text:
Q: How can I reuse the same  in different complex type definitions? I'm writing a schema for XML files that describe chapters of articles, papers, books, whatever.  The highlevel concept is that a <chapter> can have any number of paragraphs <par>, sections <section>, images and lists.  Now, the same holds for a section, it too can have any number of paragraphs, images, lists; so can subsections (not implemented yet).
My current schema looks is this:
<xs:complexType name="chapter-type">
  <xs:choice maxOccurs="unbounded">
    <xs:element name="section" type="section-type" />
    <xs:element name="par" type="par-type" />
    <xs:element name="image" type="image-type" />
    <xs:element name="ol" type="list-type" />
    <xs:element name="ul" type="list-type" />
  </xs:choice>
</xs:complexType>
<xs:complexType name="section-type">
  <xs:choice maxOccurs="unbounded">
    <xs:element name="par" type="par-type" />
    <xs:element name="image" type="image-type" />
    <xs:element name="ol" type="list-type" />
    <xs:element name="ul" type="list-type" />
  </xs:choice>
</xs:complexType>
<!-- <subsection> and other content-containing elements will repeat the par, image, ol, ul -->

As you can see, there is a lot of repetition and it'll get "worse" with subsections and other places where I'd like to reuse the content of a chapter/section.
I could add a new element, say <content> or whatever, to wrap the paragraphs/image/lists but that would then require me to add that element into my XML.  And that's what I'd like to avoid.
So my question is: how can I avoid repeating these elements everywhere?

A: Use named groups.
<xs:group name="paragraphs-etc">
  <xs:choice>
    <xs:choice minOccurs="0" maxOccurs="unbounded">
      <xs:element name="par" type="par-type" />
      <xs:element name="image" type="image-type" />
      <xs:element name="ol" type="list-type" />
      <xs:element name="ul" type="list-type" />
    </xs:choice>
  </xs:choice>
</xs:group>

Then refer to the groups from your complex types:
<xs:complexType name="chapter-type">
  <xs:choice maxOccurs="unbounded">
    <xs:element name="section" type="section-type" />
    <xs:group ref="paragraphs-etc"/>
  </xs:choice>
</xs:complexType>
<xs:complexType name="section-type">
  <xs:group ref="paragraphs-etc"/>
</xs:complexType>

The repetition information for a group reference comes from the group reference, not the group definition.  (Hence the wrapping of the paragraphs-etc group in an otherwise unnecessary xs:choice -- it ensures that any reference to the group is a reference to a repeatable set of choices.)


OESF Portables Forum > Hardware problems with pdaXrom..
Full Version: Hardware problems with pdaXrom..
Do you have a piece of hardware thats not working under pdaXrom like a CF network card, USB controller etc?
Please post your cardctl ident and cardctl status and all other info you can find about the card (links to drivers etc.) - then we will try and fix them one at a time and try and make sure that pdaXrom supports as many accessories as possible.
We will probally be holding an IRC meeting with all user who are having problems with hardware but this is meant to be a warm up to see how many problems there are and how much time it will take to fix them.
There are a few people on these boards that use cheap and nasty Zonet ZCF1100 wireless cards, including me.
product info: "AmbiCom BT2000C", "Bluetooth PC/CF Card", "", ""
has somebody any experiences with the audiovox RTM 8000 and RC8?
I had the bad vcc error at first, just like he/she did.
So, since i really dont know anything but how to follow instructions, I am at a loss.
I think Laze said there would be a how-to with this card sometime after RC8 release. I guess we wait!
card "LA4137 Spectrum24 CF WLAN CARD"
product info: "RACTOC", "USB HOST CF+ Card"
Connect to GPRS. It works.
My card is ready, and the cardctl suspend then resume doesnt work.
When dialing I get, /usr/sbin/ppd: unrecongnized option"
Ill just redo the whole process to make sure everythink is right.
Good to know it is working for others!
How about the pocketop IR keyboard?
What can I do to help someone get some working drivers going?
shows proper ESSID, Mode, Frequency and Encryption Key.
ping my AP or other PCs in my home network losses all packages.
product info: "NETGEAR", "MA701 Wireless CF Card", ""
Thanks for all the hard work on the rom!
My Billionton CFLA-100N 10/100 FastEthernet Compact Flash LAN Adapter doesn't work 'out of the box'.
card "Billionton CFLA-100N 10/100 FastEthernet"
version "CF", "100Base-Ethernet", "V", "1.0"
Thanks! You guys are doing a FANTASTIC job of pdaXrom!!
after writing files to my SD card, i plugged it in the desktop, and NADA: file is not there. returned the SD to the zaurus, and the file IS there.
it's probably a "sync/cache" issue.
the workaround is to run "sync" before i take out the card from the Z.
Do that for each loop device listed in the ps output. The umount command is actually supposed to do this for you when you unmount a loopbacked filesystem but for some reason the pdaXrom version doesn't.
no, i'm too lazy to umount it.
usually i just wait 3-5 seconds after file op is finished, and i eject the card.
I wouldn't call it a bug if you're doing something no one would ever recommend. pdaXrom has synchronous I/O disabled in the kernel (CONFIG_FS_SYNC), do you know if Cacko 1.21b does as well? If not then that would explain why you're able to remove the card after such a short time without doing a manual sync.
Which talks about same error ... is this MY problem or is it some kind of incompatibility / inconsistency between Kernel and compiled samba version AND orinocco cards ?
I have a GlobalSat BC-307 Compact Flash GPS receiver that doesn't work 'out of the box'.
I think the socketcom firmware in the spectrum24 driver is old.. my locally compiled driver works ok (under my own kernel), but the one with 1.1.0-rc8 seems to overdrive the antenna or something. Oddly, cupping my hand over the antenna seems to improve the signal quality. Quite strange.
Anyway, I attached my spectrum_fw.h generated from the latest firmware on Socket's web site. Can you check if it differs, and if so, recompile the driver against rc8's kernel? Alternatively, could you post your kernel source?
Also, in case my patch was corrupted by the description field on bug ID 245, here's a binary.
I know it listed as fixed for RC8, but it isn't working for me. That is revision B of Socket 6004 card.
card "Socket Communications CF+ LP WLAN Card Rev B"
eth0: failed to read MAC address!
Any and all help would be more than welcome and very much appreciated!!!
6004 B is not a prism2.5 card, there's no way you will get spectrum_cs work with it.
It's based on Agere HERMES II design. Someone added their drivers to OE, so you could try to build and run these.
anyone brings Pocketop keyboard works in X11 ROM?
product info: "wlan", "11Mbps_PC_Card_3.0", "ISL37100P", "Eval-RevA"
It would be great to get this card running with the HostAP drivers, preferably!
My linksys PKW-WCF12 has a problem, I have no issues connecting to a 802.11b base station, but as soon as I try to connect to a 802.11g station the card refuses to connect (even at .b speeds), other cards in laptops and the like have no problems at all.
Am I using the correct drivers? does anyone else have this problem?? Any quick fixes??
cardmgr: + SET failed on device eth0 ; Operation not supported.
cardmgr: + SET failed on device eth0 ; Invalid argument.
product info: "Linksys", "Wireless CompactFlash Card", "", ""
You could try changing drivers from orinoco to hostap. I also have a Linksys WCF12 and have noticed my card behaves much better under hostap. See this post for instructions on changing drivers.
I would like to use my Belkin-BT-Card F8T020, which works great with cacko-ROM.
With pdaxrom it is't recognized.
product info: "CF CARD", "GENERIC", "", ""
Would be nice to have it with pdaxrom too.
The other is with the USB data cable, when I set the USB settings so it will let my comp access the SD slot I keep getting my comp telling me that even when I have a card in the SD slot it says "There is no disk in the drive" The Zaurus shows up in My Computer as a new removable drive but it just will not work. It has never worked since the feature was added. Do I need to install some special driver for my Zaurus on to my comp which runs XP Pro SP 2 instead of it using the generic driver that XP installs the second you connect the Z for the first time?
One more thing that probably isn't related to the OS but... then I install the WiFi scanner from the IPK feed it doesn't give me an icon anywhere to let me use the program and I have no idea where it is installed, I have that prob with a few of the programs that I install.
One last thing... The PPP thing for accessing the internet only lets me dial a phone number, it there not a way I can get my Z to connect to my phone and connect to the internet via GPRS so that I don't have to pay for the duration that I am online, just pay for the amount of data transferred.
I hope this is the right thread to post in, but I think this is some nice info on getting support for the only 802.11g network card currently on the market (this is nice so hotspots won't get slower because a 802.11b card connects or on hotspots which are 802.11g (+WPA or WEP) exclusively).
(Pick the 7.22 version drivers, does not support older chips anymore but it reportedly supports this chip).
works on x86, so far only a report of crashes on Xscale (Zaurus Cacko).
Driver download extras: HCF directory contains firmware images to allow the card to operate in either station (STA) or Access Point (AP) mode.
Check also the following threads (I tried to make a summary of the info in this post).
There is a popular wireless CF card which isn't supported by pdaXrom, at least, I thought it was very popular and therefore I bought it.
This card is recognized either as "anonymus memory" or as Sandisk connect SDWCFB-000".
PRODID_2 = "SMC2642W 11Mbps Wireless CF Card"
Product info: " ", "SMC2642W 11Mbps Wireless CF Card", ""
Other ROMS support this card according what I read in these forums. Would you add support to this card?. I tried all kind of configurations in the /etc/pcmcia files, but now I'm clueless.
Maybe publish a list of usb Bluetooth dongles? I have one that doesn't work, but it might be easier just to find ones that do.
USB GPS?? I don't have one atm, but I haven't seen reports of their use (could be me).
USB cameras via V4L support in the kernel?
hi all.... just running pdaxrom after playing around with the sharp rom and openzaurus opie and gpe distros for a while.... i can't believe how sweet pdaXrom is! exactly what i want!
anyway, back on topic... i have the ambicom wl1100c-cf wireless card... it works very sporadically in pdaXrom, although always worked perfectly in the others... what am i missing? it has worked for me a couple times, but even then droped and reconnected quite a bit. Other times, i can't even get it to connect to my network.
I've read a bunch of the discussion on using hostap drivers, but i'm confused... i don't have ANY wireless drivers in lsmod (at least when it's not working), and only a couple even installed in the modules directory, so i'm assuming most are built in. also, my card shows up as eth0 not wlan0.
card "SonicWALL Long Range Wireless Card"
version "SonicWALL", "Long Range Wireless Card", "ISL37100P", "1.0"
card "Senao NL-2011CD PLUS Ext2 Mercury"
version "WLAN", "11Mbps_PC-Card_3.0", "ISL37100P", "Eval-RevA"
card "Senao/Origo 80211b WLAN Card"
It's prism2 based card - use hostap_cs or orinoco_cs for it. It was released by many manufacturers and IIRC it is based on Intersil reference card.
card "AmbiCom BT2000C Bluetooth PC/CF Card"
version "AmbiCom BT2000C", "Bluetooth PC/CF Card"
thats how it is setup in OZ - I dont know does it works or not.
apmsleep does not seem to work correctly on the 6000. It suspends but does not resume. Cant seem to right click (even after reading other threads). Windows still open like they are on a clamshell (have not looked for a fix).
Wireless works like rc10, it *seems* faster to me, even firefox seems to open faster. All in all a fairly large step in stability and speed. If apmsleep worked and I could script up alarms, pdaxrom would be 100% usable for me.
wlan-ng ipk in feed of rc11 (http://212.10.30.205/rc11/Zaurus-C1000-C3100/feed/wlan-ng_0.2.1-pre26-1_armv5tel.ipk) does not seem to contain prism2_cs.o.
I am going to use PLANEX GW-CF11X on C1000 and rc11. How can I use this card on rc11?
yossie: with hostap maybe? Atleast this is what I will try for prism2 cards.
Anyhow, I'm using rc12 with a C1000 and while a USB mouse works fine trying to use a USB keyboard is a no-go. Switching USB function to "serial" causes the built-in keyboard to stop working (touch screen works fine) and no keypresses from the USB keyboard are registered. Unplugging the keyboard and switching the USB function back to "storage" freezes up the system.
I've tried both a Fellowes "stowaway keyboard" as well as a standard mac usb keyboard.
how do you use the usb mouse? i just plugged it in but nothing happens... dmesg says something about usb device not activated.
I just plugged it in and dmesg picks it up properly. After that I open up the "USB Function" app and switch to "serial" mode and it just works. I don't know if it matters but this is with a Kensington Orbit two button trackball.
I'm also using a C1000 so perhaps this is C3100 specific. Did you upgrade from rc11 or was this a freshly flashed rc12?
was a fresh rc12. there shouldnt be any difference between the c3100 and the c1000... if you look rc12 is the same rom for both devices.
do you have /proc/bus/usb ? i saw that some usb functions need it (lsusb needs it... and also usbh!). but i dont have it.
i also plugged in a card reader... but nothing happens.
udc_connect: usb-device is not active.


