise.
It landed, kicking up a cloud of dust around it, and skidded into a tight turn, then slipped out of view as it made its way down the course. A few people clapped. Others leaned in and joked with eachother. Some money changed hands. Then we all turned to look to the next vehicle coming down the course – this one was an electronic motorbike: lightweight, fast, sounding like a hornet as it came down the track. It took the ramp at speed, then landed and started weaving from side to side, describing a snake-like sinusoidal pattern in the dust of the track.
"What was in that thing?" I said to my friend.
"Racing eel – explains the weaving, right?"
We looked at the dust and listened to the sounds of the machines in the distance. Then we all turned our heads and looked to the left to see another machine come over the horizon, and guess at where its brain came from.
Things that inspired this story: Imitation learning; sim2real; sim2x; robots; robots as entertainment; distortion and contortion as an aesthetic and an art form.


Completion of Craft Apprenticeship Training with at least 3 years relevant work experience.
The information collected is solely used for recruitment purpose ONLY. Unsuccessful applications will be destroyed after the recruitment activities.


While lots of folks may be happy with 12 colors, there are those of us that would just rather have like 150. Or 352. That's why I recommend a few different brands that offer a variety of color ranges. If you have a local art store, it's a great place to go and check colors out, try pens, and chat up the artsy employees who can help you find the right thing for coloring in your map aka work of art.
And as it's your work of art, you can have as few or as many colors as you damn well please.
Whatever colors you choose, at least one will be required if you want to map something. Otherwise, you'll be looking at a lovely black and white drawing—which is fine, if that makes you happy.
For the rest of us mappers, choose whatever colors and number of colors you want. You don't have to think about it too much unless you want to. I am a person who wants to, so a few tips below.
Test the colors out on the material you choose; for posters, you can also get a Color Tester, like the one above, which will allow you to test a whole bunch of shades and how they look together.
Below is a sampling of ProMarker colors I tested on the back of my canvas, which I encourage you to do as well. There's plenty of space on the back of even the smallest canvas to test colors and combos.
As a matter of personal preference, I like to choose colors in odd numbers like 3, 5, 7 because there is some part of my brain that thinks this is better than 2, 4, or 6. There may or may not be an art theory that supports this belief.
When coloring a map with swirls that are divisible by 10, I enjoy using 10 colors because it makes it easier for me to count how many I've colored in. I may be the only person who cares about this, but I still often choose 10 colors.
One brilliant soul commented that he would like to map how he felt as he accomplished the action for each swirl and would assign colors to represent his emotions as a way to see how he was feeling over the course of his goal tracking. Totally optional and totally rad. Just one way to approach it.
If you have a special brain like I do and hate the idea of swirls of the same color touching, I recommend using more than 7 colors. I burn a lot of calories (not really) trying to make sure that my colors don't touch too closely together. Again, this is just part of my charm and totally unnecessary.
Please let me know how your color choosing goes and feel free to tag on social with #mapcolors if you're game.


and its a critical age, as few faults could appear.
another 4-6 weeks before I make final decision on whether to keep her or not.
Lovely name - and lovely to see her developing - I hope she continues to fulfill the promise which she clearly shows.


Weight: 5.00 lbs FREE SHIPPING OVER $50!
When dealing with full travel lifters, certain engines respond better to a light pre-load because it recovers more quickly from any bad harmonics in the valve train. Others work better with a heavy pre-load because oil volume is reduced under the plunger, which increases stiffness. COMP Cams® Short Travel Hydraulic Roller Lifters allow you to have the advantages of both light pre-load and reduced oil volume, producing the most stable and highest revving hydraulic lifter available.
Not compatible with Multi-Displacement System (MDS). Must replace MDS lifter trays with standard lifter trays.


