Introduction
Penny Arcade is a content creation website founded by Jerry Holkins and Mike Krahulik. Although originally based on a weekly three panel webcomic, the organization (and its associated website) have expanded to include a wide range of content. The website hosts the original web comic, several other related comics, podcasts, and at least one video series. The website, found at https://www.penny-arcade.com/, is the front page for all of this content and is the subject of this usability analysis.
The website alternates between a few color palletes, mostly based on dark blues, oranges, and whites. In most cases, the contrast appears to work: the main body text of the page is white on a dark blue background. However, there are several examples in which low-contrast colors are used to display text. Consider the image below, which features a post from the website. The title and text of the post is white on dark blue (#002966). The author's name appears in a light blue (##04bbe4), although it should be pointed out that different authors have different colors. The date of the post, however, appears in a dark blue (#004ba6) that is only slightly lighter than the background. Although the colors form a coherent array for branding reasons, they don't necessarily work for readability.
Although the dark blue on darker blue presents a contrast issue, it is not the only color combination of concern. Several of the areas of the page feature white text on an orange background (#FF7600), a combination that corresponds to a contrast ratio of 2.67:1. This is far below the WCAG 2 Contrast requirement of 4.5:1.
The Navigation Bar and Site Navigation
The navigation for this page primarily as a navigation bar across the top of the page. The main content types here are: Comics; News; PATV; Podcasts; Archive; Forum; and Shop. There is also a search box to the right which allows the user to search for specific text. Several of the navigation items feature a drop-down menu, providing a sort of organizational heirarchy for the website. For example, under Comics links can be found to "the original" Penny Arcade strip, The Trenches, Camp Weedonwantcha, PA Side Stories, and PA Presents. There is also a thin menu of options above the navigation bar, although all of these lead to other sites within the Penny Arcade organization.
The entire navigation menu is sticky insomuch that sticks to the top of the web browser once the user scrolls past the banner ad at the top of the page. This means that no matter how far down the page a user goes, they always have the ability to navigate throughout the website. However, it is worth emphasizing that any link that goes to another "site" within the Penny Arcade organization does not feature any of the same navigation and it is easy to get confused. For example, three of the links under the comics navigation menu item lead to pages within the Penny Arcade website: the first (from the left) and the last two (on the right). The second and third link actually lead to external websites. This is confusing to navigate because nothing makes it clear that the user will be redirected to an external site until it happens.
Perhaps the most bizarre navigation feature on the page is the navigation link labelled archive. Unlike other conventional archives, this link actually goes to a list of keywords. Instead of providing any meaningful organization, the "archive" is just a large list of popular keywords. Given the search box in the navigation bar, one could presume that this archive is not a popular destination on the page.
The website does not use any sort of system to make it clear what the user is currently viewing or where in the site's organization that page exists. In some cases, this actually makes for rather confusing navigation. For example, there is a link under the PATV navigation menu item that takes the user to a page featuring a series of twelve videos from the Acquisitions Incorporated video series. There is also a link under the PODCASTS navigation menu item that takes the user to a page featuring a series of podcast episodes from the Acquisition Incorporated podcast series. Although these are both separate pages on the website, the content are related: the first twelve podcast episodes presented are the audio track from the twelve videos featured in the video page. It's actually a confusing distinction that likely highlights issues with the way the website has divided and organized content.
Conclusions
The Penny Arcade website represents one of those kinds of sites that feels really sharp and impressive when you first see it but that quickly becomes something less impressive the more you use it. Although the color scheme looks really good when the page first loads, some of the colors make content difficult to read. The navigation menu looks good and stays with the user, but some of the navigation takes the user off of the page without notification or links to separate pages that show the same content (but in a different way).
What this website demonstrates is that website organization should not necessarily be done in the same way as other types of organization. Having separate navigation items for videos and podcasts makes sense, except it becomes confusing when most of the content appears under both navigation items. Similarly, although it makes sense to organize all comic content under one item, that organization is suspect when two of the five items actually take the user to an external website (without notification). In all, it feels as if the Penny Arcade website suffers from a fair number of issues that are rooted in design choices made many years ago.


{% load static %}
Third Eye (Divya Drishti)
Third Eye : Your Insight
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Technology Rigged At Its Core


