Twitter is one of those platforms that many businesses struggle to generate good levels of engagement on. However, there are some simple steps that you can take to learn how to get more engagement on Twitter. We're going to help you through 5 of these below.
Taken from the mouth of co-founder, Leo "Quality is key and quantity can't be forgotten." Thus meaning your tweets should be useful to users. Whether they're informative, entertaining or educational, users should take something away with them after reading your tweet and they should see lots of them too.
Tip: There is a fine line of giving users lots of great content to spamming them. However, a general rule shows that the more tweets you write, the more followers you'll have and so, the more engagement you get. But remember, keep the quality high!
The below image is sourced from Buffer, showing that the greater number of tweets you post, the higher your follower base.
You can see that a Twitter user with 1 to 1,000 tweets has an average of 51 to 100 followers. A user who has tweeted more than 10,000 times are followed on average by 1,000 to 5,000 users and so on. But why does this work?
Lots of tweets shows to users you have lots of activity and so, followers will feel more inclined to connect and build a relationship with you.
The more you tweet, the better you get at it. That way, you really learn how to write what users want and it can help you to pick up on tweeting formulas that work.
Finally, if you've tweeted a lot, you're spending lots of time on the app. Hence, the wider the door of opportunity to grow your followers.
Interesting: If you were to post 10,000 updates in a year, you'd have to post 27 times a day.
It's important that when crafting your tweets, you're taking into consideration how many of each type of tweet you're posting.
For example, a lot of users tend to opt for "Me Now" tweets, their opinions or complaints or their random thoughts. These can often make followers feel like "me-formers" rather than "informers".
For businesses, it's important you are an informer with a few "me-former" tweets from people within the business, industry spokespeople and other.
Spread your updates evenly, don't do them all in one go for the sake of it. Make your content fit a nice, even schedule. That way, won't when you do post it won't come across spammy or annoying and instead, your followers can expect and look forward to hearing from you at certain points of the day.
A lot of businesses can fall into the trap of forgetting to post and not using scheduling tools such as Buffer, Hootsuite or similar, making the chances of sticking to a schedule, very low.
Tip: #1 priority for businesses that struggle to stick to a social schedule is to use a scheduling tool. Depending on the number of social accounts you have, Buffer is completely free and easy to use.
If you're just starting out with your social schedule, don't be put off by not knowing when is best to post.
Try different times of the day and different days of the week. Monitor how well the posts do, when you get the most impressions and whether or not they're generating engagement. After a few weeks, you should have a clearer picture of how your posting schedule should look.
4. What Do Your Users Want?
Knowing when to post and posting frequently is great, though you're unlikely to generate engagement from these posts if you're not giving users what they want.
Over time, we've learnt that the posts that receive the most retweets and likes are those containing discounts, promotions, exclusive content and to take part in competitions. As a result, it's important that you incorporate some of these wants into your daily schedule.
By tapping into relevant hashtags such as "#FreebieFriday" you can also reach a bigger audience, increasing your brand awareness. This will also help condition your followers to expect a small freebie each Friday, making them more likely to engage, keep up to date with your posts and your brand in general.
Tip: In between these competitions, you should then refer back to point #2 to make sure you're sticking to the other successful forms of updates.
Finally, lots of businesses can miss the opportunity to really showcase how great they are on Twitter. Even some of the most dominate brands can make themselves look pretty weak from their Twitter profile, often because they fall into the trap of posting boring content with no real purpose.
Just like your website, in-store leaflets and emails, your social channels are a place for you to shout about how good you are, the exciting things you're up to and more – but don't go overboard. As much as people don't like Debbie Downers, they also won't like to hear how amazing you are every time you tweet.
Interesting: Gurus, authors and experts get a bump of 100+ more followers.
Another way to gain more followers and engagement: be Steve Jobs, Elton John or Kim Kardashian. Each of these "celebrities" are doers, creators and considered leaders by their following.
As a brand, you should be looking to be a creator, a leader and a doer to help bring something new to users and the world as a whole. Convey this message within your posts, your Twitter bio, across your other social media channels and overall presence online.
Tweet high-quality content, sharing useful links, business insights and product promotions and do it often.
Make sure your tweets fit within the 9 forms of update that have been researched to work. Monitor which types of update work best for your audience and when these should be posted.