SAN ANTONIO, Texas — Air Force Airman 1st Class Shane Harris-Capuano graduated from basic military training at Lackland Air Force Base.
Harris-Capuano earned distinction as an honor graduate.
He is the son of Lauren Harris of Angiers Lane, Tenants Harbor, Maine, and Rob Capuano of River Road, Farmington.
The airman graduated in 2006 from Oyster River High School, Durham, and received a bachelor's degree in 2010 from Lewis and Clark College, Portland, Ore.


T Optics 100% HP Compatible 1000BASE-ZX1470nm SFP 80km .
T Optics 100% HP Compatible 1000BASE-ZX1510nm SFP 80km .
T Optics 100% HP Compatible 1000BASE-ZX1530nm SFP 80km .
T Optics 100% HP Compatible 1000BASE-ZX1570nm SFP 80km .
T Optics 100% HP Compatible 1000BASE-ZX 1610nm SFP 80km .


Ready to move to SharePoint?
This checklist will walk you through everything you need to keep in mind when migrating to SharePoint.
Planning on migrating to SharePoint? Benjamin Niaulin, Office Servers and Services MVP, walks you through the various stages of the migration process.
Whether you're migrating from a previous version of SharePoint, planning a move to Office 365, or simply moving files from local file shares, you're sure to find this checklist helpful.


text:
Q: Object Assignment in PHP First, sorry for the stupid question, but I was reading an article in php.net and I couldn't understand what exactly it says.
<?php
class SimpleClass
{
    // property declaration
    public $var = 'a default value';

    // method declaration
    public function displayVar() {
        echo $this->var;
    }
}
?>

<?php

$instance = new SimpleClass();

$assigned   =  $instance;
$reference  =& $instance;

$instance->var = '$assigned will have this value';

$instance = null; // $instance and $reference become null

var_dump($instance);
var_dump($reference);
var_dump($assigned);
?>

And this outputs this:
NULL
NULL
object(SimpleClass)#1 (1) {
   ["var"]=>
     string(30) "$assigned will have this value"
}

$instance and $reference point to same place, I get this and I understand why we get NULL and NULL for them.
But what about $assigned? It's it also pointing the place where $instance is stored? Why when we use $instance->var it affects $assigned, but when we set $instance to be null, there is no change for $assigned?
I thought that the all three variables point to one place in the memory, but obviously I'm wrong. Could you please explain me what exactly happens and what is $assigned? Thank you very much!

A: $reference points to the value of $instance, which is itself a reference to an object. So when you change the value contained by $instance, $reference reflects this change.
$assigned, on the other hand, is a copy of the value of $instance, and independently points to the object itself to which $instance refers. So when the value $instance is updated to point to nothing (i.e. null), $assigned is not affected, since it still points to the object, and doesn't care about the contents of $instance.

A: Setting $instance = null; doesn't update $assigned because it is not updating the data at the location where $instance points. It is instead modifying the $instance pointer itself so that pointer no longer points at the same data as $assigned.

A: An object is a separate entity in memory which can have 1 or more references. If it got 0, it is garbage collected.
A variable containing an object actually points to (refers to) that object.
So when you do this:
$var1 = new Object();
$var2 = $var1;

you just create two variables, pointing to the same object ($var2 copies the value of $var1, but that value is the reference to the object).
If you then write, $var1 = null, you remove that one reference, but $var2 still points to the object.
The & operator actually returns a reference to the variable behind it, so when you write
$var1 = &var2;

then $var1 doesn't point to the object to which $var2 points as well, but $var1 points to $var2 itself. So when you make $var2 null, $var1 points to that same null.