Indiana state park closures set for 4 days of deer hunts
INDIANAPOLIS (AP) - Seventeen Indiana state park sites will close their gates to visitors for a pair of two-day deer hunts in the coming weeks.
The hunts are scheduled for Nov. 18-19 and Dec. 2-3. The Indiana Department of Natural Resources says wildlife biologists evaluate the parks to determine where deer hunts are needed to ensure healthy habitats for native plants and animals.
This year’s hunts come after a state appeals court rejected a lawsuit challenging the DNR’s authority to allow hunters armed with rifles into state parks.
Deer hunts are planned for Chain O’Lakes, Charlestown, Clifty Falls, Fort Harrison, Harmonie, Indiana Dunes, McCormick’s Creek, Ouabache, Pokagon, Prophetstown, Shakamak, Spring Mill, Summit Lake, Tippecanoe River and Whitewater Memorial state parks, along with Cave River Valley Natural Area and Trine State Recreation Area.
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WebClientDataBufferAllocatingTests
|
100%
successful |
Tests
| Test | Method name | Duration | Result |
|---|---|---|---|
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[1] | 0.038s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[2] | 0.105s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[3] | 0.383s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[4] | 0.128s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[5] | 0.424s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[6] | 0.024s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[1] | 5.695s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[2] | 0.187s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[3] | 0.249s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[4] | 0.182s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[5] | 0.161s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[6] | 0.071s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[1] | 0.062s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[2] | 0.085s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[3] | 0.074s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[4] | 0.045s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[5] | 0.022s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[6] | 0.014s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[1] | 0.016s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[2] | 0.270s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[3] | 0.094s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[4] | 0.060s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[5] | 0.077s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[6] | 0.343s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[1] | 0.146s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[2] | 0.154s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[3] | 0.168s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[4] | 0.051s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[5] | 0.036s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[6] | 0.036s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[1] | 0.131s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[2] | 0.012s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[3] | 0.018s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[4] | 0.108s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[5] | 0.015s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[6] | 0.013s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[1] | 0.281s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[2] | 0.330s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[3] | 0.165s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[4] | 0.192s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[5] | 0.122s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[6] | 0.096s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[1] | 0.018s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[2] | 0.022s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[3] | 0.018s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[4] | 0.024s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[5] | 0.015s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[6] | 0.025s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | releaseBody(String, DataBufferFactory)[1] | 0.024s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | releaseBody(String, DataBufferFactory)[2] | 0.016s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | releaseBody(String, DataBufferFactory)[3] | 0.016s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | releaseBody(String, DataBufferFactory)[4] | 0.021s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | releaseBody(String, DataBufferFactory)[5] | 0.018s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | releaseBody(String, DataBufferFactory)[6] | 0.024s | passed |
Standard output
12:29:04.538 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [153a097e] HTTP GET http://<IP_ADDRESS>:64015/sample 12:29:06.650 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [153a097e] Response 202 ACCEPTED 12:29:06.863 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7ee62827] HTTP GET http://<IP_ADDRESS>:64032/sample 12:29:07.044 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7ee62827] Response 202 ACCEPTED 12:29:07.053 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [32a90bd8] HTTP GET http://<IP_ADDRESS>:64034/sample 12:29:07.289 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [32a90bd8] Response 202 ACCEPTED 12:29:07.303 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [270e2216] HTTP GET http://<IP_ADDRESS>:64042/sample 12:29:07.406 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [270e2216] Response 202 ACCEPTED 12:29:07.486 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [71d998b9] HTTP GET http://<IP_ADDRESS>:64044/sample 12:29:07.639 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [71d998b9] Response 202 ACCEPTED 12:29:07.645 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [dd21fb0] HTTP GET http://<IP_ADDRESS>:64046/sample 12:29:07.712 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [dd21fb0] Response 202 ACCEPTED 12:29:07.722 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3c663] HTTP GET http://<IP_ADDRESS>:64048/json 12:29:07.846 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3c663] Response 502 BAD_GATEWAY 12:29:07.867 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1017e088] HTTP GET http://<IP_ADDRESS>:64050/json 12:29:08.015 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1017e088] Response 502 BAD_GATEWAY 12:29:08.023 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3382446e] HTTP GET http://<IP_ADDRESS>:64052/json 12:29:08.183 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3382446e] Response 502 BAD_GATEWAY 12:29:08.192 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5a3eb66b] HTTP GET http://<IP_ADDRESS>:64054/json 12:29:08.235 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5a3eb66b] Response 502 BAD_GATEWAY 12:29:08.244 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [751494ea] HTTP GET http://<IP_ADDRESS>:64056/json 12:29:08.273 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [751494ea] Response 502 BAD_GATEWAY 12:29:08.280 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3f0eb5b8] HTTP GET http://<IP_ADDRESS>:64058/json 12:29:08.310 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3f0eb5b8] Response 502 BAD_GATEWAY 12:29:08.319 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1ad58a38] HTTP GET http://<IP_ADDRESS>:64060/ 12:29:08.362 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1ad58a38] Response 201 CREATED 12:29:08.381 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6415fb7c] HTTP GET http://<IP_ADDRESS>:64062/ 12:29:08.463 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6415fb7c] Response 201 CREATED 12:29:08.467 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60225039] HTTP GET http://<IP_ADDRESS>:64064/ 12:29:08.538 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60225039] Response 201 CREATED 12:29:08.542 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4091ba9d] HTTP GET http://<IP_ADDRESS>:64067/ 12:29:08.583 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4091ba9d] Response 201 CREATED 12:29:08.587 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4f063d2d] HTTP GET http://<IP_ADDRESS>:64070/ 12:29:08.606 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4f063d2d] Response 201 CREATED 12:29:08.611 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6d495d65] HTTP GET http://<IP_ADDRESS>:64076/ 12:29:08.621 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6d495d65] Response 201 CREATED 12:29:08.631 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [77dab84] HTTP GET http://<IP_ADDRESS>:64078/json 12:29:08.664 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [77dab84] Response 201 CREATED 12:29:08.669 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [531d57c9] HTTP GET http://<IP_ADDRESS>:64080/json 12:29:08.764 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [531d57c9] Response 201 CREATED 12:29:08.776 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [20557221] HTTP GET http://<IP_ADDRESS>:64082/json 12:29:08.820 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [20557221] Response 201 CREATED 12:29:09.165 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [29956cf8] HTTP GET http://<IP_ADDRESS>:64085/json 12:29:09.210 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [29956cf8] Response 201 CREATED 12:29:09.297 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1e7369e2] HTTP GET http://<IP_ADDRESS>:64087/json 12:29:09.714 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1e7369e2] Response 201 CREATED 12:29:09.718 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [72738e7d] HTTP GET http://<IP_ADDRESS>:64089/json 12:29:09.738 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [72738e7d] Response 201 CREATED 12:29:09.746 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6ab1901b] HTTP GET http://<IP_ADDRESS>:64091/json 12:29:09.758 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6ab1901b] Response 502 BAD_GATEWAY 12:29:09.765 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [246702b4] HTTP GET http://<IP_ADDRESS>:64093/json 12:29:09.780 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [246702b4] Response 502 BAD_GATEWAY 12:29:09.786 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d5396d6] HTTP GET http://<IP_ADDRESS>:64095/json 12:29:09.798 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d5396d6] Response 502 BAD_GATEWAY 12:29:09.806 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4ac307b2] HTTP GET http://<IP_ADDRESS>:64097/json 12:29:09.822 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4ac307b2] Response 502 BAD_GATEWAY 12:29:09.831 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [17c834e2] HTTP GET http://<IP_ADDRESS>:64099/json 12:29:09.839 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [17c834e2] Response 502 BAD_GATEWAY 12:29:09.847 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7d9ac9fc] HTTP GET http://<IP_ADDRESS>:64101/json 12:29:09.865 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7d9ac9fc] Response 502 BAD_GATEWAY 12:29:09.875 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6a60e328] HTTP GET http://<IP_ADDRESS>:64103/ 12:29:09.896 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6a60e328] Response 200 OK 12:29:09.900 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2ac870de] HTTP GET http://<IP_ADDRESS>:64105/ 12:29:09.913 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2ac870de] Response 200 OK 12:29:09.918 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1e042a7d] HTTP GET http://<IP_ADDRESS>:64107/ 12:29:09.929 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1e042a7d] Response 200 OK 12:29:09.934 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [724fbbe7] HTTP GET http://<IP_ADDRESS>:64109/ 12:29:09.951 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [724fbbe7] Response 200 OK 12:29:09.955 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6f2151db] HTTP GET http://<IP_ADDRESS>:64111/ 12:29:09.971 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6f2151db] Response 200 OK 12:29:09.976 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [383841ad] HTTP GET http://<IP_ADDRESS>:64113/ 12:29:09.996 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [383841ad] Response 200 OK 12:29:10.001 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4e5d4a1b] HTTP GET http://<IP_ADDRESS>:64115/json 12:29:10.012 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4e5d4a1b] Response 502 BAD_GATEWAY 12:29:10.018 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [70194475] HTTP GET http://<IP_ADDRESS>:64117/json 12:29:10.280 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [70194475] Response 502 BAD_GATEWAY 12:29:10.290 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [24513c78] HTTP GET http://<IP_ADDRESS>:64119/json 12:29:10.375 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [24513c78] Response 502 BAD_GATEWAY 12:29:10.391 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [381fe983] HTTP GET http://<IP_ADDRESS>:64121/json 12:29:10.437 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [381fe983] Response 502 BAD_GATEWAY 12:29:10.453 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [50220b8e] HTTP GET http://<IP_ADDRESS>:64123/json 12:29:10.522 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [50220b8e] Response 502 BAD_GATEWAY 12:29:10.530 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6c282421] HTTP GET http://<IP_ADDRESS>:64125/json 12:29:10.867 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6c282421] Response 502 BAD_GATEWAY 12:29:10.980 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7403f8de] HTTP GET http://<IP_ADDRESS>:64127/json 12:29:11.150 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7403f8de] Response 502 BAD_GATEWAY 12:29:11.161 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1dadbd67] HTTP GET http://<IP_ADDRESS>:64142/json 12:29:11.481 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1dadbd67] Response 502 BAD_GATEWAY 12:29:11.489 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d303d6] HTTP GET http://<IP_ADDRESS>:64149/json 12:29:11.574 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d303d6] Response 502 BAD_GATEWAY 12:29:11.658 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [153fbac7] HTTP GET http://<IP_ADDRESS>:64161/json 12:29:11.784 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [153fbac7] Response 502 BAD_GATEWAY 12:29:11.852 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [88b0b4a] HTTP GET http://<IP_ADDRESS>:64173/json 12:29:11.965 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [88b0b4a] Response 502 BAD_GATEWAY 12:29:11.974 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4e01950f] HTTP GET http://<IP_ADDRESS>:64180/json 12:29:12.065 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4e01950f] Response 502 BAD_GATEWAY 12:29:12.077 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4ee3c2cd] HTTP GET http://<IP_ADDRESS>:64184/json 12:29:12.198 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4ee3c2cd] Response 502 BAD_GATEWAY 12:29:12.204 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [e7aa242] HTTP GET http://<IP_ADDRESS>:64186/json 12:29:12.211 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [e7aa242] Response 502 BAD_GATEWAY 12:29:12.217 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1fa12b] HTTP GET http://<IP_ADDRESS>:64188/json 12:29:12.228 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1fa12b] Response 502 BAD_GATEWAY 12:29:12.236 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [13131238] HTTP GET http://<IP_ADDRESS>:64190/json 12:29:12.336 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [13131238] Response 502 BAD_GATEWAY 12:29:12.344 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [69e7597e] HTTP GET http://<IP_ADDRESS>:64200/json 12:29:12.354 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [69e7597e] Response 502 BAD_GATEWAY 12:29:12.361 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2c0e0f25] HTTP GET http://<IP_ADDRESS>:64202/json 12:29:12.367 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2c0e0f25] Response 502 BAD_GATEWAY


Honzi
/
Guides
/Hearthstone
Collecting All Cards
Colors
Decks:
Adventure Priest
Renounce Darkness Warlock
"Fun" Random
General
Hero Power Only
Leveling
Meme Decks
Tavern Brawls:
"Choose 1" Ice Block Mage
Shifter Zerus
Tools
Rarity
Craft Normal
Craft Golden
Disenchant Normal
Disenchant Golden
Common
40
400
5
50
Rare
100
800
20
100
Epic
400
1,600
100
400
Legendary
1,600
3,200
400
1,600


Front end web development and design student in Portland, Oregon. I also offer photography services, including family portraits, professional headshots, product photography and more!
I built my own business from the ground up, which means I have seven years of hands-on experience in small business branding and marketing, along with photography and design.


|
lubyk
0.5
|
#include <b2GrowableStack.h>
Public Member Functions | |
| b2GrowableStack () | |
| ~b2GrowableStack () | |
| void | Push (const T &element) |
| T | Pop () |
| int32 | GetCount () |
Private Attributes | |
| T * | m_stack |
| T | m_array [N] |
| int32 | m_count |
| int32 | m_capacity |
This is a growable LIFO stack with an initial capacity of N. If the stack size exceeds the initial capacity, the heap is used to increase the size of the stack.
Definition at line 28 of file b2GrowableStack.h.
| b2GrowableStack< T, N >::b2GrowableStack | ( | ) | [inline] |
Definition at line 31 of file b2GrowableStack.h.
References b2GrowableStack< T, N >::m_array, b2GrowableStack< T, N >::m_capacity, b2GrowableStack< T, N >::m_count, and b2GrowableStack< T, N >::m_stack.
| b2GrowableStack< T, N >::~b2GrowableStack | ( | ) | [inline] |
Definition at line 38 of file b2GrowableStack.h.
References b2Free(), b2GrowableStack< T, N >::m_array, and b2GrowableStack< T, N >::m_stack.
| int32 b2GrowableStack< T, N >::GetCount | ( | ) | [inline] |
Definition at line 72 of file b2GrowableStack.h.
References b2GrowableStack< T, N >::m_count.
Referenced by b2DynamicTree::Query(), and b2DynamicTree::RayCast().
| T b2GrowableStack< T, N >::Pop | ( | ) | [inline] |
Definition at line 65 of file b2GrowableStack.h.
References b2Assert, b2GrowableStack< T, N >::m_count, and b2GrowableStack< T, N >::m_stack.
Referenced by b2DynamicTree::Query(), and b2DynamicTree::RayCast().
| void b2GrowableStack< T, N >::Push | ( | const T & | element | ) | [inline] |
Definition at line 47 of file b2GrowableStack.h.
References b2Alloc(), b2Free(), element, b2GrowableStack< T, N >::m_array, b2GrowableStack< T, N >::m_capacity, b2GrowableStack< T, N >::m_count, b2GrowableStack< T, N >::m_stack, and T.
Referenced by b2DynamicTree::Query(), and b2DynamicTree::RayCast().
T b2GrowableStack< T, N >::m_array[N] [private] |
Definition at line 79 of file b2GrowableStack.h.
Referenced by b2GrowableStack< T, N >::b2GrowableStack(), b2GrowableStack< T, N >::Push(), and b2GrowableStack< T, N >::~b2GrowableStack().
int32 b2GrowableStack< T, N >::m_capacity [private] |
Definition at line 81 of file b2GrowableStack.h.
Referenced by b2GrowableStack< T, N >::b2GrowableStack(), and b2GrowableStack< T, N >::Push().
int32 b2GrowableStack< T, N >::m_count [private] |
Definition at line 80 of file b2GrowableStack.h.