Another job in the Montreal region: Morris Mohawk Gaming Group offers online gaming services to users in North America.
They are looking for a Web Analytics Specialist. The ideal candidate will be someone smart, enthusiastic, and technical, with a passion for data and the know-how to drive web optimization success. The candidate will be equally comfortable drawing business conclusions and presenting to key stakeholders, as they are analyzing web data and dealing with IT partners.


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Home » Trump withdraws U.S. from Paris Climate Agreement
Environmental Health and SafetyGlobalToday's News
Trump withdraws U.S. from Paris Climate Agreement
KEYWORDS climate change / regulation
President Donald Trump has announced that he is withdrawing the United States from the Paris Climate Accord, a globally agreed upon coalition aimed at reducing emissions that cause climate change. Trump called climate change a "hoax" during his presidential campaign.
The White House said the agreement, which went into effect in November 2016, doesn't sufficiently benefit the American people and had been "negotiated poorly."
The accord sets as a specific goal keeping the Earth from warming by more than 3.6 degrees Fahrenheit.
Obama: U.S. rejecting the future
The move is the latest in a series of actions taken by Trump to reverse former President Obama's steps toward reducing climate change, which include targeting the Clean Power Plan and its reduction in the amount of carbon pollution that power plants in the U.S. can legally emit.
Obama said that with the withdrawal, the U.S. "joins a small handful of nations that reject the future." He called on states and cities to enact policies to limit emissions. Syria and Nicaragua are the only two countries – now joined by the U.S. – that do not take part in the accord.
The world leaders Trump met with during his first international trip as president last week urged him to remain in the accord, as did environmental groups, Democratic lawmakers and a number of business leaders.
Clean energy companies could suffer
Environmental Entrepreneurs, a nonpartisan group of business leaders, investors, and professionals, warned that withdrawing from the agreement will:
Cede clean energy opportunities to China, Germany and other countries, hurting U.S. companies and 3 million Americans who work in solar, wind, energy efficiency and other sectors;
Exclude U.S. companies from an estimated $19 trillion in global clean energy opportunities; and
Result in possible carbon tariffs on U.S. goods, a major blow to U.S. companies that do business overseas.
While the U.S. can't technically withdraw from the agreement until November 2019, it can nullify legislation linked it.
NRDC: Heat deaths will rise sharply without U.S. in Paris Accord
Public health experts cheer climate change agreement

redpajama_set_name: RedPajamaCommonCrawl


text:
Goetze's Donates Treats to Kennedy Krieger Institute for Annual Halloween Festivities
Goetze's Candy Company donates Caramel Creams and Cow Tales Minis to Kennedy Krieger
Institute for trick-or-treating.
BALTIMORE, MD (October 31, 2019) — Goetze's Candy Company, a Maryland-based manufacturer of caramel products including Cow Tales® and Caramel Creams®, celebrated Halloween by donating sweet treats to the Kennedy Krieger Institute for its employee costume contest. Held annually, the contest serves as an interactive way for patients, their families and staff to get into the spirit of Halloween.
Goetze's Donates School Supplies to Support Baltimore Students in Need
Goetze's set up stations at Back to School Night where parents and students were invited to pick up the tools they needed to kick off a successful school year.
BALTIMORE, MD (October 10, 2019) — Goetze's Candy Company, donated more than $3,200 in new school supplies to students at Holabird Academy, a Baltimore City public school serving more than 500 students in grades pre-K through eighth grade.
Goetze's Candy Co. Partners with Monument City Brewing to create 'Bulls-Eye Beer' and Host a Charity Coat Drive benefiting MCVET
Pictured left to right: Mitchell Goetze, Cereta Spencer, Meghan Brody, and Jeffery Kendrick.
A portion of the Bulls-Eye beer proceeds are donated to MCVET and Goetze's Candy Company matched the donation with a second check.
BALTIMORE, MD (October 26, 2018) — Goetze's Candy Company partnered with Monument City Brewing to create the limited edition 'Bulls-Eye' beer. The idea began when Rob Goss of Whitey's Liquors was eating a handful of Goetze's Caramel Creams® candy, and decided to text Kennith Praay, co-founder of Monument City Brewing, to throw out the idea of brewing a beer using the iconic candies.
Team Give & Goetze Kicks off the 2016 Race Season
Team Give & Goetze right before running the Under Armour Kelly St. Patrick's Day Shamrock 5k.
BALTIMORE, MD (March 18, 2016) — Team Give & Goetze kicked off the 2016 race season at the Under Armour Kelly St. Patrick's Day Shamrock 5k on Sunday March 13th, 2016. There were 13 runners who grabbed their green and joined team Give & Goetze to complete a 5k run through the streets of downtown Baltimore City. Team Give & Goetze completed 40.3 miles, raising over $200 for the Barth Syndrome Foundation.
Goetze's Candy at Kennedy Krieger Institute's Festival of Trees
Christmas tree donated by Goetze's Candy Company to the Festival of Trees.
BALTIMORE, MD (November 2, 2015) — Be sure to join Goetze's Candy Company on Friday, November 27 through Sunday, November 29 for the Kennedy Krieger Institute's Festival of Trees!
Running for a Cause: 2015 Team Give & Goetze
The Team members of Give and Goetze run in the 2015 Baltimore Running Festival.
BALTIMORE, MD (October 23, 2015) — Goetze's Candy Company's Team Give and Goetze 2015 charity race season wraps up with feet on the ground at the 2015 Baltimore Running Festival. Despite the chilly temperature, wind, and lost buses, Team Give & Goetze ran a total of 134.1 miles, raising $670.50 for the Barth Syndrome Foundation.
Team Give & Goetze Kicks Off the First Race of 2015
Team Give & Goetze after running in the Kelly St. Patrick Day Shamrock 5k.
BALTIMORE, MD (March 1, 2015) — Team Give & Goetze kicked off the first race of the season running in the Kelly St. Patrick's Day Shamrock 5k on Sunday March 16th, 2015. A total of 18 runners participated in the event and ran a total of 55.8 miles and donated $279 to Kennedy Kreiger.
Give & Goetze Participates in Run Wild for Autism
Team Give & Goetze just before running the Run Wild for Autism 5k at the Maryland Zoo.
BALTIMORE, MD (September 28, 2014) — Team Give & Goetze participated in the Run Wild for Autism 5k Baltimore at the Maryland Zoo. In their fifth event of 2014, Team Give & Goetze ran a total of 44 miles and donated $217 to the Pathfinders for Autism.
Give & Goetze Runs To Remember
Team Give & Goetze just after running in the Run To Remember 5k in downtown Baltimore.
BALTIMORE, MD (September 14, 2014) — Team Give & Goetze participated in the Run To Remember 5k in Baltimore, MD. In their fourth event of 2014, Team Give & Goetze ran a total of 31 miles and donated $155 towards the Baltimore Community Foundation, which supports the Baltimore Police Foundation and Baltimore Fire Department. For more information about the Baltimore Community Foundation, visit www.bcf.org.
Goetze's Candy Donates to Autism Research
Team Give & Goetze just before running in the Roar for Autism 5k.
BALTIMORE, MD (April 17, 2014) — Team Give & Goetze participated in the Roar for Autism 5k at Oregon Ridge Park in Cockeysville, MD. In their second event of 2014, Team Give & Goetze ran a total of 34.1 miles and donated $170 for autism research to Kennedy Krieger Institute. For more information about the ROAR for Autism program, visit www.ROARforAutism.org.


text:
Apple has released an update for Final Cut Pro X, Motion and Compressor
Apple has updated line of corporate software Final Cut Pro X, Motion and Compressor, adding new features for animation design and significantly faster processing, compression and video transmission. Download the new version can be free through the system updates OS X.
In Final Cut Pro 10.2 appeared easy to use 3D-titles, improved masks for color correction and effects, as well as built-in support for new camera formats and processing processes RED RAW with graphics acceleration. Motion 5.2 further extends the functionality of 3D-titles with the ability to create their own materials and graphical environment with instant publication in Final Cut Pro X. Compressor 4.2 allows you to compress the film, preparing it for sale in the iTunes Store.
"Final Cut Pro X changes the existing approach to video editing - for filmmakers of Hollywood blockbusters, and for those who create their first films - said Phil Schiller, senior vice president of product marketing for Apple. - Updated Final Cut Pro X, Motion and Compressor provide an opportunity to edit video, add titles and compress files with greater ease, be it short videos or feature films".
Final Cut Pro 10.2 allows filmmakers to create 3D-editing titles by simply dragging and offers as templates for beginners and film-quality templates with built-in background and animation effects. Users can choose any style of text and customize the appearance of titles from hundreds of available combinations of structures, lighting and borders, and instantly convert titles in three-dimensional flat, watching the changes in real time. In addition, Final Cut Pro 10.2 includes support for still more video formats, including Panasonic AVC-Ultra and Sony XAVC-S, and the processing of files in RED RAW format is faster because of the opportunities Mac Pro.
Professional installation directors and graphic designers can take advantage of Motion 5.2, which offers even more opportunities to create 3D-titles. Now the application allows you to create dynamic titles with different types of lighting and shooting angles, as well as multi-scene with 3D-titles, realistic shadows and reflections on other objects.
Appendix Compressor 4.2, in turn, allows you to prepare the film for sale in iTunes Store. Simply select a movie trailer, closed captioning, and much more, and Compressor will create a complete package for the iTunes Store, which users can directly send the partner. In Compressor also been improved such key tasks as encoding, including fast rendering using the GPU function used when Send to Compressor and multi-pass encoding H.264 hardware acceleration on compatible systems.
Download Final Cut Pro X cost $ 299.99, you can follow this link , Motion and Compressor cost $ 49.99 - respectively here and here .