A: With the following line, we reserve a memory location, in which storing the new Object, and a pointer to it, labeled as $instance:
$instance = new SimpleClass();

With the following line, we create a reference to the pointer $instance, labeled as $reference:
$reference =& $instance;

With the following line, we reserve a new memory location, labeled as $assigned, different and indipendent from the one above, in which we store a copy of the pointer (not the object itself) created above:
$assigned = $instance;

By setting $instance to null, you will unset only the pointer to the memory location which contains the actual object, not the object itself. Any other reference to it (for instance, $reference) will be unset as well.
$assigned is an indipendent copy of the pointer (held in another memory location), which still points to the actual object.
This is why it can be still used to refer to the actual object.
This comment found in the PHP documentation comes in support of what above said:
<?php
class A {
    public $foo = 1;
}

$a = new A;
$b = $a;
$a->foo = 2;
$a = NULL;
echo $b->foo."\n"; // 2

$c = new A;
$d = &$c;
$c->foo = 2;
$c = NULL;
echo $d->foo."\n"; // Notice:  Trying to get property of non-object...
?>

Note
This represents a kind of exception when speaking about memory management. Whereas copying a variable or array is addressed just by to use the = operator, with objects you shall explicitely use the clone keyword, as stated in the PHP documentation:

An exception to the usual assignment by value behaviour within PHP
  occurs with objects, which are assigned by reference in PHP 5. Objects
  may be explicitly copied via the clone keyword.

A: Short answer, when you create a reference using &, this is what happens:
$A  ===+
       |===> [symbol table entry x] ====> (memory location)
$B  ===+

When you do a normal assignment after that:
$A  ===+
       |===> [symbol table entry x] ===> (memory location)
$B  ===+                                    ^
                                            |
$C  =======> [symbol table entry y] ========+

Let's step through the code:
$instance = new SimpleClass();

$assigned   =  $instance;

Assertion:
$assigned === $instance

Both $assigned and $instance reference the same instance of SimpleClass.
$reference  =& $instance;

Assertion:
$assigned === $instance === $reference

All variables reference the same instance.
$instance->var = '$assigned will have this value';

Assertion:
$assigned === $instance === $reference

Even though a property of $instance is changed, it doesn't affect the references.
$instance = null; // $instance and $reference become null

Because $reference is just an alias in the symbol table, it gets the same value as $instance; the reference count of the the original instance (i.e. memory location) gets reduced to 1, the $assigned variable.

A: As you can see in the code

$instance = null; // $instance and $reference become null

$instance has now become equal to null, but before then $assigned was set. so $assigned did not get the null value. $reference received the null value because you referenced it with =& it keeps the value of $instance.

A: It's really simple:
$a = 3;
$b = $a;
$c = &$a;
$a = 0;

var_dump($a);
var_dump($b);
var_dump($c);

The output will be:
int(0)
int(3)
int(0)

So it not only object assignment but also normal assignment.