T* b2GrowableStack< T, N >::m_stack [private] |
Definition at line 78 of file b2GrowableStack.h.


Commercializing disruptive technology that improves the world.
About CobaltCobalt is a team of entrepreneurs, scientists, innovators, and investors dedicated to commercializing groundbreaking technologies.
What We DoCobalt sources, vets, seeds and builds teams around a diverse portfolio of short, medium and long-term projects for high-level economic performance. Building upon the strengths of academic, research, and government lab partners and investments, Cobalt creates value through a unique commercialization process, a network of external and in-house experts, and strategic partnerships.
Innovation Speed
Spotlight
Smart Reefs
Cobalt is inspired by biomimicry and technology to shape how we think about protecting coastlines.
Exercise Device
for Elite Athletes
Leveraging the power of robotics and artificial intelligence to change the way athletes are trained and rehabilitated.
Cobalt
Team
Our diverse team of entrepreneurs and technology experts possesses a combined experience of over 100 years in product and business development.


Where Are We Heading?
Second star to the right and straight on till morning.
Watch me not change!
We're on a Road to Nowhere


I'm an undergraduate student majoring in Electrical Engineering at
Indian Institute of Technology, Palakkad, Kerala.
I am from Ujjain, the
city of temples, famous for Mahakaleshwar Mandir.
My hobbies are
image editing, photography and playing musical instruments. I am also
a big foodie.
I like connecting with different peoples and learning new
things from their experiences.
I'm a self motivated student and a keen
observer seeking for opportunities to enhance my skills.


This document is intended to assist software developers who want to develop applications using UTDeliver.com API. It fully documents our application programming interface (API) that allows developers to interact with our system.
To use the information provided here you should be familiar with:
Our Application Program Interface will allow you to automate the process of searching/buying player auctions and comfort trades within your own software.
Since our API is based on REST principles, it's very easy to write and test applications. You can use your browser to access URLs, and you can use pretty much any HTTP client in any programming language to interact with the API.
All responses from our API are in JSON format.
Requests are limited at 60 RPM (Requests per minute).
In order to use our API, you must have an active account at UTDeliver.com. The authentication is based on "HTTP Basic auth", making it dead simple to make calls on our platform. The following is an example with PHP, just one line of code is required for authentication.
curl_setopt($ch, CURLOPT_USERPWD, '{username}:{password}');
Our REST API is served over HTTPS. To ensure data privacy, unencrypted HTTP is not supported. The Base URL for all the requests is:
https://www.utdeliver.com/api/20
This section describes how to fetch your account coin balances.
https://www.utdeliver.com/api/20/balance
A successful call will return a JSON object.
{ "ps4": 1000000, "ps3": 50000, "xboxone": 1200000, "xbox360": 10000 }
| Name | Type | Description |
|---|---|---|
<platform> |
Integer |
Coin balance for <platform> .
|
This section describes how to get the current coin prices.
https://www.utdeliver.com/api/20/price/<platform>
Valid <platform>
parameters are:
A successful call will return a JSON object.
{ "availability": "high", "price" : 0.0745 }
| Name | Type | Description |
|---|---|---|
| availability | String | Human readable stock availability. |
| price | Float | Returns the price for 1k coins. |
This section describes how to buy coins.
https://www.utdeliver.com/api/20/buyCoins
| Name | Type | Description |
|---|---|---|
| platform | String |
One of the following:
|
| amount | Integer | Amount of coins to purchase. Min: 10000. Must be multiple of 10,000. |
| price | Float | Price of coins, as returned by previous call Coin Prices. |
A successful call will return a JSON object.
{ "success" : "Bought 100,000 ps4 @0.075", "error" : "Coin prices has changed: 0.0745" }
This section describes how to add a Comfort Trade.
https://www.utdeliver.com/api/20/comfort/add
| Name | Type | Description |
|---|---|---|
| platform | String |
One of the following:
|
| String | The Ultimate Team account email. | |
| password | String | The Ultimate Team account password. |
| backupCode | String | Origin account backup code for Two Factor authentication. |
| amount | Integer | Amount of coins you want to fill the accounts with. Example (100k): 100000. |
| orderId | String | Optional: An identifier for this order. |
| ownStock | String |
Optional: If you want to deliver this order using your own stock, you can specify this parameter to y .
|
A successful call will return a JSON object. Example:
{ "success" : true }
A failed call will return two additional fields error
containing a verbose explaination of the failure and an errorCode
. This is a list of possible errorCode
:
This section describes how to check the status of a comfort trade.
https://www.utdeliver.com/api/20/comfort/<email|couponKey>/status
You must replace <email|couponKey>
with the Ultimate Team email account or the coupon key you want to check the status of.
A successful call will return a JSON object.
{ "addedOn": "1450026393", "orderId": "custom orderIdentifier", "platform": "ps4", "email"<EMAIL_ADDRESS>"target": "150000", "delivered": "150419", "queued": "0", "status": "processed" }
If you have chosen to use your own stock for this order, an additional array cards
will be returned with the information of the cards you have to purchase with your own stock.
{ "0": { "addedOn": "1516969631", "tradeId": "209888504422", "assetId": "162280", "resourceId": "50493928", "buyNowPrice": "19500", "status": "new", "purchasedOn": null }, "1": { ... }, ... }
This section describes how to pause / unpause / remove a Comfort Trade.
https://www.utdeliver.com/api/20/comfort/<email|couponKey>/status
| Name | Type | Description |
|---|---|---|
| action | String |
One of the following:
|
A successful call will return a JSON object. Example:
{ "success" : true }
When you submit a new order and you have chosen to use your own stock it's your responsability to update the status on our system accordingly. Otherwise orders won't process correctly and your customers will be able to re-use existing coupon codes.
https://www.utdeliver.com/api/20/ownStock/submit
| Name | Type | Description |
|---|---|---|
| platform | String |
One of the following:
|
| tradeId | Integer | The Trade ID you are updating the status of. |
| action | String |
One of the following:
|
A successful call will return a JSON object. Example:
{ "success" : true }


[§658A-13] Action by majority. If there is more than one arbitrator, the powers of an arbitrator shall be exercised by a majority of the arbitrators, but all of them shall conduct the hearing under section 658A-15(c). [L 2001, c 265, pt of §1]


PLAY IT TO THE BONE A film review by Steve Rhodes Copyright 1999 Steve Rhodes RATING (0 TO ****): **
Writer/director Ron Shelton opens PLAY IT TO THE BONE with a long aerial shot of the famous pyramid. No, not one of those old run-down Egyptian pyramids but one of the fancy new hotels that dot the Las Vegas landscape, home to the lucrative sports of gambling and boxing. As the gaudy neon sign on the entrance to the city modestly proclaims, "Welcome to Fabulous Las Vegas, Nevada."
Probably intended partially as a comedy and partially as an indictment of the sport of boxing, the movie isn't much of either because of its badly underwritten script. "Somebody tell me why a Christian is getting laid, and a heathen like me isn't," is typical of its would-be funny lines. Shelton's non-subtle idea of a visual diatribe against professional fighting is to have two friends pulverize each other as the make-up department applies increasing amounts of fake blood.
The story starts when the fighters in the under card (that's the warm-up event) for the big Mike Tyson title fight in Las Vegas become unavailable. One of these second-string fighters has fried his brains on drugs, and the other has died in a car accident. The sleazy promoters turn to a couple of washed-up LA fighters to fill the bill, offering them $100,000 if they'll fly immediately to Las Vegas and fight that evening.
One of the fighters, the religiously-tattooed Vince Boudreau (Woody Harrelson), is an unconvincing, bible-carrying Christian, who regularly sees Jesus and likes to write "Jesus Saves" graffiti on bathroom walls. When Jesus appears, he looks like a hippie in white robes. After bouts of profanity, Vince likes to pray for forgiveness. Wild sex with strangers does not require any such remorse.
Vince's buddy, Caesar Dominguez (Antonio Banderas), says very funny things, but they are all in Spanish. At least the guy next to me thought that they were hilarious. Not able to comprehend Spanish, I can only comment on his English lines, which were singularly uninteresting.  This plot device allows Vince to ridicule him through most of the movie.
You might think that these down-on-their-luck guys would catch the first plane to Vegas, but you'd be wrong. In order to make the story into a road picture, Shelton has them hitch a ride with their common ex-girlfriend in her vintage, sea-grass green Oldsmobile 442. The three of them bicker as they go along the road.
Lolita Davidovich, an actress who has given few, if any, memorable performances in her career, plays their ex, Grace Pasic. Davidovich does provide the film's most impressive visual when she dons a shear, bright red dress that barely covers her body. She is cast as an inventor of items from sox to periscopes. She thinks she'll find venture capitalists in Sin City to bankroll her ideas. One potential investor, the owner of the lavish Mandalay hotel (Robert Wagner), likes her body but not her revolutionary idea for men's sox.
Also along for part of the ride is Lia (Lucy Alexis Liu), a wild woman interested only in drugs and sex. She gets plenty of the latter.
The movie culminates in a long fighting sequence in which Vince and Caesar pound each other until their faces resemble squashed tomatoes. The completely predicable conclusion seems like it will never end.
PLAY IT TO THE BONE runs 2:00. It is rated R for brutal ring violence, strong sexuality including dialogue, nudity, pervasive language and some drug content. The film would be acceptable for older teenagers.
Email<EMAIL_ADDRESS>Web: http://www.InternetReviews.com
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Interactively underwhelm high-quality process improvements and highly efficient synergy. Intrinsicly leverage other's high-quality interfaces without optimal core competencies. Continually seize interactive customer service before long-term high-impact innovation. Rapidiously reconceptualize superior leadership before goal-oriented quality vectors.
Appropriately harness e-business process improvements vis-a-vis magnetic strategic theme areas. Quickly exploit open-source infrastructures and premium technologies. Interactively e-enable resource maximizing systems without robust models.
Completely envisioneer state of the art results before multifunctional innovation. Quickly cultivate cross-media synergy with multidisciplinary strategic theme areas.