Once you've found the type of post that works, make sure you're posting it at the optimum time. Craft a schedule of weekly updates that you can follow. Use a scheduling tool and prepare your posts in advance. Make them look good before you send them. Don't let your tool automatically share a link with no hashtags, @ mentions or images. It just won't perform well.
Share what your users want. Whether that's content such as latest blog posts, product promotions or freebies – giving something back is always a great way to push start the flow of engagement.
Highlight how good you are and make sure it shows across every online platform you're on. Don't leave it to your website to do all the talking. If your Twitter looks poor, users won't click through to see your amazing blog content or case studies if the post promoting it isn't enticing.
Hopefully now you'll understand how to get more engagement on Twitter. We help deliver social media campaigns that convert. Speak to one of our experts today for more information.


Xplorer2 Lite's interface is easily adapted to your preferences. Toolbars and information windows can be moved on a whim. You can browse two or more folders in one window, using program tabs and different panes. What's more, you can customize search windows and save the settings for later use. Visual filters improve crowded directory readability. You can easily rename multiple files at once, split or merge files, synchronize folders, and shred data to prevent recovery.


Our Northampton base is the Whitepark services on the A5 near Towcester in Northants. NN7 4SE Conveniently a 45 min bus shuttle ride to Luton airport. Here you can change and get ready for your flight to Geneva or Toulouse.


text:
79 WEEK SSAC
REASONS FOR REMOVAL:    25017 Scheduled Sacrifice
REMOVAL DATE RANGE:     102094 102194
TREATMENT GROUPS:       INCLUDE 001    0 MG/KG
INCLUDE 002    0 MG/KG
INCLUDE 005    30 MG/KG
INCLUDE 007    150     MG/KG
Testes                        Hyperplasia
Clitoral Gland                Cyst
Kidney                        Nephropathy
TERMINAL SACRIFICE AT . WEEKS
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    0/10 (0%)    0/10 (0%)    0/10 (0%)  |  0/10 (0%)    3/10 (30%)   0/10 (0%)    0/10 (0%)  |
|TERMINAL (d)           |  0/0          0/0          0/0          0/0        |  0/0          0/0          0/0          0/0        |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          ---       |   ---          548 (I)      ---          ---       |
|LIFE TABLE             |    (e)          (e)          (e)          (e)      |  P=0.206N     P=0.111        (e)          (e)      |
|INCIDENTAL TUMOR       |    (e)          (e)          (e)          (e)      |  P=0.206N     P=0.111        (e)          (e)      |
|LOGISTIC REGRESSION    |    (e)          (e)          (e)          (e)      |  P=0.206N     P=0.111        (e)          (e)      |
|FISHER EXACT           |                 (e)          (e)          (e)      |               P=0.105        (e)          (e)      |
|OVERALL (a)            |  4/10 (40%)   8/10 (80%)  10/10 (100%) 10/10 (100%)|  0/10 (0%)    0/10 (0%)    1/10 (10%)   9/10 (90%) |
|ADJUSTED (b)           |  40.0%        80.0%       100.0%       100.0%      |   0.0%         0.0%        10.0%        90.0%      |
|INTERIM SACRIFICE 1 (c)|  4/10 (40%)   8/10 (80%)  10/10 (100%) 10/10 (100%)|  0/10 (0%)    0/10 (0%)    1/10 (10%)   9/10 (90%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |   ---          ---          548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.028 *    P=0.091      P=0.009 **   P=0.009 ** |  P<0.001 **     (e)        P=0.500      P<0.001 ** |