redpajama_set_name: RedPajamaStackExchange


text:
NASA Satellite orbiting Earth Credit: Nasa / Unsplash
Study: Why troposphere warming differs between models and satellite data
Zeke Hausfather
Global temperatureStudy: Why troposphere warming differs between models and satellite data
The most common measure of global temperature rise is here on the Earth's surface, but scientists also gather data on how temperatures in the atmosphere high above us are changing.
Of particular interest is the troposphere – the lowest layer of the atmosphere where almost all of our weather occurs. To track temperatures, scientists use satellites, which have been providing data since they were first launched in the late 1970s.
Since around the start of the 21st century, the tropospheric warming recorded by satellites has been slower than the rate projected by climate models. In a new study, published in Nature Geoscience, researchers find that these differences are outside the range of what we would expect from natural variability.
Instead, they say the differences could be down to recent changes in greenhouse gas emissions, solar output, volcanic eruptions and air pollution that weren't anticipated in the assumptions made by climate modellers.
Overall, the study suggests that while tropospheric warming has not accelerated to the extent that models have predicted in recent years, there's little evidence that it has slowed down.
Temperatures from satellites
Much of our historical temperature data comes from weather stations, ships, and buoys on the Earth's surface. Since 1979 temperature records of the atmosphere are also available from satellite-based microwave sounding units (MSU). These measure the "brightness" of microwave radiation bands in the atmosphere, from which scientists can estimate air temperatures.
However, the bands measured by the satellite instruments cannot easily provide the temperature of a specific layer of the atmosphere. Researchers have identified particular sets of bands that correspond to the temperature of the lower troposphere (TLT) spanning roughly 0 to 10 km, the middle troposphere (TMT) spanning around 0 to 20 km and the lower stratosphere (TLS) spanning 10 to 30 km.
Unfortunately, these bands tend to overlap a bit. For example, TMT estimates will include part of the lower stratosphere, while TLT estimates will include some surface temperature. These overlaps matter because different parts of the atmosphere are expected to react very differently to climate change.
When greenhouse gases trap incoming solar radiation, they tend to increase the temperature of the surface and lower atmosphere, and decrease the temperature of the upper atmosphere as less solar radiation is escaping. We see this in satellite observations and data from weather balloons, where the lower stratosphere is cooling while the underlying troposphere and surface are warming.
Because the tropospheric temperature estimates from satellites overlap with part of the stratosphere, they end up combining a bit of stratospheric cooling with tropospheric warming and can underestimate the true rate of warming. To avoid this issue, the new study applies a correction to remove some of the stratospheric cooling from the TMT series. The approach they use for this is described in a previous paper published in the Journal of Climate.
Correcting errors in the data
Dealing with stratospheric contamination is not the only challenge when working with satellite data. Unlike on the surface where there are tens of thousands of individual observation stations, there are only around two to three MSU satellites taking measurements at any given time, and the satellites only last about five-to-ten years before they need to be replaced.
While the satellites are designed to pass over the same part of the earth at the same time every day, that changes as their orbits decay. A satellite that once took the temperature over London at 2pm ten years ago, for example, might now be taking it at 8pm. Changing the observation times has a big effect on the temperatures measured, and researchers need to correct their measurements for this.
Similarly, a replacement satellite might measure temperatures slightly differently from its predecessor. Around the year 2000, for example, the instrument in the satellites was changed to an upgraded version of the sensor. All of these can potentially introduce bias into measurements that need to be addressed.
There are two main groups that process the same underlying MSU data to estimate atmospheric temperatures: the University of Alabama, Huntsville (UAH) and Remote Sensing Systems (RSS). Each group has a different set of assumptions to correct for various issues in the data, and they end up with fairly different results. You can see how the UAH (yellow line) and RSS (blue) figures differ in the chart below – particularly after the year 2000.
Annual global mean middle tropospheric temperatures from RSS and UAH from 1979 through 2016, covering from 82.5 N–82.5 S. No stratospheric adjustments are included as an adjusted UAH dataset is not available. Chart by Carbon Brief using Highcharts.