In this example, a master server is setup with two direct slaves. This example was written and tested using Slony-I v1.2.11 and PostgreSQL 8.2.5, running on a single Windows XP machine. The PostgresSQL pgbench utility is used to generate the test schema and workload.
Create 3 databases, master, slave1 and slave2 and ensure pl/pgsql is setup in each.
Create a pgbench schema in the master database:
> pgbench -i -U postgres master
Add a primary key called history_pkey to the history table on the tid, bid and aid columns
Create a schema-only dump of the master database, and load it into slave1 and slave2:
> pg_dump -s -U postgres master > schema.sql
> psql -U postgres slave1 < schema.sql
> psql -U postgres slave2 < schema.sql
Create Slony config files for each slon engine (daemon on Unix). The files should contain just the following two lines:
cluster_name='pgbench'
conn_info='host=<IP_ADDRESS> port=5432 user=postgres dbname=master'
Create a file for each database, adjusting the dbname parameter as required and adding any other connection options that may be needed.
(Windows only) Install the Slony-I service:
> slon -regservice Slony-I
Register each of the engines (this is only necessary on Windows - on Unix the slon daemons may be started individually and given the path to the config file on the command line using the -f option):
> slon -addengine Slony-I C:\slony\master.conf
> slon -addengine Slony-I C:\slony\slave1.conf
> slon -addengine Slony-I C:\slony\slave2.conf
In pgAdmin under the Slony Replication node in the master database, create a new Slony-I cluster using the following options:
Join existing cluster: Unchecked
Cluster name: pgbench
Local node: 1 Master node
Admin node: 99 Admin node
Under the Slony Replication node, create a Slony-I cluster in each of the slave databases using the following options:
Join existing cluster: Checked
Server: <Select the server containing the master database>
Database: master
Cluster name: pgbench
Local node: 10 Slave node 1
Admin node: 99 - Admin node
Join existing cluster: Checked
Server: <Select the server containing the master database>
Database: master
Cluster name: pgbench
Local node: 20 Slave node 2
Admin node: 99 - Admin node
Create Paths on the master to both slaves, and on each slave back to the master. Create the paths under each node on the master, using the connection strings specified in the slon config files. Note that future restructuring of the cluster may require additional paths to be defined.
Create a Replication Set on the master using the following settings:
ID: 1
Comment: pgbench set
Add the tables to the replication set using the following settings:
Table: public.accounts
ID: 1
Index: accounts_pkey
Table: public.branches
ID: 2
Index: branches_pkey
Table: public.history
ID: 3
Index: history_pkey
Table: public.tellers
ID: 4
Index: tellers_pkey
On the master node, create a new subscription for each slave using the following options:
Origin: 1
Provider: 1 - Master node
Receiver: 10 - Slave node 1
Origin: 1
Provider: 1 - Master node
Receiver: 20 - Slave node 2
Start the slon service (or daemons on Unix):
> net start Slony-I
Initial replication should begin and can be monitored on the statistics tab in pgAdmin for each node. The pgbench utility may be run against the master database to generate a test workload.


The sophomore class in particular will be divided. This is because there is a large percentage who have never experienced life on campus because of the pandemic and opted to stay home. On the other hand, some sophomores got the opportunity to spend at least a part of last school year on campus.
Here’s a few pieces of advice from a sophomore who spent half of last year in Athens, (and if you’re an incoming freshman, here’s some information you should know.)
Coronavirus
Before anything else is mentioned, I have to address the elephant in the room– or rather the air. The pandemic played a huge role in shaping my freshman and now sophomore year.
 All of my courses were online but I still was able to make the best of it because I had a semblance of the ‘’college experience’’ of living in the dorms and living in a small college town.
My few words of wisdom essentially come down to keeping yourself safe and making sure you’re surrounding yourself with people you know who take the virus seriously. I jumped on the opportunity last April to get vaccinated because I knew I was not only protecting myself, but also my friends and family.
At first, like any campus, there were a lot of people who weren’t taking the virus seriously. This worried me until I realized how much effort Athens and OU put into making sure students were staying safe and not getting sick.
To any incoming students and sophomores, I’m urging you to get vaccinated. If you can do that, we can get closer to normal operations and have a true college experience together.
Athens/Campus
There is so much to unpack in terms of Athens and campus life. My favorite part of Athens is the easy access to many beautiful parks and trails to explore. I encourage taking a few trips to parks nearby.
I also recommend spending your weekends unwinding and seeing a movie at the Athena Grand on State Street, or better yet, walk up Court Street and go to the Athena Cinema where you can watch more independent films.
If you’ve become sick of the dining hall food (I know I did after a while), don’t forget to check out the numerous types of cuisine that Athens has to offer. These would range from: sushi at Ginger Kitchen, Mexican at Casa Nueva, Indian at Star of India and wings at Wings Over to name a few.
Social Life
As sophomores, we made most of our friends last year either back home or on the internet. When I came to Athens last spring, I tried to make the most of my situation and met as many people as I could. I joined clubs and organizations and made my goal to put myself out there.
As I urged the freshmen last year, I’m now urging sophomores to enjoy their time at OU and make the most of it. Get connected, reach out and don’t be afraid to have fun. There’s just about every club you can imagine here on campus and student organizations that will help you in your career field.
There’s also tons of Greek life with numerous fraternities and sororities that thrive on brother and sisterhood and strive for excellence.
Regardless of the advice that can be given or taken, this year is all about connecting with our fellow bobcats, making up for lost time and continuing our education. This year will be a great one for us as we look forward to what is to come.
Tre Spencer is a sophomore studying photojournalism at Ohio University. Please note that the views and opinions of the columnists do not reflect those of The Post. Want to talk more about it? Let Tre know by tweeting him @trerspencer1.


Abyssal Saintess Elcadia:
Alright. Time to see what you are made of, adventurer. Defeat the monsters I have prepared for you, and I'll know there's more to you than just a pretty face.


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Generic stream formatted print implementation. More...
#include <util.h>
#include <string.h>
#include <stream.h>
#include <compiler.h>
Go to the source code of this file.
Data Structures | |
| struct | string_stream |
| string stream object to convert from a string buffer to a struct stream object. More... | |
Defines | |
| #define | BUFFER_STREAM_BUFFER_SIZE 32 |
| Internal string stream buffer. | |
Functions | |
| static struct string_stream * | string_stream_of (struct stream *s) |
| Return the buffer stream containing the stream s. | |
| static void | snprintf_stream_commit (struct stream *s) |
| static void | sprintf_stream_commit (struct stream *s) |
| static bool | string_stream_make_room (struct stream *s, unsigned int goal) |
| int | snprintf (char *str, size_t size, const char *format,...) |
| Streamed formatted size limited output conversion. | |
| int | sprintf (char *str, const char *format,...) |
| Streamed formatted output conversion. |
Generic stream formatted print implementation.
Copyright (C) 2010 Atmel Corporation. All rights reserved.
Definition in file stream_string.c.
| #define BUFFER_STREAM_BUFFER_SIZE 32 |
Internal string stream buffer.
For internal use only.
Definition at line 47 of file stream_string.c.
Referenced by snprintf(), and sprintf().
| int snprintf | ( | char * | str, | |
| size_t | size, | |||
| const char * | format, | |||
| ... | ||||
| ) |
Streamed formatted size limited output conversion.
This is simply a convenience wrapper around stream_printf(), which will translate a character buffer in memory into a stream object. It will at most write size bytes to the str buffer from the format stream, and it does also take a variable number of arguments.
Definition at line 152 of file stream_string.c.
References string_stream::buffer, BUFFER_STREAM_BUFFER_SIZE, stream::data, memset(), string_stream::offset, string_stream::stream, and stream_vprintf().
Referenced by sub_frame_draw_handler().
| static void snprintf_stream_commit | ( | struct stream * | s | ) | [static] |
For internal use only.
Definition at line 80 of file stream_string.c.
References string_stream::offset, string_stream::size, stream_buf_extract_char(), stream_buf_has_data(), string_stream::string, and string_stream_of().
| int sprintf | ( | char * | str, | |
| const char * | format, | |||
| ... | ||||
| ) |
Streamed formatted output conversion.
This is simply a convenience wrapper around stream_printf(), which will translate a character buffer in memory into a stream object. It will write to the str buffer from the format stream until it reaches the null byte terminator, hence the user must be careful to avoid buffer overflow. It does also take a variable number of arguments.
Definition at line 196 of file stream_string.c.
References string_stream::buffer, BUFFER_STREAM_BUFFER_SIZE, stream::data, memset(), string_stream::offset, string_stream::stream, and stream_vprintf().
| static void sprintf_stream_commit | ( | struct stream * | s | ) | [static] |
For internal use only.
Definition at line 111 of file stream_string.c.
References string_stream::offset, stream_buf_extract_char(), stream_buf_has_data(), string_stream::string, and string_stream_of().
| static bool string_stream_make_room | ( | struct stream * | s, | |
| unsigned int | goal | |||
| ) | [static] |
For internal use only.
Definition at line 128 of file stream_string.c.
References stream_ops::commit, and stream::ops.
| static struct string_stream* string_stream_of | ( | struct stream * | s | ) | [static, read] |
Return the buffer stream containing the stream s.
For internal use only.
Definition at line 71 of file stream_string.c.
References container_of.
Referenced by snprintf_stream_commit(), and sprintf_stream_commit().