|INCIDENTAL TUMOR       |  P=0.028 *    P=0.091      P=0.009 **   P=0.009 ** |  P<0.001 **     (e)        P=0.500      P<0.001 ** |
|LOGISTIC REGRESSION    |  P=0.028 *    P=0.091      P=0.009 **   P=0.009 ** |  P<0.001 **     (e)        P=0.500      P<0.001 ** |
|FISHER EXACT           |               P=0.085      P=0.005 **   P=0.005 ** |                 (e)        P=0.500      P<0.001 ** |
|OVERALL (a)            |  3/10 (30%)   1/10 (10%)   2/10 (20%)   0/10 (0%)  |  0/10 (0%)    0/10 (0%)    1/10 (10%)   0/10 (0%)  |
|INTERIM SACRIFICE 1 (c)|  3/10 (30%)   1/10 (10%)   2/10 (20%)   0/10 (0%)  |  0/10 (0%)    0/10 (0%)    1/10 (10%)   0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      ---       |   ---          ---          548 (I)      ---       |
|OVERALL (a)            |  0/0 (0%)     0/0 (0%)     0/0 (0%)     0/0 (0%)   |  0/9 (0%)     0/10 (0%)    0/8 (0%)     3/10 (30%) |
|ADJUSTED (b)           |   0.0%         0.0%         0.0%         0.0%      |   0.0%         0.0%         0.0%        30.0%      |
|INTERIM SACRIFICE 1 (c)|  0/0          0/0          0/0          0/0        |  0/9 (0%)     0/10 (0%)    0/8 (0%)     3/10 (30%) |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          ---       |   ---          ---          ---          548 (I)   |
|INCIDENTAL TUMOR       |    (e)          (e)          (e)          (e)      |  P=0.010 *      (e)          (e)        P=0.129    |
|LOGISTIC REGRESSION    |    (e)          (e)          (e)          (e)      |  P=0.010 *      (e)          (e)        P=0.129    |
|OVERALL (a)            |  0/0 (0%)     0/0 (0%)     0/0 (0%)     0/0 (0%)   |  5/9 (56%)    3/10 (30%)   2/8 (25%)    4/10 (40%) |
|INTERIM SACRIFICE 1 (c)|  0/0          0/0          0/0          0/0        |  5/9 (56%)    3/10 (30%)   2/8 (25%)    4/10 (40%) |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          ---       |   548 (I)      548 (I)      548 (I)      548 (I)   |
|OVERALL (a)            | 10/10 (100%) 10/10 (100%) 10/10 (100%) 10/10 (100%)|  6/10 (60%)   7/10 (70%)   8/10 (80%)   9/10 (90%) |
|INTERIM SACRIFICE 1 (c)| 10/10 (100%) 10/10 (100%) 10/10 (100%) 10/10 (100%)|  6/10 (60%)   7/10 (70%)   8/10 (80%)   9/10 (90%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |    (e)          (e)          (e)          (e)      |  P=0.125      P=0.500      P=0.317      P=0.157    |
|INCIDENTAL TUMOR       |    (e)          (e)          (e)          (e)      |  P=0.125      P=0.500      P=0.317      P=0.157    |
|LOGISTIC REGRESSION    |    (e)          (e)          (e)          (e)      |  P=0.125      P=0.500      P=0.317      P=0.157    |
|FISHER EXACT           |               P=1.000N     P=1.000N     P=1.000N   |               P=0.500      P=0.314      P=0.152    |
|OVERALL (a)            |  2/10 (20%)   4/10 (40%)   1/10 (10%)   1/10 (10%) |  4/10 (40%)   4/10 (40%)   4/10 (40%)   0/10 (0%)  |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   4/10 (40%)   1/10 (10%)   1/10 (10%) |  4/10 (40%)   4/10 (40%)   4/10 (40%)   0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |   548 (I)      548 (I)      548 (I)      ---       |
|LIFE TABLE             |  P=0.234N     P=0.317      P=0.500N     P=0.500N   |  P=0.025N*    P=0.672      P=0.672      P=0.051N   |
|INCIDENTAL TUMOR       |  P=0.234N     P=0.317      P=0.500N     P=0.500N   |  P=0.025N*    P=0.672      P=0.672      P=0.051N   |
|LOGISTIC REGRESSION    |  P=0.234N     P=0.317      P=0.500N     P=0.500N   |  P=0.025N*    P=0.672      P=0.672      P=0.051N   |
|FISHER EXACT           |               P=0.314      P=0.500N     P=0.500N   |               P=0.675N     P=0.675N     P=0.043N*  |