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Here are other ways you can help contribute to progress in advancing our knowledge for cancer treatments.
The Alberta Cancer Foundation is the largest philanthropic investor in cancer research in Alberta. Click on the links below to find out more about how you can contribute to clinical trials in our province.
Together, we can make a difference by investing in clinical trials. Without the Alberta Cancer Foundation's support, clinical trials would not take place. ACCT invites you to donate to cancer research and discovery.


text:
Tag: Industrial Designer
Defies Description, Furnishings, Furniture, Industrial Design July 15, 2018 July 15, 2018
Self-taught designer and early plastics pioneer, Neal Small (b. 1937) was known as the "Prince of Plastics" in his Chelsea neighbor where he opened up shop in the 1960s.
Before he left plastic industrial design to concentrate on a quiet life in the woods of Maine, Small created a number of innovative and iconic designs, including the "Origami" magazine holder and the Model 5031 acrylic coffee table. The 5031 coffee table, crafted from a single sheet of acrylic, was lauded as one of the purest modern forms of the time. Small still resides in Maine, and if you're lucky, you may catch a glimpse of him driving around town in his black Subaru…that just happens to be adorned with black rats. Plastic ones, of course.
Filed under: 70s, Industrial Design, Industrial Designer, Mid Century Modern, mod, Neal Small, Plastic, Pop Art
Finnish industrial designer, Tapio Wirkkala (1915-1985), was a master in the many mediums he used for his designs in glassware, tableware, cutlery, jewelry, art glass, furniture and more.
An artist and sculptor at heart, Wirkkala's work took a necessary, practical approach after the war and turned to industrial design. A recluse that preferred the isolation of the woodlands of Lapland, Wirkkala's main inspiration was nature and the frozen landscape of his homeland. He translated that love of home into some of his most well-known designs such as the iconic Ultima Thule (Ultima Thule is a mythological distant place located beyond the "borders of the known world") and Aslak (a Finnish boy's name meaning "supporter of Thorgest," a 9th century Viking chief) glassware for Iittala.
Wirkkala also created an extensive collection of porcelain and stoneware for Rosenthal Ag starting in 1956, a career which produced eight tableware services and over 200 porcelain decorative objects, and colorful, blown glass for Venini.
And while Wirkkala is known for some of the most beautiful, modernist housewares of the mid-century, he's also known for many utilitarian masterpieces. A plastic ketchup bottle (Paulig Company), an incandescent light bulb (Airam), the Finnish markka banknotes (1955-1981), and the Finlandia "Frozen Ice" vodka bottle (1970-2000).
A modest man, Wirkkala was "a maestro without a maestro's affections."
Row 1: "Avena" vase for Iitala, 1970; "Alpina" vase for Iitala, 1966; "Ultima Thule" glass for Iitala, 1968; "Kalvolan Kanto" vase for Iittala, 1948; Row 2: Model 9020 coffee table for Akso, est. 1958; silver pendant, 1957 (photo credit: Wright 20).
Filed under: Finland, Furniture Designer, Iittala, Industrial Designer, Mid Century Modern, Modernism, Modernist, Rosenthal Ag, Tapio Wirkkala
Architecture, Defies Description, Furnishings, Furniture, Industrial Design July 8, 2018 July 8, 2018
"… arguably the single greatest omission of design history." –Nina Stritzler-Levine
Aino Marsio-Aalto
Marsio (b. 1894) was a Finnish architect and industrial designer, and the first wife of Alvar Aalto. In 1920, Marsio earned a degree in architecture at Helsingin Suomalainen Tyttökoulu (Helsinki University of Technology), and four years later took an assistant's position with a young architect by the name of Alvar Aalto. In 1925, Marsio and Aalto married and would begin a collaboration that would influence the design world for many decades to come. In 1935, the Aaltos, along with Maire Gullichsen and Nils-Gustav Hahlin, co-founded Artek Oy, a Finnish design firm with a storefront in a busy shopping district in Helsinki. There, the Aalto's introduced their Functionalist masterpieces to Finland. In 1936, Aino and Alvar collaborated on a vase that was inspired by the dress of indigenous Lapland women, which was coined the "Savoy Vase" after it was displayed at Restaurant Savoy, a tony restaurant in Helsinki designed by the Aalto's firm. The Savoy vase design won a competition by Karhula/Iittala and was subsequently shown at the 1937 World's Fair in Paris. That accolade, however, went to Alvar alone. And again, in 1939, Alvar won 1st prize for Aino's Finnish pavilion design at the New York World's Fair. But one of Aino's must enduring contributions may be her simple, but iconic Functionalist pressed glassware for Iittala. Designed in 1932, it was inspired by the ripples that form on the surface when a stone is thrown into the water. While Aino Aalto's contributions to the Artek legacy may never be fully know, her talents are unmistakable and the ripple effect created by her known classic designs has lasted for nearly a century. Aino Marsio-Aalto died in Helsinki in 1949.
Far left: Floor lamp, 1930s. (Photo: Artnet)
Middle, row 1: Glassware for Iittala, 1932 (Photo: Bukowskis); Savoy Vase, 1936, for Iitalla; Lapland woman (Photo: public domain)
Middle, row 2: Table, 1932 (Photo: Artnet); 606 Side Table for Artek, 1932 (Photo: Jacksons); Floor lamp model called "floor-reflector" from 1937-38 with rare aluminum shade (Photo Jacksons).
Far right: Finnish Pavillion, 1936 New York World's Fair (Photo: Ezra Stoller)
Filed under: Aalto, Aino Aalto, Architect, Artek, Finland, Functionalism, Furniture Designer, Iittala, Industrial Designer, MCM, Mid Century Modern, Modernism, Savoy Vase
Defies Description, Furnishings, Furniture, Industrial Design July 4, 2018 July 9, 2018
"Less, but better." — Dieter Rams
Dieter Rams (b. 1932) is a functionalist German industrial designer known for his work with Braun and Vitsoe.
In 1947, having recognized Dieter's talent his father enrolled his 15-year-old son in Wiesbaden School of Art to study architecture and interior design. After two years, Rams left the school to take a three-year carpentry apprenticeship after which he returned to the school and completed his degree with honors in 1953.
During his absence, the school took a decided turn toward modernism. It was then that Rams was introduced to German modernism and the Ulm School of Design. After graduating, he worked with Otto Apel's architecture firm and was further exposed to modernism through the firm's association with modernist colleagues in America. These brushes with modernism would prove fateful two years later when Rams accepted an in-house architect and interior design position with Braun to design new office space for the company.
Rams went to work planning a new space that included a wall-mounted shelving system. With this design, his collaboration with Vitsoe was born. With the approval of Edwin Braun, Rams took the idea to Vitsoe. One year later, the Vitsoe 606 Universal Shelving System was launched.
In the early 1960s, Rams used his architecture background and began work on a planned community in Kronberg for Braun employees. "Roter Hang" is a community of grouped and terraced bungalows that line a sloped hillside. There can be found his only fully-realized architectural design;his L-shaped dopplebungalow. Although Braun delayed the project, it was eventually completed by Rudolf Kramer in 1974. The community, as well as Dieter Rams's personal home, which is a testament to his personal credo of "less for more," due to its modest footprint and sparse decoration, have been granted protected status and designated a cultural monument.
Rams is known for his "10 Principles of Good Design," one of which is "environmentally friendly." In a 1976 speech, Rams said, "there is an increasing and irreversible shortage of natural resources." He has long believed we must "move away from the throwaway habit" and "[that] it will be less important to have many things and more important to exercise care about where and how we live." Dieter Rams products fully embody his 10th principle – simplicity and purity.
Dieter Rams retired from Braun in 1995, but continues to work for Vitsoe. He and his wife still live in the Roter Hang bungalow in Kronberg.
"Question everything generally thought to be obvious."
― Dieter Rams
Row 1 (left to right): Braun RT 20 Radio, 1961 (Photo: Core77); Vitsoe 620 Chair, 1962 (Photo Artnet); Dieter Rams and his Frankfurt home;
Row 2 (left to right): Control panel on the Braun T580 Transistor Radio, 1961 (Photo: MoMA); Vitsoe 606 Shelving System, 1960; Vitsoe 601 Chair;
Row 3 (left to right): "Roter Hang" dopplebungalow settlement for Braun employees; Street view of Roter Hang" dopplebungalow settlement for Braun employees; Dieter Rams
Filed under: Braun, Dieter Rams, Functionalism, Furniture, Furniture Designer, Germany, Industrial Design, Industrial Designer, MCM, Mid Century Modern, Vitsoe


text:
\section{Introduction and Related Work}
\begin{comment}
Recent work in supervised learning for computer vision~\citep{krizhevsky_imagenet, inception, resnet} has allowed increasingly complex features to be extracted directly from pixel data. This has led to the appearance of a new set of reinforcement learning algorithms, namely deep reinforcement learning algorithms, that are able to learn directly from raw image data~\citep{atari_rl_2013, vizdoom_fb} and in some domains even surpass human performance~\citep{mnih2015nature, a3c, go}.
\end{comment}
\begin{comment}
Recent work in deep supervised learning for computer vision~\citep{krizhevsky_imagenet,
inception, resnet} has enabled reinforcement learning algorithms to better approximate
large state spaces~\citep{atari_rl_2013, vizdoom_fb}, and even surpass human performance
in some problem domains~\citep{mnih2015nature, a3c, go}.