Bounty Bay is being remodelled (Spring/Summer 2009), armouring to strengthen the jetty, as well as widening and deepening. Extensive wind and wave data have shown that a breakwater would not increase landing capacity or safety significantly enough to make it economically viable. The governement are looking at the possibility of an alternate landing facility at the other side of the Island, however this will be a long way off.
All projects on Pitcairn are covered by an environmental impact assessment and the government want to ensure that nothing is changed that make Pitcairn special or attractive as a tourist destination.
See formalities on the main Pitcairn Island page.
Pitcairn is rugged, and its coast lined by cliffs for nearly the whole of the island. Nowhere giving easy access to the sea. Although the canoes can be launched in many places, Bounty Bay and the Tedside landing are the only two places on the island that offer a reasonably safe landing. It is only possible to land at Tedside when winds are easterly and no swell from southwest.
Anchoring in Bounty Bay should be just to seaward of a line between the tree on Adams Rock and Isaacs Rocks. This will put you on sand in about 11 to 14m, about 350m from the landing.
Burned on 23 January 1790, the remains of Bounty lie 3m below the surface of Bounty Bay. Although tourists are allowed to dive on the wreck, sadly, over the years, Bounty relics have disappeared from the site and today there is very little left.
Last updated August 2014.


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What is mruby
mruby is the lightweight implementation of the Ruby language complying to (part of) the ISO standard. Its syntax is Ruby 2.x compatible.
mruby can be linked and embedded within your application. We provide the interpreter program “mruby” and the interactive mruby shell “mirb” as examples. You can also compile Ruby programs into compiled byte code using the mruby compiler “mrbc”. All those tools reside in the “bin” directory. “mrbc” is also able to generate compiled byte code in a C source file, see the “mrbtest” program under the “test” directory for an example.
This achievement was sponsored by the Regional Innovation Creation R&D Programs of the Ministry of Economy, Trade and Industry of Japan.
How to get mruby
The stable version 2.1.0 of mruby can be downloaded via the following URL: https://github.com/mruby/mruby/archive/2.1.0.zip
The latest development version of mruby can be downloaded via the following URL: https://github.com/mruby/mruby/zipball/master
The trunk of the mruby source tree can be checked out with the following command:
$ git clone https://github.com/mruby/mruby.git
You can also install and compile mruby using ruby-install, ruby-build or rvm.
mruby home-page
The URL of the mruby home-page is: http://www.mruby.org.
Mailing list
We don’t have a mailing list, but you can use GitHub issues.
How to compile and install (mruby and gems)
See the compile.md file.
Running Tests
To run the tests, execute the following from the project’s root directory.
$ make test
Or
$ ruby ./minirake test
Building documentation
There are two sets of documentation in mruby: the mruby API (generated by yard) and C API (Doxygen)
To build both of them, simply go
rake doc
You can also view them in your browser
rake view_api
rake view_capi
How to customize mruby (mrbgems)
mruby contains a package manager called mrbgems. To create extensions in C and/or Ruby you should create a GEM. For a documentation of how to use mrbgems consult the file mrbgems.md. For example code of how to use mrbgems look into the folder examples/mrbgems/.
License
mruby is released under the MIT License.
Note for License
mruby has chosen a MIT License due to its permissive license allowing developers to target various environments such as embedded systems. However, the license requires the display of the copyright notice and license information in manuals for instance. Doing so for big projects can be complicated or troublesome. This is why mruby has decided to display “mruby developers” as the copyright name to make it simple conventionally. In the future, mruby might ask you to distribute your new code (that you will commit,) under the MIT License as a member of “mruby developers” but contributors will keep their copyright. (We did not intend for contributors to transfer or waive their copyrights, Actual copyright holder name (contributors) will be listed in the AUTHORS file.)
Please ask us if you want to distribute your code under another license.
How to Contribute
See the contribution guidelines, and then send a pull request to http://github.com/mruby/mruby. We consider you have granted non-exclusive right to your contributed code under MIT license. If you want to be named as one of mruby developers, please include an update to the AUTHORS file in your pull request.


Public Art Hong Kong (PAHK) is a non-profit organization funded by the Y.K.Pao Foundation with an aim to nurture and promote public art in Hong Kong. It was incorporated in 2005 with the Hong Kong Arts Centre as its executing organization. PAHK wishes to create an interactive relationship among the artwork, site and audience and intends to reflect public interests while featuring Hong Kong as a vibrant cultural city.
Ms. Cissy Pao, BBS (Chairperson)
Ms. Candy Chuang
The Hon Christopher Chung Shu-kun, BBS, MH, JP
Ms. Jennifer Dong
Mr. Andre Fu
Mr. Keith Kerr, SBS, JP
Mr. Y.S. Daniel Lai
Ms. Shelley Lee Lai-kuen, GBS, OBE, JP
Dr. Michael W T Ng
Dr. Dennis Sun, BBS, JP
Ms. Angela Tam
Our consultants are experts in creating distinctive projects with you from start to finish, bringing art into your space, promoting public art in a diversified form.
We work closely with emerging artists in Hong Kong. Our consultants select original artworks based on your preference, coordinating the selection, acquisition, and installation of the artwork.
We enable you to experience the excitement of bringing an art concept to life. Our consultants work with you to commission artists to create an artwork that interact visually with the environment of your space as well as your vision.
Art education is important to us. Together with our partner we offer specially designed free docent tours for you to enjoy the artistic journey and behind-the-scene stories at the Hong Kong Arts Centre.
We enjoy breathing life to public space and bring people of the community together; proactively, we commission talented artist to create new art for our space and interesting spaces in Hong Kong.
It’s the insight, knowledge together with experience that give us the expertise in curating public art project that speak to the people and resonate with the contemporary.


They are fun to watch
Check out the Otter Cam!


class Builder : TextStatementBuilder<Key>
A builder for a DeleteStatement. See Database.deleteFrom.
<init> |
A builder for a DeleteStatement. See Database.deleteFrom. Builder(db: Database, table: Table) |
getReusable |
Gives a reference to a reusable statement object. This allows clients to avoid the (small) lookup overhead for a frequently-used delete statement. fun getReusable(): ReusableDeleteStatement |
run |
Run setBody to set any needed Parameter values on the delete statement, then execute the statement. See Database.deleteFrom. infix fun run(setBody: (DeleteStatement) -> Unit): Int |


Visit Ant - Doxygen task home here.
Version 1.6.1
Doxygen
Description
This task is a wrapper
for the configuration options for doxygen, a document generation-tool. To know
more about doxygen in the words of the author himself -
" Doxygen is a documentation
system for C++, C, Java, IDL (Corba, Microsoft, and KDE-DCOP flavors) and to
some extend PHP.
- It can generate an
on-line documentation browser (in HTML) and/or an off-line reference manual
from a set of documented source files. There is also support for generating
output in RTF (MS-Word), PostScript, hyperlinked PDF, compressed HTML, and
Unix man pages. The documentation is extracted directly from the sources,
which makes it much easier to keep the documentation consistent with the source
code.
- Doxygen can be configured
to extract the code structure from undocumented source files. This can be
very useful to quickly find your way in large source distributions. The relations
between the various elements are be visualized by means of include dependency
graphs, inheritance diagrams, and collaboration diagrams, which are all generated
automatically."
Visit doxygen software home here.
Parameters
doxygen task does not take any attribute. But it takes 'property' child nodes as attribute. The structure of 'property' node is as follows:
<property name="<doxygen_property_name>" value="<property_value>" />
The field 'doxygen_property_name' corresponds to the property defined as per the doxygen configuration file. Please see the following examples to get a better idea of the same.
Examples:
1. To generate documentation
by default in current directory, basic option.
- Ant 1.7+:
<project name="my-project" xmlns:doxygen="antlib:org.doxygen.tools" .... />
<doxygen:doxygen>
<property name="INPUT" value="${inputdir}" />
</doxygen:doxygen>
or
<taskdef name="doxygen" classname="org.doxygen.tools.DoxygenTask"
classpath="${destdir}" />
<doxygen>
<property name="INPUT" value="${inputdir}" />
</doxygen>
2. To generate html documentation
recursively for a given dir. and suppress latex documentation
- Ant 1.7+:
<project name="my-project" xmlns:doxygen="antlib:org.doxygen.tools" .... />
<doxygen:doxygen>
<property name="INPUT" value="${inputdir}" />
<property name="RECURSIVE" value="yes" />
<property name="GENERATE_LATEX" value="false" />
<property name="PROJECT_NAME" value="Ant-Doxygen Test Docs" />
<property name="GENERATE_TREEVIEW" value="yes" />
<property name="SOURCE_BROWSER" value="yes" />
</doxygen:doxygen>
or
-
<taskdef name="doxygen" classname="org.doxygen.tools.DoxygenTask"
classpath="${destdir}" />
<doxygen>
<property name="INPUT" value="${inputdir}" />
<property name="RECURSIVE" value="yes" />
<property name="GENERATE_LATEX" value="false" />
<property name="PROJECT_NAME" value="Ant-Doxygen Test Docs" />
<property name="GENERATE_TREEVIEW" value="yes" />
<property name="SOURCE_BROWSER" value="yes" />
</doxygen>


Plant Journal!
Plant Name:
Select your plant type:
Succulent
Cactus
Flower
Fern
Select the day of planting:
Did you water this plant today?
Yes
No
Add your plant!
Plant List


| Command |
Discription |
Usage |
| lock |
Locks a channel from normal users |
.lock |
|
| unlock |
Unlocks a channel from normal users |
.unlock |
|
| report |
Allows you to report users for a reason (only if setup by server admins use .reportsetup in the channel for reports) |
.report {who} {reason} |
|
| serverinfo |
Show infomation about the server |
.serverinfo |
|
| resetmessages |
Delete's all messages in every channel |
.resetmessages |
|
| clearuser |
Delete's all messages sent by the given user in every channel |
.clearuser {user} |
|
| raw |
Show the raw data of a message |
.raw {data} |
|
| clear |
Allows you to clear a amount of messages in a channel |
.clear {ammount/user} |
|
| mute |
Allows you to mute a user |
.mute {user} |
|
| unmute |
Allows you to unmute a user |
.unmute {user} |
|
| kick |
Allows you to kick a user |
.kick {user} |
|
| ban |
Allows you to ban a user |
.ban {user} |
|
| reportsetup |
Allows staff to setup reporting for your server! type in the report log channel. |
.reportsetup |
|
| reportreply |
Allows server staff to respond to user reports |
.reportreply {target/sender} {message} {report_id} |
|
| report |
Allows you to report users for a reason (only if setup by server admins use .reportsetup in the channel for reports) |
.report {user} {reason} |
|
| play |
Play a song from youtube or resume a paused song |
.play {url/search} |
|
| pause |
Pause a playing song |
.pause |
|
| join |
Makes the bot join a channel or join the channel your in |
.join |
|
| leave |
Make the bot leave the channel its currently in |
.leave |
|
| stop |
Leave's the channel and clears the queue |
.stop |
|
| np |
Allows you to see the song the bot is currently playing |
.np |
|
| queue |
Allows you to see the queue |
.queue |
|
| skip |
Allows you to skip the current song |
.skip |
|
| translate |
Translate text to a diffrent langage |
.translate {country_code} {text_to_translate} |
|
| talk |
The bot will talk for you in a diffrent langage |
.talk {country_code} {text_to_say} |
|
| remove |
Removes any song form the queue |
.remove {song_number} |