|OVERALL (a)            |  0/10 (0%)    0/10 (0%)    0/10 (0%)    4/10 (40%) |  8/10 (80%)   9/10 (90%)  10/10 (100%)  9/10 (90%) |
|ADJUSTED (b)           |   0.0%         0.0%         0.0%        40.0%      |  80.0%        90.0%       100.0%        90.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    0/10 (0%)    0/10 (0%)    4/10 (40%) |  8/10 (80%)   9/10 (90%)  10/10 (100%)  9/10 (90%) |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          548 (I)   |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.001 **     (e)          (e)        P=0.051    |  P=0.526      P=0.500      P=0.234      P=0.500    |
|INCIDENTAL TUMOR       |  P=0.001 **     (e)          (e)        P=0.051    |  P=0.526      P=0.500      P=0.234      P=0.500    |
|LOGISTIC REGRESSION    |  P=0.001 **     (e)          (e)        P=0.051    |  P=0.526      P=0.500      P=0.234      P=0.500    |
|FISHER EXACT           |                 (e)          (e)        P=0.043 *  |               P=0.500      P=0.237      P=0.500    |
|OVERALL (a)            | 10/10 (100%) 10/10 (100%)  9/10 (90%)  10/10 (100%)|  8/10 (80%)   4/10 (40%)   9/10 (90%)  10/10 (100%)|
|ADJUSTED (b)           | 100.0%       100.0%        90.0%       100.0%      |  80.0%        40.0%        90.0%       100.0%      |
|INTERIM SACRIFICE 1 (c)| 10/10 (100%) 10/10 (100%)  9/10 (90%)  10/10 (100%)|  8/10 (80%)   4/10 (40%)   9/10 (90%)  10/10 (100%)|
|LIFE TABLE             |  P=0.765        (e)        P=0.500N       (e)      |  P=0.022 *    P=0.091N     P=0.500      P=0.234    |
|INCIDENTAL TUMOR       |  P=0.765        (e)        P=0.500N       (e)      |  P=0.022 *    P=0.091N     P=0.500      P=0.234    |
|LOGISTIC REGRESSION    |  P=0.765        (e)        P=0.500N       (e)      |  P=0.022 *    P=0.091N     P=0.500      P=0.234    |
|FISHER EXACT           |               P=1.000N     P=0.500N     P=1.000N   |               P=0.085N     P=0.500      P=0.237    |
|OVERALL (a)            |  4/10 (40%)   8/10 (80%)   9/10 (90%)   8/10 (80%) |  7/10 (70%)  10/10 (100%) 10/10 (100%)  9/10 (90%) |
|ADJUSTED (b)           |  40.0%        80.0%        90.0%        80.0%      |  70.0%       100.0%       100.0%        90.0%      |
|INTERIM SACRIFICE 1 (c)|  4/10 (40%)   8/10 (80%)   9/10 (90%)   8/10 (80%) |  7/10 (70%)  10/10 (100%) 10/10 (100%)  9/10 (90%) |
|LIFE TABLE             |  P=0.270      P=0.091      P=0.034 *    P=0.091    |  P=0.510      P=0.111      P=0.111      P=0.293    |
|INCIDENTAL TUMOR       |  P=0.270      P=0.091      P=0.034 *    P=0.091    |  P=0.510      P=0.111      P=0.111      P=0.293    |
|LOGISTIC REGRESSION    |  P=0.270      P=0.091      P=0.034 *    P=0.091    |  P=0.510      P=0.111      P=0.111      P=0.293    |
|FISHER EXACT           |               P=0.085      P=0.029 *    P=0.085    |               P=0.105      P=0.105      P=0.291    |
|OVERALL (a)            |  2/10 (20%)   0/10 (0%)    2/10 (20%)   2/10 (20%) |  0/10 (0%)    1/10 (10%)   0/10 (0%)    3/10 (30%) |
|ADJUSTED (b)           |  20.0%         0.0%        20.0%        20.0%      |   0.0%        10.0%         0.0%        30.0%      |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   0/10 (0%)    2/10 (20%)   2/10 (20%) |  0/10 (0%)    1/10 (10%)   0/10 (0%)    3/10 (30%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      ---          548 (I)      548 (I)   |   ---          548 (I)      ---          548 (I)   |
|LIFE TABLE             |  P=0.428      P=0.234N     P=0.707      P=0.707    |  P=0.041 *    P=0.500        (e)        P=0.111    |
|INCIDENTAL TUMOR       |  P=0.428      P=0.234N     P=0.707      P=0.707    |  P=0.041 *    P=0.500        (e)        P=0.111    |