While RSS generally agrees with the rate of warming seen globally in surface temperature records, UAH shows much less warming – including a more pronounced slowdown in temperature rise after 1998. The differences between satellite records are much larger than those between different surface temperature estimates. Co-author Dr Carl Mears, the co-founder of RSS, suggests that:
"In general, I think that the surface datasets are likely to be more accurate than the satellite datasets. The between-research spreads are much larger than for the surface data, suggesting larger structural uncertainty."
These large uncertainties between satellite datasets somewhat complicate any comparison of tropospheric temperatures with climate models, as it makes it unclear if the disagreement is due to issues in the models or in the observations, and leaves open the possibility that additional corrections to the data may happen in the future.
Comparisons with climate models
In their paper, the researchers employed a number of different statistical tests to compare climate models and observations of TMT. They corrected both models and observations for stratospheric cooling influence, and compared the two over the period from 1979 through 2016 as shown in the figure below. The upper chart shows the model output and the lower chart shows the observations from RSS.
Top panel shows stratosphere-corrected RSS TMT compared to the CMIP5 multimodel average TMT. Bottom panel shows the difference between the two over time. Source: Santer et al. (2017)
While the rate of warming in the models and observations is pretty close prior to the year 2000, the differences after 2000 are much larger. Some of these differences are explained by short-term natural variability, such as El Niño events, which do not necessarily occur at the same time in the models as in the observations and tend to average out. However, even with this removed from the observations, the researchers find that notable differences remain.
To explain these differences, the researchers tested a number of different possible factors. First, they looked to see if the difference could be explained by longer-term multi-decadal natural variability from El Nino and ocean temperature oscillations that was not captured in the model average.
They found that while natural internal variability can explain most of the relatively small differences between modeled and observed tropospheric warming in the last two decades of the 20th century, but can't fully explain why model tropospheric warming is larger than in the satellite data during much of the early 21st century.
Second, they looked to see if the difference might be caused by models being too sensitive to CO2. They found no discernable relationship between model sensitivity and their ability to accurately predict tropospheric temperatures over this period.
The conclusion the researchers came to was that the model-observation discrepancy isn't down to a single factor, but a combination. Specifically, they posit that it is due to a combination of internal variability and that models got some climate forcings wrong in recent years.
Climate models used historic data for factors like greenhouse gas concentrations, solar output, volcanic eruptions, air pollution, and other factors that can affect the climate through 2005 or so, but after that point made assumptions of how these would change in the future. Recent research has suggested that a series of moderate volcanic eruptions, a long and unusually low minimum in the sun's energy output during the last solar cycle, and an uptick in particulate pollution from Chinese coal-fired power plants have all changed these forcings in ways unanticipated by the modelers.
These forcings will be updated in current modeling effort, called CMIP6, being done in preparation for the next Intergovernmental Panel on Climate Change report. This new generation of models, featuring forcings closer to observations in recent years, will likely show better correspondence with tropospheric temperature observations, but may not be any more or less sensitive to CO2 than the prior generation of models (CMIP5).
According to Dr Gavin Schmidt, director of NASA's Goddard Institute for Space Studies, who was not involved in the paper, there are even plans to rerun the older CMIP5 generation of climate models with updated forcings to see what happens if those are updated in isolation without changing other factors.
Ultimately, the paper finds that while there is a mismatch between climate models and observations in the troposphere since the year 2000, there is little evidence to-date that the model/observation differences imply that the climate is less sensitive to greenhouse gases. The results suggest that while these short-term differences between models and observations are a subject of great scientific interest, it does not diminish the reality of long-term human-driven warming.
Santer, B. D. et al. (2017) Causes of differences in model and satellite tropospheric warming rates, Nature Geoscience, doi:10.1038/ngeo2973
View Comments (24) Close Comments