The standard supervised learning paradigm, including when employed for deep learning, assumes training examples to be independent and identically distributed (i.i.d.). In addition, supervised learning algorithms are assumed independent of the process used for collecting the examples. The reinforcement learning paradigm violates these assumptions. The policy being learnt affects the distribution of encountered states, which in turn affects the policy. Thus, a direct application of supervised learning approaches within reinforcement learning presents some challenges.
\end{comment}

Incorporating deep learning models within reinforcement learning (RL) presents some challenges. Standard stochastic gradient descent algorithms for training deep learning models assume all training examples to be
independent and identically distributed (i.i.d.). This constraint is often violated by RL agents, given the high
correlation between encountered states. Additionally, when learning on-policy, the policy affects the distribution of encountered states, which in turn affects the policy, creating a feedback loop that may lead to divergence~\citep{atari_rl_2013}. Two main attempts have been made to solve these issues. One is to store experiences in a large replay memory and employ off-policy RL methods~\citep{atari_rl_2013}. Sampling the replay memory can break
the state correlations, thus reducing the effect of the feedback loop. Another is to execute multiple asynchronous agents in parallel, each interacting with an instance of the environment independently of each other~\citep{a3c}. Both of these approaches suffer from different drawbacks; experience replay can only be employed with off-policy methods, while asynchronous agents can perform inconsistent parameter updates due to stale gradients\footnote{Gradients may be computed w.r.t. stale parameters while updates applied to a new parameter set.} and simultaneous parameter updates from different threads.

\begin{comment}
Training time has been a limiting factor in this type of deep reinforcement learning. \citet{mnih2015nature} train for 8 days on a GPU for each environment, \citet{gorilla} are able to reduce training time to 4 days by distributing training across 100 machines utilizing only CPUs. \citet{a3c} are able to reduce training time to 4 days on a single machine utilizing only CPUs by running asynchronous actors in parallel.\\
\end{comment}

Parallel and distributed compute architectures have motivated innovative modifications
to existing RL algorithms to efficiently make use of parallel execution.
In the General Reinforcement Learning Architecture (Gorila)~\citep{gorilla}, the DQN~\citep{mnih2015nature} algorithm is distributed across multiple machines.
Multiple \textit{learners} learn off-policy using experiences collected into a common replay memory by multiple \textit{actors}. Gorila is shown to outperform standard DQN in a variety of Atari games, while only training for 4 days. The distribution of the learning process is further explored in~\citep{a3c}, where multiple actor-learners are executed asynchronously on a single machine. Each actor-learner holds its own copy of the policy/value function and interacts with its own instance of the environment. This allows for both off-policy, as well as on-policy learning.  The actor-learners compute gradients in parallel and update shared parameters asynchronously in a \textsc{Hogwild!}~\citep{hogwild} fashion. The authors suggest that multiple agents collecting independent
experiences from their own environment instances reduces correlation between samples,
thereby improving learning. The asynchronous advantage actor-critic (A3C) algorithm~\citep{a3c} was able to
surpass the state of the art on the Atari domain at the time of publication,
while training for 4 days on a single machine with 16 CPU cores. GA3C~\citep{nvidia} is a GPU implementation of A3C. It batches action selection and learning using queues. Actors sample from a shared policy by submitting a task to a \textit{predictor}, which executes the policy and returns an action once it has accumulated enough tasks. Similarly, learning is performed by submitting experiences to a \textit{trainer}, which computes gradients and applies updates once enough experiences have been gathered. If the training queue is not empty when the model is updated, the learning will no longer be on-policy, since the remaining experiences were generated by an old policy. This leads to instabilities during training, which the authors address with a slight modification to the weight updates.

We propose a novel framework for efficient parallelization of deep reinforcement learning algorithms, which keeps the strengths of the aforementioned approaches, while alleviating their weaknesses. Algorithms based on this framework can learn from hundreds of actors in parallel, similar to Gorila, while running on a single machine like A3C and GA3C.  Having multiple actors help decorrelate encountered states and attenuate feedback loops, while allowing us to leverage the parallel architecture of modern CPUs and GPUs. Unlike A3C and Gorila, there is only one copy of the parameters, hence parameter updates are performed synchronously, thus avoiding the possible drawbacks related to asynchronous updates. Our framework has many similarities to GA3C. However, the absence of queues allows for a much more simpler and computationally efficient solution, while allowing for true on-policy learning and faster convergence to optimal policies. We demonstrate our framework with a Parallel Advantage Actor-Critic algorithm, that achieves state of the art performance in the Atari 2600 domain after only a few hours of training. This opens the door for much faster experimentation.

\section{Background}
Reinforcement learning algorithms attempt to learn a policy $\pi$ that maps states to actions, in order to maximize the expected sum of cumulative rewards $R_t = \mathbb{E}_{\pi}\big[\sum_{k=0}^{\infty}\gamma^kr_{t+k}\big]$ for some discount factor $0 < \gamma < 1$, where $r_t$ is the reward observed at timestep $t$. Current reinforcement learning algorithms represent the learned policy $\pi$ as a neural network, either implicitly with a value function or explicitly as a policy function.

\subsection{Batching with Stochastic Gradient Descent}
Current reinforcement learning algorithms make heavy use of deep neural networks, both to extract high level features from the observations it receives, and as function approximators to represent its policy or value functions. \\
Consider the set of input-target pairs $S=\{(x_0,y_0),(x_1, y_1),...(x_n,y_n)\}$ generated by some function $f^*(x)$. The goal of supervised learning with neural networks is to learn a parametrized function $f(x;\theta)$ that best approximates function $f*$. The performance of $f$ is evaluated with the empirical loss
\begin{equation}
L(\theta) = \frac{1}{|S|}\sum\limits_{s\in S}l(f(x_s;\theta), y_s)
\end{equation}
where $l(f(x_s;\theta), y_s)$ is referred to as a loss function, and gives a quantitative measure of how good $f$ is at modelling $f^*$. The model parameters $\theta$ are learned with stochastic gradient descent (SGD) by iteratively applying the update
$$
\theta_{i+1} \gets \theta_i - \alpha\nabla_{\theta_i}L(\theta_i)
$$

for a learning rate $\alpha$. In SGD, $L(\theta)$ is usually approximated with
$$\bar{L}(\theta)=\frac{1}{|S'|}\sum_{s'\in S'}l(f(x_{s'};\theta), y_{s'}),$$
where
$S'\subset S$ is a mini-batch sampled from $S$. The choice of $\alpha$ and $n_{S'}=|S'|$ presents a trade-off between computational efficiency and sample efficiency. Increasing $n_{S'}$ by a factor of $k$ increases the time needed to calculate $\nabla_{\theta}\bar{L}$ by a factor of $k'$, for $k' \leq k$, and reduces its variance proportionally to $\frac{1}{k}$~\citep{optimization_for_large_scale}. In order to mitigate the increased time per parameter update we can increase the learning rate to $\alpha'$ for some $\alpha' \geq \alpha$. However there are some limits on the size of the learning rate, so that in general $\alpha' \leq k\alpha$~\citep{optimization_for_large_scale}. The hyper-parameters $\alpha'$ and $k$ are chosen to simultaneously maximize $\frac{k}{k'}$ and minimize $L$.

\subsection{Model-free Value Based Methods}
Model-free value based methods attempt to model the Q-funciton $q(s_t, a_t)=\mathbb{E}_{\pi}\big[ \sum_{k=0}^{\infty}\gamma^kr_{t+k+1}\big| s=s_t, a=a_t \big]$ that gives the expected return achieved by being in state $s_t$ taking action $a_t$ and then following the policy $\pi$. A policy can be extracted from the Q-function with $\pi(s_t)=\arg\max_{a'}q(s_t,a')$. DQN~\citep{atari_rl_2013} learns a function $Q(s,a;\theta)\approx q(s,a)$ represented as a convolutional neural network with parameters $\theta$. Model parameters are updated based on model targets provided by the Bellman equation
\begin{equation}
q(s,a)=\mathbb{E}_{s'}\Big[r + \gamma \max_{a'}q(s',a')|s,a\Big]
\end{equation}
to create the loss function
\begin{equation}
\bar{L}(\theta_{i}) = (r_t + \gamma \max_{a'}Q(s_{t+1},a';\theta_i) - Q(s_t, a_t;\theta_i))^2
\end{equation}

The parameters $\theta$ are improved by SGD with the gradient

\begin{equation}
\label{eq:dqntarget}
\nabla_{\theta_i}L(\theta_i)\approx\nabla_{\theta_i}\bar{L}(\theta_{i})=-\frac{1}{2}\big( r + \gamma \max_{a'}Q(s',a';\theta_{i})-Q(s,a;\theta_i) \big) \nabla_{\theta_i}Q(s,a;\theta_i)
\end{equation}

\begin{comment}

In practice the full expectation above cannot be efficiently calculated, and is replaced by the sample estimate

\begin{equation}
\label{eq:dqntarget}
\nabla_{\theta_i}L(\theta_i)\doteq \big( r_{t+1} + \gamma \max_{a'}Q(s_{t+1},a';\theta_{i-1})-Q(s_t,a_t;\theta_i)) \big) \nabla_{\theta_i}Q(s_t,a_t;\theta_i)
\end{equation}

Estimates are generated by having an actor interact with an environment by following the policy $\pi(s_t)$ and observing the next state $s_{t+1}$ and reward $r_{t+1}$.

\end{comment}

\subsection{Policy Gradient Methods}
\label{subsed:policy_gradient_methods}
Policy gradient methods~\citep{policy_gradient} directly learn a parametrized policy $\pi(a|s;\theta)$. This is possible due to the policy gradient theorem~\citep{sutton1999policy}
\begin{equation}
\label{eq:policy_gradient_loss}
\nabla_{\theta}L(\theta)=\mathbb{E}_{s,a}\big[q(s,a) \nabla_{\theta}\log\pi(a|s;\theta) \big],
\end{equation}
which provides an unbiased estimate of the gradient of the return with respect to the policy parameters.
\citet{sutton1999policy} propose an improvement upon the basic policy gradient update by replacing the Q function with the advantage function $A_{\pi}(s,a)=(q(s,a) - v(s))$ where $v(s)$ is the value function given by $\mathbb{E}_{\pi}\big[ \sum_{k=0}^{\infty}\gamma^kr_{t+k+1}\big| s=s_t\big]$. When $\pi$ is continuously differentiable, $\theta$ can be optimized via gradient ascent following

\begin{equation}
\label{eq_policy_loss_exp}
\nabla_{\theta}L(\theta)=\mathbb{E}_{s,a}\big[ \big( q(s,a) - v(s) \big) \nabla_{\theta}\log\pi(a|s;\theta) \big]
\end{equation}

\citet{a3c} learn an estimate $V(s;\theta_v)\approx v(s)$ of the value function, with both $V(s;\theta_v)$ and $\pi(a|s;\theta)$ being represented as convolutional neural networks. Additionally, they estimate the Q-function with the n-step return estimate given by

\begin{equation}
Q^{(n)}(s_t,a_t;\theta,\theta_v) = r_{t+1}+...+\gamma^{n-1}r_{t+n-1} + \gamma^nV(s_{t+n};\theta_v)
\end{equation}

with $0 < n \leq t_{max}$ for some fixed $t_{max}$. The final gradient for the policy network is given by

\begin{equation}
\label{eq_policy_loss}
\nabla_{\theta}L(\theta)\approx\big( Q^{(n)}(s_t,a_t;\theta,\theta_v) - V(s_t;\theta_v) \big) \nabla_{\theta}\log\pi(a_t|s_t;\theta)
\end{equation}

The gradient for the value network $V$ is given by
\begin{equation}
\label{eq:value_loss}
\nabla_{\theta_v}L(\theta_v) \approx \nabla_{\theta_v}\Big[\big( Q^{(n)}(s_t,a_t;\theta,\theta_v) - V(s_t;\theta_v) \big)^2\Big]
\end{equation}

Samples are generated by having an actor interact with an environment by following the policy $\pi(s_t)$ and observing the next state $s_{t+1}$ and reward $r_{t+1}$.