Presentation@Uni in Bremen
December 5, 2007
Yesterday I gave my first presentation in english on geographical and urban economics. It was at the University of Bremen (Germany). Right now, I´m visiting my friend Fabian for a week, half of it in Hamburg and the other half one here in Bremen. Since he asked me to give such a speech, I couldn´t say no so I accepted and now I think it was a really good experience I should really be thankful to him about.
The presentation went in my view very well, it was in a very friendly environment and people even asked afterwards, which made me feel really fine. I hope it´s the first one of a long list of collaboration and co-work between Fabian and me from now on. Time will tell.
[You can check, download and use the presentation as long as you respect the CC license it is under, which basically imposes you to credit myseld whenever you use it, not to use it for a comercial purpose and to license everything you create from my presentation under the same or very close license. The .ppt is available in the downloads feature of this website, blue square on the left.]


Backgroud
The mobile phone will send a message to our server when an App is installed, in general, the message - called ‘activate log’ - contains some information, such as the timestamp the app installed, the name and version of the app, etc. In order to see publishes of upgrade or new versions are good or bad, we need to know how many users install the App.
The matter should be noticed is that a device should be caculated only once even if the same App is installed many times. Maybe a user re-install the same App after uninstalled it, we just need the message received at the first installation, and discard others - reduplicative activate log.
In general case, we get more than 200 thousand activates (both new installation and upgrade) just in the United States, at some special time, the number may exceed 1 million.
Previous Work
We have a non-real-time process platform, using Hadoop for caculation, HDFS for storage of log files, HBase for dropping-reduplication.
HBase1 has a natrual charater suitable to dropping-reduplication bacause each inserted data has a timestamp, each cell can store one or more records of multiple versions with different timestamps. The version with the maximal timestamp means that it is the latest inserted one, and we will get the letest version of each cell when we query Hbasei by default. In order to discard all the later activate log but store the first one, just guarantee the first log has the maximal timestamp, although the reduplicative records are inserted into HBase, we can also get the first log with maximal timestamp.
The official release of HBase has no method to insert data using custom timestamp, my collegue modified the source of HBaseStorage(org.apache.pig.backend.hadoop.hbase.HBaseStorage)
to support custom timestamp in Pig2, so we insert the first activate log with a maximal custom timestamp.
We insert daily activate log into HBase to discard reduplication, and dump it on HDFS, then start a Hadoop3 Streaming job to do a statistic.
Imporve
There are some factors that block us to realize real-time computing, Hadoop Streaming job has its drawback to real-time job, and HBase’s shell has limitations and so on.
Spark
Compare to traditional off-line batch job, Spark4 Streaming makes it easy to build scalable fault-tolerant streaming applications.
Internally, it works as follows. Spark Streaming receives live input data streams and divides the data into batches, which are then processed by the Spark engine to generate the final stream of results in batches.
You could select a specific interval for yourself, so Spark Streaming gets a small batch data and process on it which could improve the real-time ability.
Cassandra
Compare to the limitation of shell in HBase, Cassandra5 - another NoSql - provides a more convenient acess, that is Cql. Although Cql is not as strong as Sql of relational database, it has the basic CRUD, a.k.a. insert
/select
/update
/delete
in SQL, which make it much clearer and easier to handle with data.
bin/cqlsh is an interactive command line interface for Cassandra. cqlsh allows you to execute CQL (Cassandra Query Language) statements against Cassandra. Using CQL, you can define a schema, insert data, execute queries.
In additional, you could filter data in Cassandra server using select
statement, that is, computing system could just read the specific data, not a complete table, which make process more effective. And many advantages make of Cassandra lead it to be massively scalable.
Cassandra supplies linear scalability, meaning that capacity may be easily added simply by adding new nodes online. For example, if 2 nodes can handle 100,000 transactions per second, 4 nodes will support 200,000 transactions/sec and 8 nodes will tackle 400,000 transactions/sec:
Meanwhile, although the insert statement in Cassandra doesn’t check primary key confilcts like relational database in default, it supports write-time as the timestamp of each cell in HBase, record with a larger write-time will overwrite the smaller one.
INSERT INTO NerdMovies (movie, director, main_actor, year)
VALUES ('Serenity', 'Joss Whedon', 'Nathan Fillion', 2005)
USING TIMESTAMP 86400;
Kakfa
We receive many logs about activate and active and others every day, which are divided by some key words, then we sent the data we need to Kafka6 cluster. Also, messages in Kafka are divided by topics, that is, you could use any topic you want.
Apache Kafka is publish-subscribe messaging rethought as a distributed commit log.
Something may be confused is that whether the log would be discard after any consumer used it? No, Kafka sustains its messages until the date of this log file is over a threshold which you can set yourself or 7 days in default.
Results
The picture below shows the statitstics of Spark Streaming, as we can see, the input rate is around 9.11 events/sec that means there are more than 9 messages read from the Kafka cluster averagely. In brief, our processing contains parse, formation and insertion on every log, and the job process on a small batch data every 10 senconds, the processing time of a batch is around 81ms.
Then, we start another job every minute to query the data newly inserted into Cassnadra and do a statistic. So we can know how many new users install our App and how many old users upgrade our App in time because our results are freshed every minute.
We can also use this framework to calculate DAU, a.k.a daily active user in real time.
(END)


Chose a link target:
The link target is only considered at render time. So this demo forces a reload when you chose a different option.
There are several kinds of links:
By default, external links are opened in the same window. In other words, clicking the link amounts to leaving the Angular application. To prevent this, you have two options:
defaultOptions
to override the default for externalLinkTarget
.
You can manipulate links using the pageRendered
event. This demo deactivates
the links. Note you can't modify the appearance of the links. They are part of the PDF file,
so they can't be displayed differently. But you can modify the invisible annotation layer.


Reports availability of stub packages.
Stub package is a package that contains type information for the corresponding runtime package.
Using stub packages ensures better coding assistance for the corresponding python package.