|LOGISTIC REGRESSION    |  P=0.428      P=0.234N     P=0.707      P=0.707    |  P=0.041 *    P=0.500        (e)        P=0.111    |
|FISHER EXACT           |               P=0.237N     P=0.709N     P=0.709N   |               P=0.500        (e)        P=0.105    |
|OVERALL (a)            |  0/10 (0%)    2/10 (20%)   1/10 (10%)   1/10 (10%) |  2/10 (20%)   1/10 (10%)   2/10 (20%)   1/10 (10%) |
|ADJUSTED (b)           |   0.0%        20.0%        10.0%        10.0%      |  20.0%        10.0%        20.0%        10.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    2/10 (20%)   1/10 (10%)   1/10 (10%) |  2/10 (20%)   1/10 (10%)   2/10 (20%)   1/10 (10%) |
|FIRST INCIDENCE (DAYS) |   ---          548 (I)      548 (I)      548 (I)   |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.686      P=0.234      P=0.500      P=0.500    |  P=0.493N     P=0.500N     P=0.707      P=0.500N   |
|INCIDENTAL TUMOR       |  P=0.686      P=0.234      P=0.500      P=0.500    |  P=0.494N     P=0.500N     P=0.707      P=0.500N   |
|LOGISTIC REGRESSION    |  P=0.686      P=0.234      P=0.500      P=0.500    |  P=0.494N     P=0.500N     P=0.707      P=0.500N   |
|OVERALL (a)            |  8/10 (80%)   5/10 (50%)   1/10 (10%)   0/10 (0%)  |  7/10 (70%)   6/10 (60%)   7/10 (70%)   1/10 (10%) |
|INTERIM SACRIFICE 1 (c)|  8/10 (80%)   5/10 (50%)   1/10 (10%)   0/10 (0%)  |  7/10 (70%)   6/10 (60%)   7/10 (70%)   1/10 (10%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      ---       |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.002N**   P=0.180N     P=0.004N**   P<0.001N** |  P=0.005N**   P=0.500N     P=0.683      P=0.013N*  |
|INCIDENTAL TUMOR       |  P=0.002N**   P=0.180N     P=0.004N**   P<0.001N** |  P=0.005N**   P=0.500N     P=0.683      P=0.013N*  |
|LOGISTIC REGRESSION    |  P=0.002N**   P=0.180N     P=0.004N**   P<0.001N** |  P=0.005N**   P=0.500N     P=0.683      P=0.013N*  |
|COCHRAN-ARMITAGE       |  P=0.002N**                                        |  P=0.004N**                                        |
|FISHER EXACT           |               P=0.175N     P=0.003N**   P<0.001N** |               P=0.500N     P=0.686N     P=0.010N** |
|OVERALL (a)            |  0/10 (0%)    1/10 (10%)   0/10 (0%)    3/10 (30%) |  0/10 (0%)    0/10 (0%)    2/10 (20%)   0/10 (0%)  |
|ADJUSTED (b)           |   0.0%        10.0%         0.0%        30.0%      |   0.0%         0.0%        20.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    1/10 (10%)   0/10 (0%)    3/10 (30%) |  0/10 (0%)    0/10 (0%)    2/10 (20%)   0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   ---          548 (I)      ---          548 (I)   |   ---          ---          548 (I)      ---       |
|LIFE TABLE             |  P=0.037 *    P=0.500        (e)        P=0.111    |  P=0.694N       (e)        P=0.234        (e)      |
|INCIDENTAL TUMOR       |  P=0.037 *    P=0.500        (e)        P=0.111    |  P=0.694N       (e)        P=0.234        (e)      |
|LOGISTIC REGRESSION    |  P=0.037 *    P=0.500        (e)        P=0.111    |  P=0.694N       (e)        P=0.234        (e)      |
|COCHRAN-ARMITAGE       |  P=0.036 *                                         |  P=0.696N                                          |
|OVERALL (a)            | 10/10 (100%)  6/10 (60%)   6/10 (60%)   0/10 (0%)  |  0/10 (0%)    0/10 (0%)    0/10 (0%)    1/10 (10%) |
|ADJUSTED (b)           | 100.0%        60.0%        60.0%         0.0%      |   0.0%         0.0%         0.0%        10.0%      |
|INTERIM SACRIFICE 1 (c)| 10/10 (100%)  6/10 (60%)   6/10 (60%)   0/10 (0%)  |  0/10 (0%)    0/10 (0%)    0/10 (0%)    1/10 (10%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      ---       |   ---          ---          ---          548 (I)   |