\section{Parallel Framework for Deep Reinforcement Learning}
\label{parallel_framework}
We propose a general framework for deep reinforcement learning, where multiple actors can be trained synchronously on a single machine. A set of $n_e$ environment instances are maintained, where actions for all environment instances are generated from the policy. The architecture can be seen in Figure~\ref{fig:para_frameworl}.
\begin{figure}[htb]
  \centering
  \includegraphics[width=0.8\linewidth]{figures/paac}
  \caption{Architecture of the Parallel Framework for Deep RL}
  \label{fig:para_frameworl}
\end{figure}
The policy function can be represented implicitly, as in value based methods, or explicitly as in policy gradient methods. As suggested in \citet{a3c}, by having multiple environments instances in parallel it is likely that they will be exploring different locations of the state space at any given time, which reduces the correlation of encountered states and helps stabilize training. This approach can be motivated as an \textit{on-line} experience memory, where experiences are sampled from the distribution currently being observed from the environment, instead of sampling uniformly from previous experience.

At each timestep the master generates actions for all environment instances by sampling the current policy. Note, that the policy may be sampled differently for each environment. A set of $n_w$ workers then apply all the actions to the their respective environments in parallel, and store the observed experiences. The master then updates the policy with the observed experiences. This allows the evaluation and training of the policy to be batched, which can be efficiently parallelized, leading to significant speed improvements on modern compute architectures.

\section{Parallel Advantage Actor Critic}
\label{paac}
We used the proposed framework to implement a version of the n-step advantage actor-critic algorithm
proposed by \citet{a3c}. This algorithm maintains a policy $\pi(a_{t}|s_{t};\theta)$
and an estimate $V(s_{t};\theta_{v})$ of the value function, both
approximated by deep neural networks. The parameters $\theta$ of
the policy network (the actor) are optimized via gradient ascent following $$\nabla_{\theta}\log\pi(a_{t}|s_{t};\theta)A(s_{t},a_{t};\theta,\theta_{v})+\beta\nabla_{\theta}H(\pi(s_{e,t};\theta))$$
~\citep{sutton1999policy}, where $A(s_{t},a_{t};\theta,\theta_{v})=Q^{(n)}(s_{t},a_{t};\theta,\theta_{v})-V(s_{t};\theta_{v})$
is an estimate of the advantage function, $Q^{(n)}(s_{t},a_{t};\theta,\theta_{v})=\sum_{k=0}^{n-1}\gamma^{k}r_{t+k}+\gamma^{n}V(s_{t+n};\theta_{v})$, with $0<n\leq t_{max}$, is the \emph{n}-step return estimation and $H(\pi(s_{e,t};\theta))$ is the entropy of the policy $\pi$, which as suggested by \citet{a3c} is added to improve exploration by discouraging premature convergence to suboptimal deterministic policies. The
parameters $\theta_{v}$ of value network (the critic) are in turn
updated via gradient descent in the direction of
$$\nabla_{\theta_{v}}\Big[\big(Q^{(n)}(s_{t},a_{t};\theta,\theta_{v})-V(s_{t};\theta_{v})\big)^{2}\Big]$$

In the context of our framework, the above gradients are calculated
using mini batches of experiences. For each of the $n_{e}$ environments,
$t_{max}$ experiences are generated, resulting in batches of size
$n_{e}\cdotp t_{max}$. The gradients $\nabla_{\theta}^{\pi}$ for
the policy network and the gradients $\nabla_{\theta}^{V}$ for the
value function thus take the following form:

\begin{equation}
\nabla_{\theta}^{\pi}\approx\frac{1}{n_e\cdot t_{\max}}\sum_{e=1}^{n_e}\sum_{t=1}^{t_{\max}} \big( Q^{(t_{\max}-t+1)}(s_{e,t},a_{e,t};\theta,\theta_v) - V(s_{e,t};\theta_v) \big) \nabla_{\theta}\log\pi(a_{e,t}|s_{e,t};\theta)+\beta\nabla_{\theta}H(\pi(s_{e,t};\theta))
\end{equation}

\begin{equation}
\nabla_{\theta_{v}}^{V}\approx\nabla_{\theta_{v}}\frac{1}{n_{e}\cdot t_{max}}\sum_{e=1}^{n_{e}}\sum_{t=1}^{t_{\max}}\big(Q^{(t_{\max}-t+1)}(s_{e,t},a_{e,t};\theta,\theta_{v})-V(s_{e,t};\theta_{v})\big)^{2}
\end{equation}

Pseudocode for our parallel advantage actor-critic algorithm (PAAC)
is given in Algorithm~\ref{alg:paac}. As shown in the next section,
PAAC achieves state of the art performance on the Atari 2600 domain
in half of the time required by GA3C and in only one eigth of the time
required by A3C.
Note that, although we implement an actor-critic algorithm, this framework can be used to implement any other reinforcement learning algorithm.

\section{Experiments}
\label{headings}
We evaluated the performance of PAAC in 12 games from Atari 2600 using the Atari Learning Environment~\citep{ale}. The agent was developed in Python using TensorFlow~\citep{abadi2015tensorflow} and all performance experiments were run on a computer with a 4 core Intel i7-4790K processor and an Nvidia GTX 980 Ti GPU.
\subsection{Experimental setup}
\label{exp_setup}
To compare results with other algorithms for the Atari domain we follow the same pre-processing and training procedures as \citet{a3c}. Each action is repeated 4 times, and the per-pixel maximum value from the two latest frames is kept. The frame is then scaled down from $210\times 160$ pixels and 3 color channels to $84\times 84$ pixels and a single color channel for pixel intensity. Whenever an environment is restarted, the state is reset to the starting state and between 1 and 30 no-op actions are performed before giving control to the agent. The environment is restarted whenever the final state of the environment is reached.

\begin{algorithm}[H]
\small
\caption{Parallel advantage actor-critic}
\label{alg:paac}
\begin{algorithmic}[1]
\State Initialize timestep counter $N = 0$ and network weights $\theta$, $\theta_v$
\State Instantiate set $\vect{e}$ of $n_e$ environments
\Repeat
\For{$t=1$ to $t_{max}$}
\State Sample $\vect{a}_t$ from $\pi(\vect{a}_t|\vect{s}_t;\theta)$
\State Calculate $\vect{v}_t$ from $V(\vect{s}_t;\theta_v)$
\ParFor{$i=1$ to $n_e$}\;\label{alg:par_for_start}
\State Perform action $a_{t,i}$ in environment $e_i$
\State Observe new state $s_{t+1,i}$ and reward $r_{t+1,i}$
\EndParFor \;\label{alg:par_for_end}
\EndFor
\State $\vect{R}_{t_{\max}+1} =
    \left\{
    \begin{array}{l l}
      0  \quad & \text{for terminal } \vect{s}_t\\
      V(s_{t_{\max}+1};\theta) & \text{for non-terminal } \vect{s}_t
    \end{array} \right.$
\For {$t=t_{\max}$ down to $1$}
\State $\vect{R}_t = \vect{r}_t + \gamma \vect{R}_{t+1}$
\EndFor
\State $d\theta=\frac{1}{n_e\cdot t_{max}}\sum_{i=1}^{n_e}\sum_{t=1}^{t_{max}}(R_{t,i} - v_{t,i})\nabla_{\theta}\log\pi(a_{t,i}|s_{t,i};\theta) +\beta\nabla_{\theta}H(\pi(s_{e,t};\theta))$\;\label{alg:grad_start}
\State $d\theta_v=\frac{1}{n_e\cdot t_{max}}\sum_{i=1}^{n_e}\sum_{t=1}^{t_{max}}\nabla_{\theta_v} \left(R_{t,i} - V(s_{t,i};\theta_v)\right)^2$\;\label{alg:grad_end}
\State Update $\theta$ using $d\theta$ and $\theta_v$ using $d\theta_v$.
\State $N \gets N + n_e\cdot t_{\max}$
\Until $N \geq N_{max}$
\end{algorithmic}
\end{algorithm}

As in~\citep{a3c}, a single convolutional network with two separate
output layers was used to jointly model the policy and the value functions.
For the policy function, the output is a softmax with one node per
action, while for the value function a single linear output node is
used. Moreover, to compare the efficiency of PAAC for different model
sizes, we implemented two variants of the policy and value convolutional
network. The first variant, referred to as $\mathcal{\text{arch}_{\text{nips}}}$,
is the same architecture used by A3C~FF~\citep{a3c}, which is a
modified version of the architecture used in \citet{atari_rl_2013},
adapted to an actor-critic algorithm. The second variant, $\text{arch}_{\text{nature}}$,
is an adaptation of the architecture presented in \citet{mnih2015nature}.
The networks were trained with RMSProp. The hyperparameters used to
generate the results in Table~\ref{table:results} were $n_{w}=8$,
$n_{e}=32$, $t_{\max}=5$, $N_{\max}=1.15\times10^{8}$, $\gamma=0.99$,
$\alpha=0.0224$, $\epsilon=0.1$, $\beta=0.01$, and a discount factor
of $0.99$ for RMSProp. Additionally gradient clipping \citep{gradient_clipping} with a threshold of 40 was used.

\begin{comment}
All layers except the final share parameters. The first convolutional layer had 16 filters of size $8\times8\times4$ and a stride of 4, the second had 32 filters of size $4\times 4\times16$ with a stride of 2. The final shared layer was fully connected with 256 neurons. The policy network had additional linear output neuron for each valid action, and the value network had a single linear output neuron.
The second architecture, $\text{arch}_{\text{nature}}$, uses the architecture from \citet{mnih2015nature} with three convolutional layers. The first layer with 32 filters of size $8\times8\times4$, the second with 32 filters of size $4\times4\times32$, and the third layer with 64 filters of size $3\times3\times32$ with strides of 4, 2 and 1 respectively. The final layer was fully connected with 512 neurons. Finally similar to $\text{arch}_{\text{nips}}$ the policy network has an additional linear output neuron for each valid action, and the value network had a single linear output neuron. All non-output layers used a rectified linear unit~\citep{nair2010rectified} non-linearity.