3 Descriptives and Visualizations Study 1
3.1 Overview
In this section, I describe and visualize the sample and variables.
We have variables on the meta-level (about the survey), the person-level, the app-level, and the day-level.
App-level data is in the apps_long
data file; all other in the study1
data file.
Meta-level
- Duration of the entry survey, when participants reported traits (
duration_personality
) - Duration of the exit survey, when participants reported their screen time (
duration_screen_time
)
Person-level
- Participant identifier (
id
) age
in yearsethnicity
- Notifications of social media apps over the past week (
weekly_notifications
) - Basic Psychological Need Satisfaction (
autonomy_trait
,competence_trait
,relatedness_trait
) plus their individual items (starting withbpns_
) - Big Five (
extraversion
,agreeableness
,conscientiousness
,neuroticsim
,openness
) plus their individual items (starting withbig_five_
)
App-level
- What app participants report use for (
app
) - On what rank was that app on participants’ top ten (
rank
) - Notifications for that app for the week (
notifications_per_week
) - Pickups for that app on that day (
pickups
) - Screen time for that app on that day (
social_media_objective
)
Day-level
- Duration of the survey on that day (
duration_diary
) day
the survey was answered- Estimated time on social media on that day (
social_media_subjective
) - Estimated pickups of social media apps on that day (
pickups_subjective
) - Estimated notifications of social media apps on that day (
notifications_subjective
) - Objective time on social media on that day (
social_media_objective
) - Objective pickups of social media apps on that day (
pickups_objective
) - Well-being on that day (
well_being
) plus its individual items (starting withlow_
andhigh_
) - Basic psychological needs on that day (
autonomy_state
,competence_state
,relatedness_state
) plus their individual items (starting withautonomy_
,competence_
,relatedness_
respectively) - Experiences of satisfaction, boredom, stress, enjoyment on that day (
satisfied
,boring
,stressful
,enoyable
)
3.2 Meta-level
I begin with describing and plotting the duration of the entry and exit surveys. Table 3.1 shows descriptive stats; Figure 3.1 shows that twp participants had their entry surveys open for a day before pressing send, which skews the mean massively. However, those people’s data look good, so I wouldn’t exclude them here. Note: Colors are from here.
| variable | mean | sd | median | min | max | range | cilow | cihigh |
|---|---|---|---|---|---|---|---|---|
| duration_personality | 1H 5M 56S | 4H 36M 55S | 15M 40S | 1M 22S | 1d 9H 33M 36S | 1d 9H 32M 14S | 9M 50S | 2H 2M 3S |
| duration_screen_time | 20M 21S | 20M 8S | 13M 18S | 1M 8S | 1H 51M 29S | 1H 50M 21S | 16M 17S | 24M 26S |
3.3 Person-level
Let’s have a look at the final sample. Overall, our sample size is N = 96. The sample has a mean age of M = 20, SD = 1. The sample consists mostly of women (66 women, 30 men, and one non-binary participant).
Most participants are Asian, followed by White, Black, and Hispanic, see Table 3.2
| ethnicity | count | percent |
|---|---|---|
| Asian | 40 | 42 |
| White | 26 | 27 |
| Black or African American | 11 | 11 |
| Hispanic or Latino | 10 | 10 |
| Multiracial | 6 | 6 |
| NA | 2 | 2 |
| Native Hawaiian or Other Pacific Islander | 1 | 1 |
Alright, next we look at the objective count of notifications over the past week, aggregated across all apps. Table 3.3 shows that participants received quite a lot of notifications from social media apps only. That distribution is heavily skewed (Figure 3.2 by a couple of participants who received several thousand notifications over the week.
| variable | mean | sd | median | min | max | range | cilow | cihigh |
|---|---|---|---|---|---|---|---|---|
| weekly_notifications | 997.6354 | 673.4178 | 868.5 | 126 | 3382 | 3256 | 861.1883 | 1134.083 |
Now we look at the trait variables: the basic psychological need satisfaction and the big five. Note that I follow recent recommendations and calculate \(\omega\) for reliability. Table 3.4 shows the descriptive information of the three psychological needs and the big five. Figure 3.3 shows their distribution. The sample isn’t too large, so considering the small size, I’d say everything looks pretty good.
| variable | mean | sd | median | min | max | range | cilow | cihigh | omega |
|---|---|---|---|---|---|---|---|---|---|
| autonomy_trait | 4.51 | 0.88 | 4.50 | 1.25 | 6.88 | 5.62 | 4.33 | 4.68 | 0.82 |
| competence_trait | 5.16 | 0.70 | 5.31 | 3.50 | 6.50 | 3.00 | 5.01 | 5.30 | 0.75 |
| relatedness_trait | 4.54 | 1.03 | 4.56 | 2.38 | 6.62 | 4.25 | 4.33 | 4.75 | 0.88 |
| extraversion | 3.13 | 0.74 | 3.00 | 1.62 | 5.00 | 3.38 | 2.98 | 3.29 | 0.86 |
| agreeableness | 3.68 | 0.56 | 3.59 | 2.33 | 5.00 | 2.67 | 3.57 | 3.80 | 0.75 |
| conscientiousness | 3.50 | 0.58 | 3.50 | 2.00 | 4.89 | 2.89 | 3.39 | 3.62 | 0.75 |
| neuroticism | 3.29 | 0.50 | 3.38 | 2.00 | 4.38 | 2.38 | 3.19 | 3.39 | 0.59 |
| openness | 3.54 | 0.48 | 3.60 | 2.10 | 4.80 | 2.70 | 3.45 | 3.64 | 0.66 |
lm
lines goes to data prone, whose idea I adapted.
3.4 App-level
First, Figure 3.5 shows what apps mostly nominated (i.e., used). We see that out of the sample, most participants had Messaging, Snapchat, Whatsapp etc. as part of their top ten.social_media_objective
that have NA
.
The NA
here can mean participants just didn’t fill in anything, or they had zero duration on that day.
Because adding up the raw scores across apps was so close to the daily total, I’ll exclude NA
s here.
3.5 Day level
Alright, we’re at the most interesting section, the daily surveys. I first look at how long people typically took for a survey. Table 3.5 shows that the mean is highly skewed because of outliers and the median more appropriate to describe the duration. In Figure 3.9 we see that a couple of people took a long time from opening to submitting the survey. I checked those participants who took a long time in the data processing section. The maximum duration here from someone who didn’t open the survey on a Friday. So that duration is just the survey closing automatically after two days, which really drives up the mean.
| variable | mean | sd | median | min | max | range | cilow | cihigh |
|---|---|---|---|---|---|---|---|---|
| duration_diary | 50M 22S | 2H 44M 17S | 16M 0S | 25S | 2d 0H 27M 48S | 2d 0H 27M 23S | 35M 5S | 1H 5M 40S |
Alright, next I inspect overall response rate in the final sample, aka how many valid surveys do we have among the final sample. Each participant received five surveys, one for each day, so 96 participants x 5 = 480. We have 435 surveys in the final sample where participants actually responded, which means a 91% response rate among the final sample.
Let’s inspect response rate per day. As is to be expected, participants lost motivation over the course of the week. However, even the response rate on Friday is really high (at least among our sample of valid responses). We should still consider to take the day grouping into account when modelling the data later in the analysis.Next, I describe and plot the distributions of the social media use variables. The distribution and CI is of the entire sample, not aggregated by participant or day first. Table 3.6 shows that participants weren’t too far off in their estimates, which is interesting. As expected (Figure 3.11), the social media variables are a bit skewed, but overall, they look fine.
| variable | mean | sd | median | min | max | range | cilow | cihigh |
|---|---|---|---|---|---|---|---|---|
| social_media_subjective | 153 | 112 | 130 | 5 | 692 | 687 | 143 | 164 |
| social_media_objective | 139 | 94 | 118 | 2 | 565 | 563 | 130 | 148 |
| error | 46 | 156 | -3 | -96 | 1186 | 1282 | 31 | 61 |
| pickups_subjective | 34 | 43 | 17 | 0 | 259 | 259 | 30 | 38 |
| pickups_objective | 49 | 31 | 44 | 0 | 196 | 196 | 46 | 52 |
| notifications_subjective | 61 | 99 | 30 | 0 | 700 | 700 | 52 | 71 |
Now let’s look at the state well-being and psychological needs variables plus the four experiences (e.g., boring
).
Again, I calculate \(\omega\), but this time for the entire sample in Table 3.7.
That will necessarily bias the estimate because there’s multiple measures per person.
I’m not aware of a consensus reliability procedure for repeated measures.
Figure 3.13 shows that the data look pretty good.
| variable | mean | sd | median | min | max | range | cilow | cihigh | omega |
|---|---|---|---|---|---|---|---|---|---|
| well_being_state | 3.23 | 0.70 | 3.17 | 1.25 | 5 | 3.75 | 3.17 | 3.30 | 0.85 |
| autonomy_state | 4.50 | 1.16 | 4.25 | 1.00 | 7 | 6.00 | 4.39 | 4.60 | 0.69 |
| competence_state | 4.60 | 1.27 | 4.50 | 1.00 | 7 | 6.00 | 4.48 | 4.72 | 0.79 |
| relatedness_state | 5.33 | 1.07 | 5.50 | 2.50 | 7 | 4.50 | 5.23 | 5.43 | 0.70 |
| satisfied | 4.61 | 1.33 | 5.00 | 1.00 | 7 | 6.00 | 4.49 | 4.74 | NA |
| boring | 3.40 | 1.55 | 3.00 | 1.00 | 7 | 6.00 | 3.25 | 3.55 | NA |
| stressful | 3.96 | 1.81 | 4.00 | 1.00 | 7 | 6.00 | 3.79 | 4.13 | NA |
| enjoyable | 4.27 | 1.41 | 4.00 | 1.00 | 7 | 6.00 | 4.14 | 4.40 | NA |
3.6 Plots for paper
Here, I’ll create summary figures for the paper. I’ll begin with plotting the traits.
For the plot, the data need to be in the long format.
<-
dat %>%
study1 group_by(id) %>%
slice(1) %>%
ungroup() %>%
select(all_of(c("id", trait_descriptives$variable))) %>%
pivot_longer(
-id,
names_to = "variable",
values_to = "value"
)
<- c(
rename_levels "Autonomy",
"Competence",
"Relatedness",
"Agreeableness",
"Conscientiousness",
"Extraversion",
"Neuroticism",
"Openness"
)
<- "_trait"
my_string
# reorder and rename factor levels
<-
clean_plot_data function(
dat,
levels_to_rename,
string_to_remove
){<-
dat %>%
dat mutate(
# in case it's social media variables
variable = case_when(
== "social_media_objective" ~ "Objective (h)",
variable == "social_media_subjective" ~ "Subjective (h)",
variable == "error" ~ "Accuracy (%)",
variable TRUE ~ variable
),# remove _trait at the end and capitalize
variable = str_to_sentence(str_remove(variable, string_to_remove)),
variable = as.factor(variable),
variable = str_replace(variable, "_", "-"),
# reorder factor levels
variable = fct_relevel(
variable,
levels_to_rename
)
)return(dat)
}
<- clean_plot_data(dat, rename_levels, my_string)
dat <- clean_plot_data(trait_descriptives, rename_levels, my_string) trait_descriptives
Okay, we already have the aggregated info in trait_descriptives
, so we can get to plotting.
# function for breaks
<-
my_breaks function(x) {
if (max(x) > 5){
1:7
else {
} 1:5
}
}
# function for limits
<-
my_limits function(x) {
if (max(x) > 5){
c(1,7)
else {
} c(1,5)
}
}
# color palette
<- c("#000000", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
cb_palette
# plot
ggplot(
dat,aes(
x = value,
y = 1,
color = variable,
fill = variable
)+
) geom_quasirandom(groupOnX=FALSE, size = 0.3, alpha = 0.5) +
facet_wrap(
~ variable,
scales = "free_x"
+
) scale_x_continuous(breaks = my_breaks, limits = my_limits) +
geom_text(
data = trait_descriptives,
aes(
x = 1.6,
y = 1.4,
label = paste0("M = ", mean),
family = "Corbel"
),size = 2.5,
color = "black"
+
) geom_text(
data = trait_descriptives,
aes(
x = 1.6,
y = 1.3,
label = paste0("SD = ", sd),
family = "Corbel"
),size = 2.5,
color = "black"
+
) geom_text(
data = trait_descriptives,
aes(
x = 1.6,
y = 1.2,
label = paste0("\u03a9 = ", omega),
family = "Corbel"
),size = 2.5,
color = "black"
+
) theme_cowplot() +
scale_colour_manual(values=cb_palette) +
scale_fill_manual(values = cb_palette) +
theme(
axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.line.y = element_blank(),
strip.background.x = element_blank(),
strip.background.y = element_blank(),
legend.position = "none",
text = element_text(family = "Corbel")
-> figure1
)
figure1
ggsave(
here("figures", "figure1.tiff"),
plot = figure1,
width = 21 * 0.8,
height = 29.7 * 0.4,
units = "cm",
dpi = 300
)
Okay, next the state variables.
<-
dat %>%
study1 select(all_of(c("id", state_descriptives$variable))) %>%
pivot_longer(
-id,
names_to = "variable",
values_to = "value"
)
<- c(
rename_levels "Autonomy",
"Competence",
"Relatedness",
"Boring",
"Enjoyable",
"Satisfied",
"Stressful",
"Well-being"
)
<- "_state"
my_string
<- clean_plot_data(dat, rename_levels, my_string)
dat <- clean_plot_data(state_descriptives, rename_levels, my_string) state_descriptives
Then to plotting.
# plot
ggplot(
dat,aes(
x = value,
y = 1,
color = variable,
fill = variable
)+
) geom_quasirandom(groupOnX=FALSE, size = 0.1, alpha = 0.5) +
facet_wrap(
~ variable,
scales = "free_x"
+
) scale_x_continuous(breaks = my_breaks, limits = my_limits) +
geom_text(
data = state_descriptives,
aes(
x = 1.6,
y = 1.4,
label = paste0("M = ", mean),
family = "Corbel"
),size = 2.5,
color = "black"
+
) geom_text(
data = state_descriptives,
aes(
x = 1.6,
y = 1.3,
label = paste0("SD = ", sd),
family = "Corbel"
),size = 2.5,
color = "black"
+
) geom_text(
data = state_descriptives,
aes(
x = 1.6,
y = 1.2,
label = paste0("\u03a9 = ", omega),
family = "Corbel"
),size = 2.5,
color = "black",
alpha = if_else(is.na(state_descriptives$omega), 0, 1) # one-item measure don't have omega, so I make those see through
+
) theme_cowplot() +
scale_colour_manual(values=cb_palette) +
scale_fill_manual(values = cb_palette) +
theme(
axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.line.y = element_blank(),
strip.background.x = element_blank(),
strip.background.y = element_blank(),
legend.position = "none",
text = element_text(family = "Corbel")
-> figure2
)
figure2
ggsave(
here("figures", "figure2.tiff"),
plot = figure2,
width = 21 * 0.8,
height = 29.7 * 0.4,
units = "cm",
dpi = 300
)
Alright, last the smartphone use variables.
<-
dat %>%
study1 select(all_of(c("id", "social_media_objective", "social_media_subjective", "error"))) %>%
# turn to hours
mutate(
across(
contains("social_media"),
~ .x /60
)%>%
) pivot_longer(
-id,
names_to = "variable",
values_to = "value"
)
<- c(
rename_levels "Objective (h)",
"Subjective (h)",
"Accuracy (%)"
)
<- "_state"
my_string
<- clean_plot_data(dat, rename_levels, my_string)
dat <- clean_plot_data(social_media, rename_levels, my_string) %>%
social_media2 filter(variable %in% c("Objective (h)", "Subjective (h)", "Accuracy (%)")) %>%
# add x axis position for geom_text
mutate(
x_position = case_when(
== "Accuracy (%)" ~ 1200*0.8,
variable TRUE ~ 0.8*13
) )
And the plot.
# function for breaks
<-
my_breaks function(x) {
if (max(x) < 100){
seq(0, 13, 2)
else {
} c(-200, 0, 400, 800, 1200)
}
}
# function for limits
<-
my_limits function(x) {
if (max(x) < 100){
c(0, 13)
else {
} c(-200, 1200)
}
}
# plot
ggplot(
dat,aes(
x = value,
y = 1,
color = variable,
fill = variable
)+
) geom_quasirandom(groupOnX=FALSE, size = 0.2, alpha = 0.5) +
facet_wrap(
~ variable,
scales = "free_x"
+
) scale_x_continuous(breaks = my_breaks, limits = my_limits) +
geom_text(
data = social_media2,
aes(
x = x_position,
y = 0.7,
label = paste0("M = ", mean),
family = "Corbel"
),size = 3,
color = "black"
+
) geom_text(
data = social_media2,
aes(
x = x_position,
y = 0.67,
label = paste0("SD = ", sd),
family = "Corbel"
),size = 3,
color = "black"
+
) theme_cowplot() +
scale_colour_manual(values=cb_palette) +
scale_fill_manual(values = cb_palette) +
theme(
axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.line.y = element_blank(),
strip.background.x = element_blank(),
strip.background.y = element_blank(),
legend.position = "none",
text = element_text(family = "Corbel")
-> figure3
)
figure3
ggsave(
here("figures", "figure3.tiff"),
plot = figure3,
width = 21 * 0.8,
height = 29.7 * 0.4,
units = "cm",
dpi = 300
)