|LIFE TABLE             |  P<0.001N**   P=0.051N     P=0.051N     P<0.001N** |  P=0.215        (e)          (e)        P=0.500    |
|INCIDENTAL TUMOR       |  P<0.001N**   P=0.051N     P=0.051N     P<0.001N** |  P=0.215        (e)          (e)        P=0.500    |
|LOGISTIC REGRESSION    |  P<0.001N**   P=0.051N     P=0.051N     P<0.001N** |  P=0.215        (e)          (e)        P=0.500    |
|COCHRAN-ARMITAGE       |  P<0.001N**                                        |  P=0.212                                           |
|FISHER EXACT           |               P=0.043N*    P=0.043N*    P<0.001N** |                 (e)          (e)        P=0.500    |
|OVERALL (a)            |  3/10 (30%)   5/10 (50%)   2/10 (20%)   1/10 (10%) |  0/10 (0%)    0/10 (0%)    9/10 (90%)   1/10 (10%) |
|ADJUSTED (b)           |  30.0%        50.0%        20.0%        10.0%      |   0.0%         0.0%        90.0%        10.0%      |
|INTERIM SACRIFICE 1 (c)|  3/10 (30%)   5/10 (50%)   2/10 (20%)   1/10 (10%) |  0/10 (0%)    0/10 (0%)    9/10 (90%)   1/10 (10%) |
|LIFE TABLE             |  P=0.107N     P=0.328      P=0.500N     P=0.293N   |  P=0.491        (e)        P<0.001 **   P=0.500    |
|INCIDENTAL TUMOR       |  P=0.107N     P=0.328      P=0.500N     P=0.293N   |  P=0.491        (e)        P<0.001 **   P=0.500    |
|LOGISTIC REGRESSION    |  P=0.107N     P=0.328      P=0.500N     P=0.293N   |  P=0.491        (e)        P<0.001 **   P=0.500    |
|FISHER EXACT           |               P=0.325      P=0.500N     P=0.291N   |                 (e)        P<0.001 **   P=0.500    |
|OVERALL (a)            |  0/10 (0%)    4/10 (40%)   3/9 (33%)    0/10 (0%)  |  1/10 (10%)   4/10 (40%)   4/10 (40%)   3/10 (30%) |
|ADJUSTED (b)           |   0.0%        40.0%        33.3%         0.0%      |  10.0%        40.0%        40.0%        30.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    4/10 (40%)   3/9 (33%)    0/10 (0%)  |  1/10 (10%)   4/10 (40%)   4/10 (40%)   3/10 (30%) |
|FIRST INCIDENCE (DAYS) |   ---          548 (I)      548 (I)      ---       |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.142N     P=0.051      P=0.093        (e)      |  P=0.507      P=0.157      P=0.157      P=0.293    |
|INCIDENTAL TUMOR       |  P=0.142N     P=0.051      P=0.093        (e)      |  P=0.507      P=0.157      P=0.157      P=0.293    |
|LOGISTIC REGRESSION    |  P=0.142N     P=0.051      P=0.093        (e)      |  P=0.507      P=0.157      P=0.157      P=0.293    |
|FISHER EXACT           |               P=0.043 *    P=0.087        (e)      |               P=0.152      P=0.152      P=0.291    |
|OVERALL (a)            |  1/10 (10%)   4/10 (40%)   6/9 (67%)    3/10 (30%) |  2/10 (20%)   1/10 (10%)   5/10 (50%)   3/10 (30%) |
|INTERIM SACRIFICE 1 (c)|  1/10 (10%)   4/10 (40%)   6/9 (67%)    3/10 (30%) |  2/10 (20%)   1/10 (10%)   5/10 (50%)   3/10 (30%) |
|LIFE TABLE             |  P=0.617N     P=0.157      P=0.021 *    P=0.293    |  P=0.325      P=0.500N     P=0.180      P=0.500    |
|INCIDENTAL TUMOR       |  P=0.617N     P=0.157      P=0.021 *    P=0.293    |  P=0.325      P=0.500N     P=0.180      P=0.500    |
|LOGISTIC REGRESSION    |  P=0.617N     P=0.157      P=0.021 *    P=0.293    |  P=0.325      P=0.500N     P=0.180      P=0.500    |
|FISHER EXACT           |               P=0.152      P=0.017 *    P=0.291    |               P=0.500N     P=0.175      P=0.500    |
|OVERALL (a)            |  1/10 (10%)   3/10 (30%)   1/9 (11%)    2/10 (20%) |  0/10 (0%)    0/10 (0%)    0/10 (0%)    0/10 (0%)  |
|INTERIM SACRIFICE 1 (c)|  1/10 (10%)   3/10 (30%)   1/9 (11%)    2/10 (20%) |  0/10 (0%)    0/10 (0%)    0/10 (0%)    0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |   ---          ---          ---          ---       |