Gradient calculations in Algorithm~\ref{alg:paac} lines \ref{alg:grad_start}-\ref{alg:grad_end} are done in a single pass by using a $(n_e\cdot~t_{max})\times84\times84\times4$ dimensional input tensor.
\end{comment}

\subsection{Results}
\label{eval}
The performance of PAAC with $\text{arch}_{\text{nips}}$ and $\text{arch}_{\text{nature}}$ was evaluated on twelve different Atari 2600 games, where agents were trained for 115 million skipped frames (460 million actual frames). The results and their comparison to Gorila~\citep{gorilla}, A3C~\citep{a3c} and GA3C~\citep{nvidia} are presented in Table~\ref{table:results}. After a few hours of training on a single computer, PAAC is able to outperform Gorila in 8 games, and A3C FF in 8 games. Of the 9 games used to test GA3C, PAAC matches its performance in 2 of them and surpasses it in the remaining 7.

\begin{table}[httb]
\centering
\scriptsize
\begin{tabular}{lcccccc}
\toprule
Game & Gorila & A3C FF & GA3C & PAAC $\text{arch}_{\text{nips}}$ & PAAC $\text{arch}_{\text{nature}}$\\
\cmidrule(lr){2-6}
Amidar & 1189.70 & 263.9 & 218 & 701.8 & 1348.3 \\
Centipede & 8432.30 & 3755.8 &  7386 & 5747.32 & 7368.1\\
Beam Rider & 3302.9 & 22707.9 & N/A & 4062.0 & 6844.0\\
Boxing & 94.9 & 59.8 & 92 & 99.6 & 99.8\\
Breakout & 402.2 & 681.9 & N/A & 470.1 & 565.3\\
Ms. Pacman & 3233.50 & 653.7 & 1978 & 2194.7 & 1976.0\\
Name This Game & 6182.16 & 10476.1& 5643 & 9743.7 & 14068.0\\
Pong & 18.3 & 5.6 & 18 & 20.6 & 20.9\\
Qbert & 10815.6 & 15148.8 & 14966.0 & 16561.7 & 17249.2\\
Seaquest & 13169.06 & 2355.4 & 1706 & 1754.0 & 1755.3 \\
Space Invaders & 1883.4 & 15730.5 & N/A & 1077.3 & 1427.8\\
Up n Down & 12561.58 & 74705.7 & 8623 & 88105.3 & 100523.3\\
\cmidrule(lr){1-6}
Training & 4d CPU cluster & 4d CPU & 1d GPU & 12h GPU & 15h GPU\\
\bottomrule
\end{tabular}
\caption{Scores are measured from the best per-
forming actor out of three, and averaged over 30
runs with upto 30 no-op actions start condition. Results for A3C FF use human start condition are therefore not directly comparable. Gorila scores taken from \citet{gorilla}, A3C FF scores taken from \citet{a3c} and GA3C scores take from \citet{nvidia}. Unavailable results are shown as N/A.}
\label{table:results}
\end{table}
\begin{figure}[ht]
	\mbox{\includegraphics[width=0.32\linewidth]{figures/efficiency}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/environment_interaction}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/model_interaction}}
    \caption{Time usage in the game of Pong for different $n_e$.}
    \label{fig:runtimes}
\end{figure}
To better understand the effect of the number of actors (and batch size) on the score, tests were run with $n_e \in \{16, 32, 64, 128, 256\}$. The learning rate was not tuned for each batch size, and was chosen to be $0.0007\cdot n_e$ for all runs across all games. Increasing $n_e$ decreases the frequency of parameter updates, given that parameter updates are performed every $n_e\cdot t_{\max}$ timesteps. As the theory suggests, the decreased frequency in parameter updates can be offset by increasing the learning rate. As can be seen in Figure~\ref{fig:score_comparison} most choices of $n_e$ result in similar scores at a given timestep, however Figure~\ref{fig:training_time} shows that higher values of $n_e$ reach those timesteps significantly faster. The choice of $n_e = 256$ results in divergence in three out of the four games, which shows that the learning rate can be increased proportional to the batch size, until a certain limit is reached.
\begin{figure}[htp]
    \mbox{\includegraphics[width=0.32\linewidth]{figures/beam_rider_timestep}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/boxing_timestep}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/breakout_timestep}}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/pong_timestep}}
    \hspace{2px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/qbert_timestep}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/space_invaders_timestep}}
    \caption{Score comparison for PAAC on six Atari 2600 games for different $n_e$, where one training epoch is equivalent to 1 million timesteps (4 million skipped frames).}
    \label{fig:score_comparison}
\end{figure}
\vspace{-15px}
\begin{figure}[ht]
    \mbox{\includegraphics[width=0.32\linewidth]{figures/beam_rider_time}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/boxing_time}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/breakout_time}}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/pong_time}}
    \hspace{2px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/qbert_time}}
    \hspace{1px}
    \mbox{\includegraphics[width=0.32\linewidth]{figures/space_invaders_time}}
    \caption{Training time and score comparison for PAAC on six Atari 2600 games for different $n_e$.}
    \label{fig:training_time}
\end{figure}
A limiting factor in the speed of training is the time spent in agent-environment interaction. When using $\text{arch}_{\text{nips}}$ for $n_e=32$ approximately 50\% of the time is spent interacting with the environment, while only 37\% is used for learning and action selection, as is shown in Figure~\ref{fig:runtimes}. This has strong implications for the models and environments that can be used. Using a model-environment combination that doubles the time needed for learning and action calculation would lead to a mere 37\% increase in training time. This can be seen in Figure~\ref{fig:runtimes} where using $\text{arch}_{\text{nature}}$ on the GPU leads to a drop in timesteps per second 22\% for $n_e=32$ when compared to $\text{arch}_{\text{nips}}$. When running on the CPU however this leads to a 41\% drop in timesteps per second.
\section{Conclusion}
In this work, we have introduced a parallel framework for deep reinforcement learning that can be efficiently parallelized on a GPU. The framework is flexible, and can be used for on-policy and off-policy, as well as value based and policy gradient based algorithms. The presented implementation of the framework is able to reduce training time for the Atari 2600 domain to a few hours, while maintaining state-of-the-art performance. Improvements in training time, will allow the application of these algorithms to more demanding environments, and the use of more powerful models.

redpajama_set_name: RedPajamaArXiv


text:
\section{Introduction\label{sec:intro}}

The $\delta$ Scuti stars are intermediate-mass pulsating variables
with spectral types ranging from A2 to F0. They are located on and
just off the main sequence in the lower part of the Cepheid
instability strip (luminosity classes V \& IV). Nowadays, the $\delta$
Scuti stars are considered as particularly suitable for asteroseismic
studies of poorly known hydrodynamical processes occurring in stellar
interiors such as convective overshoot, mixing of chemical elements
and redistribution of angular momentum (Zahn 1992), etc. Due to the
complexity of the oscillation spectra, their pulsating behaviour is
not fully understood, in particular in what regards the
rotation-pulsation interaction (see a complete rewiew on such effects
in Goupil et al. 2005). In the last decade, numerous interpretation
works have taken the effects of rotation into account (Foz Machado et
al. 2006; Su\'arez et al. 2007a; Su\'arez et al. 2007b; Bruntt et
al. 2007)

The very precise space photometry supplied by the CoRoT mission give
us the possibility to deal with a range and an amount of frequencies
not reached by usual ground based observations. In this work we focus
on the star HD\-174936. This is a field $\delta$ Scuti star observed
during the first short run SRc01 for which we have a frequency
resolution corresponding to 27 days of observation, namely
0.45~$\mu$Hz.

The evolutionary code CESAM (Morel 1997; Morel \& Lebreton 2008) and
the pulsation codes GraCo (Moya et al. 2004; Moya \& Garrido 2008)
have been used as numerical codes to calculate frequencies, growth
rates and other physical quantities. GraCo provides, in particular,
non-adiabatic variables and growth rates. Comparing the theoretical
predictions given by these numerical codes with the observed range of
excited frequencies and studying the periodic spacing in the
oscillation frequency distribution, we have performed a seismic study
in order to constrain the physical parameters of the star.

Finally, we have used a representative model of HD\-174936 to study if
the star can excite, at the same time, the huge number of pulsational
modes observed in $\delta$ Scuti stars from space (Poretti et
al. 2009; Moya \& Rodr\'iguez-L\'opez 2010).

\section{Analysis of the data \label{sec:data}}

The star was observed during the first short run of CoRoT. Around 27
days of very precise photometry at a sampling time of 32~s is the data
base used for the frequency analysis presented here. The spectral
window of the satellite observations is almost perfect (less than 5\%
of side lobes). A detailed explanation of the analysis of this star
can be found in Garc\'ia Hern\'andez (2009).

The time series was analysed using the prescriptions given in Reegen
(2007) and Lenz \& Breger (2005). If we adopt the rather conservative
criteria to stop the search for frequencies when the significance
level is 10 (see Reegen 2007), then 422 frequencies are found. The
obtained power spectrum is shown in Fig.~\ref{fig:spectrum}. More
peaks could be extracted because of the high significance of the
corresponding fitting, but the prewhitening procedure becomes
exponential and we can not be sure whether we are filtering real
frequencies from the object or any other artifact due to the
instrument or intrinsic to the mathematical technique (Poretti et
al. 2009).

Recently , Kallinger \& Matthews (2010) have suggested that the lowest
amplitude modes observed in $\delta$ Scuti stars from space can be due
to surface granulation, and as a consequence only some tenths of modes
with the highest amplitude would be real pulsation modes.

\begin{figure
 \begin{center}
  \scalebox{.20}{\includegraphics{spectrum7613.eps}}
  \caption{A total number of 422 frequencies, ranging from 50 to
    1000~$\mu$Hz, have been obtained. The highest peaks on amplitude
    fall in the interval of 250 to 450 $\mu$Hz.}
  \label{fig:spectrum}
 \end{center}
\end{figure}

Mode identification, mainly for $\delta$ Scuti stars, is one of the
bottle necks for the progress in asteroseismology. Individual mode
identification using white light, as supplied by the CoRoT photometer,
is not possible. However, statistical properties of the full stellar
oscillation spectrum provide us with information related with global
properties of the stellar model. In particular, the classical large
($\Delta\nu=\nu_{n+1,\ell}-\nu_{n,\ell}$) and small
($\delta\nu=\nu_{n,\ell}-\nu_{n-1,\ell+2}$) separations, frequently
used in the solar context, could also be applied to this
star. However, some caution has to be taken, because for $\delta$
Scuti main sequence stars, the excited oscillation modes are not
expected to be in the asymptotic regime.

In order to search for periodic patterns in the frequency set, we
consider them as a set of Dirac's $\delta$'s of equal amplitude,
centred at each frequency value. If the frequencies were equally
spaced, then we will have a Dirac comb with Fourier transform being
another Dirac comb with periodic inverse values and multiples of the
original spacing. That means that if we have a given periodicity in
the frequency set of $\delta f$, then we will have a peak in the
Fourier Transform of $\delta f$ and its sub-multiples, i.e. $\delta
f/n$ with $n=1, 2, 3...$. Although Handler et al. (2000) uses a
similar technique, they do not give any details of the method.

\begin{figure*
 \begin{center}
  \scalebox{.20}{\includegraphics{7613_pattern.eps}}
  \scalebox{.31}{\includegraphics{11932fig5.eps}}
  \caption{Left panel: Power spectrum for various subsets of
    frequencies, selected by amplitudes. The solid line represents the
    power spectrum when the highest 50 frequencies are selected; the
    dashed line correspond to the highest 100 frequencies; the dotted
    line to 250; and the dot-dashed line to all of them. It can be
    seen how the peaks disappear as the number of frequencies
    increases. The peak corresponding to the large separation (25.8
    $\mu\mbox{Hz}$) and its sub-multiples are labelled. Right panel:
    Power spectrum of the theoretical frequencies calculated for a
    representative model of HD\,174936. Only modes with frequencies in
    the range [100,700] and with $\ell=0-3$ have been taken into
    account. The peak at 26.61~$\mu$Hz (and sub-multiples) is the half
    of the possible large separation obtained using these modes.}
  \label{fig:large-sep}
 \end{center}
\end{figure*}

We started this analysis assuming the hypothesis that, selecting a
subset with the highest peaks of the entire frequency set, we are
actually considering mainly the modes of the lowest $\ell$ values. The
visibility of the modes decreases approximately as $\ell^{-2.5}$ or
$\ell^{-3.5}$, depending whether the $\ell$ degree is odd or even
(Dziembowski 1977). Although some authors have identified higher
$\ell$ values in the frequency spectrum of a star observed as a whole
(Daszy\'nska-Daszkiewicz et al. 2006), in general, the selection of
the highest amplitude modes ensures that most of the modes have
$\ell<4$, enough to obtain general properties with an statistical study.