text:
CTSI launches Consumer Day at Bournemouth Conference
Today (Thursday 2 July 2015) CTSI will launch it's first ever Consumer Day during Conference at Bournemouth International Centre.
Consumer Day gives local consumers and consumer organisations the opportunity to engage with one another and hear about current issues. The day begins with a Plenary Session facilitated by BBC presenter Winifred Robinson, 'Coming together to help the individual' a consumer focused discussion with an excellent panel of guests including Gillian Guy CBE chief executive of Citizens Advice.
With National Scams Awareness Month launched yesterday (1 July 2015) by Citizens Advice, the morning plenary will focus on consumer issues and scams with panel members discussing the campaign.
Scams Awareness Month 2015 (SAM15) runs throughout July with the theme "Don't be Rushed, Don't be Hushed". The campaign is asking people to keep two things in mind whenever they receive an unsolicited approach or when looking for goods or services: don't be rushed and don't be hushed. People should take their time making a decision and be sure of their facts before parting with money or personal information, and speak out when they think they've spotted a scam. This campaign is encouraging residents to report suspicious activities, get advice if they think they've been conned, and to warn others to help stop scams from spreading.
Trading standards supports the campaign by urging people to get advice if they think they've been conned and to warn others to help stop scams spreading. The extensive work of trading standards officers has been fundamental in creating more knowledge and understanding for consumers of the risks of scams and tackling the issue continuously.
Between April 2014 and March 2015, 41 per cent of scams reported to Citizens Advice were cold calls. Fraudulent banking services, dodgy credit brokers and bogus investment opportunities were reported as being the highest recorded type of cold calls.
CTSI chief executive Leon Livermore said: "Protecting vulnerable people from scams is a task which trading standards take very seriously. We deal with heart breaking cases of financial loss and mental anguish. Unfortunately a huge number of scams go unreported, leaving the path clear for these scammers to devastate lives and we urge citizens report fraudsters.
Scams Awareness Month reaches out to guide those most at risk, helping them to spot a fraudster, report them and avoid falling victim to these sinister schemes in the first place."
Gillian Guy, Chief Executive of Citizens Advice said: "Scammers can target anyone, anytime. Our research found that scams are most likely to be cold calls, posing as financial services and going on to steal people's details.
"Scams are not only bad for consumers, but bad for business too. Rogue tradesmen, fake online ads and false investment opportunities all undermine genuine businesses. Reporting scams is the only way to protect more people from getting conned, and keep our businesses from being out-done by fraudulent offers that are too good to be true."
Lord Toby Harris, Chair, National Trading Standards said: "Our National Trading Standards teams are actively pursuing criminals that deceive consumers through scams. This includes operators behind online scams – such as free trial scams for products like diet pills – postal scams and doorstep crime.
Our investigations are informed by people reporting suspected scams to Citizens Advice, but we know that there are thousands of cases each year that go unreported. National Trading Standards is pleased to support Scams Awareness Month and we hope that it will encourage many more people to come forward to report potential scams.
If you suspect that you or someone you know may be at risk of falling victim to a scam we urge you to contact the Citizens Advice consumer service on 03454 04 05 06."
Main Conference Sponsor
Millions of people a year in the UK fall prey to scammers. Estimates of the total cost of mass-market scams run to £5 billion, but with few consumers reporting them, the loss could be a lot higher. Research shows that fewer than one in 20 victims report scams to the authorities. But it isn't only about money. Scams blight people's lives and lead to emotional trauma for families and loss of confidence among victims and consumers worried they'll be next.
This is the first year Consumer Day has been launched at CTSI annual conference. For more information please visit our website: http://www.tradingstandards.uk/events/consumerday.cfm
Scams Awareness Month information can be found on the Citizens Advice website: https://www.citizensadvice.org.uk/about-us/campaigns/current_campaigns/scams-awareness-month/scams-awareness-month/
From April 2014 - March 2015, Citizens Advice dealt with 20,689 fraud and scam cases. This comprises 14,933 cases dealt with by the Consumer Service, and 5,756 cases handled by local Citizens Advice.
For further information please contact the CTSI press office on 01268 582240 or pressoffice@tsi.org.uk


text:
Sida confusa är en malvaväxtart som beskrevs av Hassler. Sida confusa ingår i släktet sammetsmalvor, och familjen malvaväxter. Inga underarter finns listade i Catalogue of Life.

Källor

Sammetsmalvor
confusa


text:
Stan Getz song lyrics
ABDEGIKMOTWZ
Any Old Time of Day
Darling Joe
I Never Had a Chance
Midnight Samba
This Can't Be Love
Where Flamingos Fly
About Stan Getz
One of the greatest tenor saxophonists, Stan Getz played in several major swing big bands while a teenager before recording his debut as a leader in 1946. Though his main early influence was Lester Young, Getz broke away from Young's style, spent 1958-1960 in Europe, and returned to the U.S., where he helped usher in the bossa nova era by recording Jazz Samba with Charlie Byrd and Getz/Gilberto with Antonio Carlos Jobim and João Gilberto. The latter was his biggest seller, thanks to "The Girl from Ipanema." Afterward, Getz chose to play more challenging jazz and proved that he was not shy to take chances, exploring aspects of fusion. ~ Scott Yanow
Stan Getz discography
386 discs
Stan Getz songs in January