Gateway
BOT
23-Aug-18 12:08 PM
[dscrdeql] <MySoulisNotForSale> @AndronicusBass-Founder awww, I thought maybe they felt bad for what they did to the aboriginies and needed some time to say sorry
[dscrdeql] <Combat Wom-mod> said sorry enough in my opinion
[dscrdeql] <Combat Wom-mod>
[dscrdeql] <MySoulisNotForSale> ^^^ lol
[dscrdeql] <AndronicusBass-Founder> They already did in 2007
[dscrdeql] <MySoulisNotForSale> I wonder about you sometimes henry. . "you may fold under questioning"
[dscrdeql] <Combat Wom-mod> also i am not saying sorry.. i didn't do nothing
[dscrdeql] <Jellysmash> more political shenanigans
[dscrdeql] <Combat Wom-mod> i dunno what thats from mysoul lol prob some movie?
[dscrdeql] <MySoulisNotForSale> yes. . "goodfellas"
[dscrdeql] <MySoulisNotForSale> one of the best lines in the movie
[dscrdeql] <Combat Wom-mod> ahhhhh
[dscrdeql] <Jellysmash> they do go on and on a bit in Canberra
[dscrdeql] <Combat Wom-mod>
[dscrdeql] <Combat Wom-mod> they are a joke jelly
[dscrdeql] <Jellysmash> just wish they'd get on with their jobs
[dscrdeql] <MySoulisNotForSale> Henry get's "pinched" for selling stolen cigeretts. .
[dscrdeql] <Combat Wom-mod> yes i remember that but he doesn't snitch
[dscrdeql] <MySoulisNotForSale> yep
[dscrdeql] <Combat Wom-mod> @Jellysmash yeah that would be the day... politicians doing their job lol
[dscrdeql] <MySoulisNotForSale> they do their job everyday. . IE , stealing our money
[dscrdeql] <AndronicusBass-Founder> They milk negative gearing for all its worth in their personal investment properties


Symbol Index for "Subject Location"
Symbol Index for diagram
"Subject Location"
classifier (Association)
end for (Association)
Inter Subject Relationship (Class)
Involvement In Incident (Class)
Location (Class)
location for (Association)
SPr/Association (Generalization Node)
start for (Association)
Subject Characteristic (Class)
Subject Location (Class)
Subject Location Type (Class)
Subject Property (Class)
Timepoint (Class)


Command line API: cd
This test-case is intended for command line cd method.
Jan Odvarko<EMAIL_ADDRESS>- Open Firebug and enable the Console panel.
- Execute following expressions in the command line and check the results
'expression' -> 'result'
cd(frames[0]) -> "Current window:", Window cdFrame.html]
$("#test-iframe-1") -> <div id="test-iframe-1">
cd(top) -> ["Current window:", Window cd.html]
cd(undefined) -> Error: Object must be a window.
Special case to test: Focus the command line and reload the window
by pressing F5 key (the command line should be still focused after reload).
Now write cd(frames[0]) into it and press
enter (make sure the command line doesn't lose the focus).
Logged Current window should not be undefined.


View the source for this page for instructions on how to get started.
You may find the following resources helpful:


THE QUEUE
Noah Niesen
Marketing Page Developer
Implemented UI
Worked with GIT
Implemented Responsive Design
Worked with the LESS Pre-Processor
Furno West
Marketing Page Developer
Implemented UI
Worked with GIT
Implemented Responsive Design
Worked with the LESS Pre-Processor
Milosz Samec
React I Developer
Requested networks for reading data
Obtained information from an API
Implemented industry standards while architecting and developing
Darrell Conkinn
React II Developer
Developed the state management system
Handled HTTP requests for CRUD methods
Implemented client-side authentication
Germaine Pannell
Backend Developer
Developed the API that provided the endpoints for the frontend developers using the REST architectural pattern


Susan Granger's review of "BRIDE OF CHUCKY"
If you're a horror film buff, you'll recall Chucky, the supernatural doll with the soul of a serial killer, who came to life in "Child's Play" (1988) and slashed his way through two subsequent sequels. Now, he's back! But with a difference. Like "Scream" and "I Know What You Did Last Summer," this Chucky tale, written by Don Mancini, is an irreverent satire of the horror genre, aimed directly at the teenage crowd. David Kirschner, the producer, states his purpose succinctly: "We worked hard to get an R-rating because, if you're not R-rated, you lose your 16, 17, and 18 year-old crowd. They want to see the excitement, the chases, and the kill so, basically, this is kind of a psychotic muppet movie." Which isn't too surprising since Kirschner began his career as an illustrator for Jim Henson, creator of the Muppets. In this story, Chucky (a.k.a. Charles Lee Ray, voiced by Brad Dourif) has a former girl-friend, Tiffany (Jennifer Tilly) whose tarty soul has migrated into a doll too: a bridal babe. Chucky and Tiffany do what you'd expect them to do, supervised by Hong Kong director Ronny Yu ("The Bride with White Hair"), considering the only way they can live happily ever after as humans is to find compatible body donors. And the greatest horror is that, given an offspring, there might be yet another sequel. On the Granger Movie Gauge of 1 to 10, "Bride of Chucky" is a malevolent, blood splattering 1. It's just too gross!
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