Therefore, we use the hypothesis that, selecting a subset of
frequencies with the highest amplitudes, we select mainly the
frequencies of lowest $\ell$ values. To probe that, we have
constructed several subsets with an arbitrary number of frequencies
taking always the highest peaks and applied the Fourier transform to
them. We have applied the method to HD\,174936:
Fig. \ref{fig:large-sep} (left panel) shows that the greater the
number of frequencies in the subset, the lower the peaks. Clearly,
when we select 50 frequencies a periodic pattern can be recognised,
because of the simultaneous appearance of peaks at 25.8, 13, 8, 6.5
and 4.9~$\mu$Hz. This indicates that we probably have a Dirac comb of
25.8~$\mu$Hz, which is the signature of a large separation of around
52~$\mu$Hz.  We adopted a range of values of [45,60] $\mu$Hz to be
representative of this large separation. Other peaks surrounding the
main one at 25.8 $\mu$Hz (and sub-multiples) may be produced by the
quasi-periodic ``sampling'' exhibited by the frequency set. The rest of
shorter periodicities are less clear to explain, because the periodic
pattern of small separations and g-modes are of the same order.

\section{The modelling \label{sec:models}}

The stellar models were computed with the evolutionary code CESAM
following the recommendations of the ESTA group studies (Lebreton et
al. 2008; Moya et al. 2008). The physics used is that suitable for this
stellar type, and used in numerous studies (Casas et al. 2006; Casas
et al. 2009; Garc\'ia Hern\'andez et al. 2009).

Theoretical oscillation spectra were computed for the equilibrium
models using the GRAnada oscillation COde provides diagnostics on the
instability and non-adiabatic observables. In this code the
non-adiabatic pulsation equations are solved following Unno et
al. (1989).

\section{Constraining the seismic models of HD\,174936 \label{sec:results}}

\begin{figure
 \begin{center}
  \scalebox{.20}{\includegraphics{growth.eps}}
  \caption{Frequency versus growth rate and amplitude. Growth rate
    (solid line, left axis) shows the stability range ($<$ 0) and one
    vertical line of the amplitude height for each frequency is
    represented (right axis).}
  \label{fig:growth}
 \end{center}
\end{figure}

HD\,174936 has a $T_{\rm eff}=8000\pm 200$K, a $\log g=4.08\pm 0.2$
and a $[Fe/H]=-0.32\pm0.2$ . These values are taken from ``CorotSky
Database'' (Charpinet et al. 2006). The rotational velocity ($v\,\sin
i = 169.7$ km/s) has been determined from high-resolution
spectroscopy. It was obtained in the framework of the mission
preparation and it is available at the GAUDI archive (Solano et
al. 2005). It has been shown that rapid rotation should be considered
when calculating the stellar physical parameters from
photometry. Following Michel et al. (1998); Su\'arez et al. (2002),
and considering the absence of additional information on the
inclination angle of the star, uncertainties in the HR-Diagram box of
200~K in $T_{\rm eff}$ and $\sim$ 0.2~dex in $logg$ are adopted.

We constructed models in the HR diagram corresponding to the four
corners and the center of the uncertainty box, with the observed
metallicity and its errors (see Fig.~\ref{fig:box1}), $\alpha_{\rm
  MLT}=0.5$ and overshooting 0.2. Then, for each equilibrium model we
computed the corresponding adiabatic and non-adiabatic oscillations,
and from the whole set of models, we selected those fitting the
average large separation defined in Sect. 2. Finally, from the
remaining subset of models we selected those predicting unstable the
observed frequencies with the largest amplitudes. The properties of
the resulting subset of models are then discussed and analysed.

Rapid rotation makes the seismic interpretation of the oscillation
spectra of $\delta$ Scuti stars difficult, specially regarding the
mode identification. For very fast rotators, it has been shown
(Lignieres et al. 2006) that the rotation-pulsation interaction cannot
be described using a perturbation theory. The non-perturbative theory
for the oscillations computation applied to polytropes predict that
both small and large spacings are affected by rotation. Following
Reese et al. (2008) we estimate (within the range [250, 450] $\mu$Hz)
such an effect on the large separation is about 6 $\mu$Hz for the
models considered in this work.\footnote{Predictions obtained for a
  n=3 polytropic model.} This value remains within the uncertainties
in the determination of the large separation given in Sect. 2,
allowing us to use non-rotating models to restrict the space of valid
models as described in the previous section. This allows us to use
non-rotating models to restrict the space of valid models as described
in the previous section.

\begin{figure
 \begin{center}
  \scalebox{.26}{\includegraphics{box2-0.12.eps}}
  \caption{HR diagram showing the observational photometric
    uncertainty box (the large one) for HD\,174936. The small box is
    that obtained when the asteroseismological constraints are
    used. Filled stars correspond to models representative of the
    star.}
  \label{fig:box1}
 \end{center}
\end{figure}

Equilibrium non-rotating models were computed in the manner described
in Sect. \ref{sec:models}. Only models showing large separations
within the range of [45 ,60] were considered.

For the $\delta$ Scuti stars, the range of the observed frequencies is
far from the asymptotic regime and a clear periodicity is not
expected. However, as it is demonstrated in
Sect. 2, a pattern, identifiable as a large
separation, can be indeed found in the data (Fig. \ref{fig:large-sep},
left panel).

We thus searched for similar regularities in the models (see
Fig. \ref{fig:large-sep}, right panel). We found that the peak at
26.61 $\mu$Hz (and sub-multiples) is the half of the probable large
spacing, allowing us to discard the models that have not reached the
observed large separation. Note that only modes with frequencies in the
range [100,700] and with $\ell=0-3$ were taken into account.
Additional constraints come from the stability analysis of the modes,
as it is illustrated in Fig. 3.

Following an iterative method, the original uncertainty box can be
reduced drastically (Fig. 4). The preliminary result obtained is that
we have the following ranges in age, mass and radius of HD\,174936:
age [788.5, 1705.9] Myr, mass [1.47, 1.82] $M_{\odot}$ and radius [1.61,
  2,05] $R_{\odot}$. This implies a drastic decrease of the mass
uncertainty from a 54\% (without asterosiemology) to a 23\% (with
asteroseismology). A rough estimate of the rotation effects on these
seismic models predicts a variation of 0.03 $M_{\odot}$ in mass, which
is lower than the accuracy here obtained.

Finally, using a representative model for this star, we have studied
if the star can have, from an energetic point of view, all these modes
exited at the same time, with the result that all these modes need a
very small amount of stellar energy (Moya \& Rodr\'iguez-L\'opez 2010).

\section{Conclusions \label{sec:conclusions}}

We have performed an asteroseismic analysis of the $\delta$ Scuti star
HD\,174936, observed by CoRoT during its first short run, SRc01. The
very precise space photometry provides the possibility of dealing with
a significantly large number of frequencies (around 400), for which we
demonstrated that the star has enough energy to excite. However,
Kallinger \& Matthews (2010) have recently suggested that most of the
lowest amplitude frequencies can be a consequence of surface
granulation.

We have combined the classical seismic analysis with the use of
statistical properties of the modes. In particular, we have searched
for periodic patterns in the frequency spectrum of HD\,174936 in order
to find new observational constraints. We have found a peak
distribution in the frequency spectrum that seems to correspond with a
large separation about 50~$\mu$Hz.

We have then performed a theoretical analysis in which models have
been constrained to fit the observed large separation and to predict
unstable the observed modes. These restrictions yield a range of
models with [7801, 8192]~K in $T_{eff}$ and [4.07, 4.19] in $\log g$,
which corresponds to a range of [1.47, 1.82]~$M_{\odot}$ in mass,
[788.5, 1705.9]~Myr in age and [1.61, 2,05]~$R_{\odot}$ in radius.

\acknowledgements {A.G.H. and R.G. acknowledge support from the
  Spanish ``Plan Nacional del Espacio" under project
  ESP2007-65480-C02-01. A.G.H. acknowledges support from a ``FPI"
  contract of the Spanish Ministry of Science and Innovation. CRL
  acknowledges an \'Angeles Alvari\~no contract under Xunta de
  Galicia.JCS acknowledges support from the "Instituto de
  Astrof\'{\i}sica de Andaluc\'{\i}a (CSIC)" by an "Excellence Project
  post-doctoral fellowship" financed by the Spanish "Conjerer\'{\i}a
  de Innovaci\'on, Ciencia y Empresa de la Junta de Andaluc\'{\i}a"
  under proyect "FQM4156-2008".}


text:
via WMFA
Carter Sickels on Capturing Grief and Collective Memory
In Conversation with Courtney Balestier on the WMFA Podcast
By WMFA
Writing can be lonely work; WMFA counters that with conversation. It's a show about creativity and craft, where writer and host Courtney Balestier talks shop with some of today's best writers and examines the issues we face when we do creative work. The mission of WMFA is to explore why we writers do what we do, so that we can do it with more intention, and how we do what we do, so that we can do it better.
In this episode, Carter Sickels talks with Courtney about his latest novel, The Prettiest Star, activist art, writing poignancy without sentimentality, and documenting queer rural narratives.
From the episode:
Carter Sickels: The impetus for the novel was a memory I had from when I grew up in the 80s, which was watching Oprah Winfrey. She did an episode on a man in West Virginia who had returned to his small town. He was gay and had AIDS, and he went swimming in the public swimming pool. Afterwards, he was kicked out and the pool was drained and he was barred from returning. I remembered watching that show and it stuck with me for reasons I didn't understand.
I keep a notebook of novel ideas and story ideas. That was one, a man who returns home who is gay and dying of AIDS in the 80s, that kept showing up in my ideas list. So I started writing actually from the perspective of his younger sister, and then Brian, who's the main character, from his perspective. I just wasn't sure if he would have legs for a novel or if it would be more of a short story, but the characters kept calling me back.
To listen to the rest of the episode, as well as the whole archive of WMFA, subscribe and listen on iTunes or wherever else you find your favorite podcasts.
Carter Sickels is the author of the novel The Evening Hour. He is the recipient of the 2013 Lambda Literary Emerging Writer Award, and has been awarded scholarships to Bread Loaf Writers' Conference, the Sewanee Writers' Conference, VCCA, and the MacDowell Colony. His essays and fiction have appeared in various publications, including Guernica, Bellevue Literary Review, and BuzzFeed, and he is the editor of Untangling the Knot: Queer Voices on Marriage, Relationships & Identity. Carter is Assistant Professor of English at Eastern Kentucky University, where he teaches in the Bluegrass Writers Studio Low-Residency MFA program. He lives in Lexington, Kentucky.
Carter SickelsCourtney BalestierLit Hub RadiopodcastsThe Prettiest StarWMFA
Night. Sleep. Death. The Stars.
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And in the cemetery, she has become lost. A day in early winter slipping to dusk. Impulsively she has decided that it is imperative...


Eye health is a popular topic among pet parents these days because eye diseases and issues can be prevalent in dogs, especially in certain breeds. Fortunately, nature has provided us with quite a few fresh super foods, rich in eye-worthy nutrients that can help keep eyes healthy and strong, and even ward off diseases. Is your pup or kitty's diet nourishing their eyes? Check out this list of foods for great vision to find out! Blueberries Blueberries are some of the best ingredients out there to support eye health for pets. They contain everything from eye-healthy carotenoids, phytonutrients, and flavonoids, as well as zinc and selenium. All of these healthy nutrients help with everything from general eye health, to night vision support, to reduction of eye fatigue. Consider these the eye-solution of foods, and be sure to incorporate them into your pup's diet. Our Vital Slice & Serve rolls are packed with delicious blueberries! Broccoli Broccoli is one of the best veggies for eye health, packed with beta-carotene. Broccoli has even been found to protect the retina from free radical damage. Simply boil up a few florets and add to your pup or kitty's bowl – and don't forget the leaves, as they contain even more beta-carotene! Carrots Carrots are loaded with vitamins like vitamin A, beta-carotene, vitamins B, C, D, E, and K, riboflavin, niacin, calcium… the list goes on and on. Carrots also protect the eye from UVB radiation and damage from free radicals. Many Freshpet foods contain this nutrient-rich veggie, from our Slice & Serve rolls to our Roasted Meals. Cold Water Fish like Salmon and Tuna These fish are rich in Omega-3 fatty acids, important for cellular health. Fish is especially high in DHA, which makes up 30% of the fatty acids that make up the retina. We'd recommend our Vital Chicken, Beef, Salmon and Egg roll or our Vital Complete Meals for dogs to get the benefits of these cold-water fish. Eggs Rich in cycteine, sulphur, and lutein, eggs have been found to protect eyes from cataract formation and reduce the risk of developing macular degeneration. And more than that, eggs are one of the best sources of protein out there. Get some for your furball in our Roasted Meals, Vital Complete Meals, and select Slice & Serve rolls. Kale Kale is a great source of lutein and zeaxanthin, two special antioxidants that act like "internal sunglasses." So protect your fur-kid from the sun with this high quality veggie. This is another great veggie to add to your pet's bowl, especially if you have some around the house for yourself. Sweet Potatoes Often deemed one of the world's healthiest foods, sweet potatoes are loaded with beta-carotene, making them the perfect choice to protect eye health. They also are packed with anthocyanins that have antioxidant and anti-inflammatory properties. Grab some Dog Joy Sweet Potato treats to give your pup a delicious and extremely healthy snack!


text:
An old-school, 'authentic' Tel Aviv market has become a vegan haven
By	Karen Chernick	 April 2, 2019 10:43 am
A vendor roasts nuts in the back of his shop in Tel Aviv's Levinsky Market. (Karen Chernick)
TEL AVIV (JTA) — In a city where new eateries open and older ones close with the frequency of the waves lapping at the nearby seashore, this city's Levinsky Market stands as a place where people have anchored their food businesses for decades.
Chef Haim Rafael, for instance, still prepares Turkish tarama salad according to his grandmother's recipe, whisking breadcrumbs and light pink fish eggs into the same spreadable paste the way she did when the family set up their delicatessen in the market in 1958.
Occupying a seven-block stretch of Levinsky Street in the south of Tel Aviv, the marketplace of dry goods, spices and delis founded in the 1930s by working-class Balkan Jews attracts shoppers looking for specialty items and the smoked and briny flavors of a bygone past.
With its inclination toward kippered fish, cured meats and pungent cheeses, Levinsky Market might not seem at first glance like a logical locus for a vegan invasion.
But it was, in fact, the market's time-honored quality that recently attracted a surprising newcomer to the scene: the upscale vegetable-centric restaurant Opa.
"I think that Levinsky Market is one of the last truly authentic places remaining in the city," said Shirel Berger, chef and co-owner of Opa, about her choice to open a fine dining establishment there last November. "People have had their stores for generations, and I really like the vibe – it seems real and not like a mall, or anything new. It's very raw and authentic."
The market, which occupies a seven-block stretch of Levinsky Street in the south of town, was founded in the 1930s by working-class Balkan Jews. (Karen Chernick)
Opa is the latest plant-based addition to the neighborhood, but certainly not the market's first vegan establishment. Over the past few years, the number of Israeli vegans has swelled to 5 percent of the city's population of approximately 400,000, ranking it high among the countries with the largest number of vegans per capita. Tel Aviv alone boasts 400 vegan-friendly eateries, and several have found a home in Levinsky Market.
"Levinsky Market was actually always a place for vegans without intending to be," said Ori Shavit, a Tel Aviv-based food journalist and vegan advocate. "It has an abundance of pantry staples that are an inextricable part of vegan nutrition, especially anything related to the world of grains and beans, nuts, seeds, dried fruits and of course an enormous range of spices."
"Many vegans shop in Levinsky Market and also live nearby, so it was only natural that they'd eat in the area, and with time their culinary options expanded."
Certain plant-based foods were always abundantly available through vendors in the market, such as the nationally beloved hummus and falafel. But Levinsky's vegan menu has now grown to include items such as nondairy malabi (a vegan version of the traditional Persian milk pudding topped with rosewater syrup and crushed pistachios), cashew-cheese pizza, borekas (Balkan phyllo dough pastries) and nondairy cheeses.
A vendor sells vegan malabi outside the Eliahu Hanavi synagogue on Levinsky Street. (Karen Chernick)
There is even an all-vegan delicatessen resembling the style of Haim Rafael's veteran establishment. The Taste for Life deli opened five years ago. Like many of its Levinsky Street neighbors, it makes all of its own spreads, producing pepper-corned pastrami made from walnuts, tart coconut-based yogurt and soy cheeses.
"It just seemed necessary" to open a location in Levinsky Market, said Daniel Mikitas, co-owner of Taste for Life, "because there are regular delis, so we vegans deserve to have one, too."
The deli, a vegan pioneer when it opened, is in good company now.
"Today the vegan options around the market are very diverse," said Shikma Jacoby, a vegan blogger and advocate who found only two plant-based eateries in the market when she moved to the area three years ago. "You can have anything from incredible desserts to vegan shawarma."
A view of Opa, a vegan newcomer in the market. (Yoav Gurin)
These options include the veteran street vendor permanently parked in front of the Eliahu Hanavi synagogue with signs advertising the rare homemade vegan malabi; Café Kaymak, which serves plant-based versions of traditional home-cooked dishes; a tahini-based tapas restaurant with an entirely vegan menu section called Hatahinia; and an outdoor café, Tony ve Esther, offering elaborate vegan breakfasts that include almond-based labane cheese, tofu scrambles and vegan affogato (ice cream-topped espresso).
Side streets off of Levinsky house Lila Pizza, which happily substitutes cashew cheese on any of its pies, and an artisanal coffee roaster, Cafelix, serving vegan desserts.
These eateries are certainly not the establishments that Levinsky Market was built upon, but they seem to easily coexist with the veterans. Opa sits midway on a block bordered by Fat Dog hot dogs on one corner and a cheese shop called Hahalban (Hebrew for "the milkman") on the other. Berger has found ways to incorporate some of her neighbors into her kitchen.
This kohlrabi dish is served at Opa. (Aviv Shkury)
"All the dry goods are definitely from Levinsky Market, of course," Berger said. "We have a small nut roaster right next door, so of course we work with him. I have relationships with everyone."
For the market's old-timers, it seems to make sense to welcome the new vegan arrivals. Vegans mean business, fresh clientele and renewed interest in the historic market.
Asked how long he's been selling coconut-based malabi from his street cart, the vendor outside the Eliahu Hanavi synagogue answered "for years already. Everybody likes it."
"I think that Levinsky Market is extremely open to veganism and is embracing it," Jacoby said. "It's almost as if when you don't offer vegan options, you are kind of out of the loop."
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Explosions heard near Kiev's main airport after Putin announces military operation in Ukraine
Kiev [Ukraine]: Multiple explosions were heard near the main airport in the Ukrainian capital of Kiev soon after Russia announced a military operation in Ukraine, media reports said on Thursday. Several reports indicate several explosions in the Boryspil area to the east of the capital, CNN reported. According to the American broadcaster, at least two massive explosions were reported in the early hours of Thursday. Announcing a special "military operation" in the Donbas region, Russian President Vladimir Putin warned other countries that any attempt to interfere with the Russian action would lead to "consequences". Delivering an emergency address, Putin said the operation has been launched to demilitarize Ukraine and defend people's "suffering, persecution and genocide" by the Kiev regime."I have taken the decision to carry out a special military operation. Its goal will be to defend people who for eight years are suffering persecution and genocide by the Kiev regime. For this we will aim for demilitarization and de-Nazification of Ukraine," said Putin, asking Ukrainian soldiers to lay down arms. This comes hours after Ukrainian President Volodymyr Zelenskyy said Ukraine has not posed and will not pose a threat to Russia. In an emotional appeal delivered largely in Russian, Zelenskyy refuted Moscow's claims that his country poses a threat to Russia and warned that a Russian invasion would cost tens of thousands of lives. After the military operation was announced, US President Joe Biden condemned Russia's actions, in the Donbas region of eastern Ukraine. The US President said that he is monitoring the situation from the White House, and will soon meet with the other G7 leaders.
at 8:43 PM Posted by www.kickassnews.in


text:
https://sixerswire.usatoday.com/2020/10/08/sixers-team-with-african-american-chamber-of-commerce-black-businesses/
Sixers team with African American Chamber of Commerce, Black businesses
The Philadelphia 76ers continue to step up and help the Black community in the area. After the managing group of Josh Harris and David Blitzer stepped up and donated $20 million in order to help the fight against systematic racism and they then hired David Gould to lead their racial equality initiatives.
Now, the Sixers are teaming up with the African American Chamber of Commerce for Pennsylvania, New Jersey, and Delaware. The team wants to help promote more Black-owned businesses in the area and the Sixers will be the title sponsor for the Chamber's annual event on October 29 which will be held virtually this year.
"This is the start of a great relationship with the African American Chamber of Commerce. As exemplified by the $20 million commitment made by our managing partners earlier this year, we are deeply committed to pushing for racial equity and know that supporting Black-owned businesses is a critical component to that effort," said Gould via a press release. "The Chamber's partnership will be critical in helping us reach and support Black-owned businesses, and we're looking forward to working with the Chamber to ensure that more of these companies can compete and thrive within our region and economy."
The virtual event will include speaking opportunities, a six-part digital content series highlighting local Black-owned businesses across social media and email, in addition to active recruitment of applicants to participate in the 76ers new upcoming programs supporting Black-owned businesses.
This is another example of Harris, Blitzer, and the rest of the organization stepping up and helping the Black community. In a time where there is a huge civil rights movement going on, it is inspiring to see bigger companies stepping into the fight for equality in the world.
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