|OVERALL (a)            |  2/10 (20%)   3/10 (30%)   1/10 (10%)   7/10 (70%) |  4/10 (40%)   1/10 (10%)   0/10 (0%)    1/10 (10%) |
|ADJUSTED (b)           |  20.0%        30.0%        10.0%        70.0%      |  40.0%        10.0%         0.0%        10.0%      |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   3/10 (30%)   1/10 (10%)   7/10 (70%) |  4/10 (40%)   1/10 (10%)   0/10 (0%)    1/10 (10%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |   548 (I)      548 (I)      ---          548 (I)   |
|LIFE TABLE             |  P=0.009 **   P=0.500      P=0.500N     P=0.040 *  |  P=0.252N     P=0.157N     P=0.051N     P=0.157N   |
|INCIDENTAL TUMOR       |  P=0.009 **   P=0.500      P=0.500N     P=0.040 *  |  P=0.252N     P=0.157N     P=0.051N     P=0.157N   |
|LOGISTIC REGRESSION    |  P=0.009 **   P=0.500      P=0.500N     P=0.040 *  |  P=0.252N     P=0.157N     P=0.051N     P=0.157N   |
|COCHRAN-ARMITAGE       |  P=0.008 **                                        |  P=0.249N                                          |
|FISHER EXACT           |               P=0.500      P=0.500N     P=0.035 *  |               P=0.152N     P=0.043N*    P=0.152N   |
|OVERALL (a)            |  2/10 (20%)   1/10 (10%)   0/10 (0%)    0/10 (0%)  |  1/10 (10%)   1/10 (10%)   0/10 (0%)    0/10 (0%)  |
|ADJUSTED (b)           |  20.0%        10.0%         0.0%         0.0%      |  10.0%        10.0%         0.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   1/10 (10%)   0/10 (0%)    0/10 (0%)  |  1/10 (10%)   1/10 (10%)   0/10 (0%)    0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      ---          ---       |   548 (I)      548 (I)      ---          ---       |
|OVERALL (a)            |  0/10 (0%)    0/10 (0%)    0/10 (0%)    6/10 (60%) |  1/10 (10%)   0/10 (0%)    9/10 (90%)   9/10 (90%) |
|ADJUSTED (b)           |   0.0%         0.0%         0.0%        60.0%      |  10.0%         0.0%        90.0%        90.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    0/10 (0%)    0/10 (0%)    6/10 (60%) |  1/10 (10%)   0/10 (0%)    9/10 (90%)   9/10 (90%) |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          548 (I)   |   548 (I)      ---          548 (I)      548 (I)   |
|LIFE TABLE             |  P<0.001 **     (e)          (e)        P=0.009 ** |  P<0.001 **   P=0.500N     P=0.001 **   P=0.001 ** |
|INCIDENTAL TUMOR       |  P<0.001 **     (e)          (e)        P=0.009 ** |  P<0.001 **   P=0.500N     P=0.001 **   P=0.001 ** |
|LOGISTIC REGRESSION    |  P<0.001 **     (e)          (e)        P=0.009 ** |  P<0.001 **   P=0.500N     P<0.001 **   P<0.001 ** |
|COCHRAN-ARMITAGE       |  P<0.001 **                                        |  P<0.001 **                                        |
|FISHER EXACT           |                 (e)          (e)        P=0.005 ** |               P=0.500N     P<0.001 **   P<0.001 ** |
|OVERALL (a)            |  2/3 (67%)    1/1 (100%)   3/3 (100%)   0/0 (0%)   |  4/4 (100%)   3/3 (100%)   2/2 (100%)   1/1 (100%) |
|ADJUSTED (b)           |  66.7%       100.0%       100.0%         0.0%      | 100.0%       100.0%       100.0%       100.0%      |
|INTERIM SACRIFICE 1 (c)|  2/3 (67%)    1/1 (100%)   3/3 (100%)   0/0        |  4/4 (100%)   3/3 (100%)   2/2 (100%)   1/1 (100%) |
|LIFE TABLE             |  P=0.999      P=0.718      P=0.500        (e)      |    (e)          (e)          (e)          (e)      |
|INCIDENTAL TUMOR       |  P=0.999      P=0.718      P=0.500        (e)      |    (e)          (e)          (e)          (e)      |
|LOGISTIC REGRESSION    |  P=0.999      P=0.718      P=0.500        (e)      |    (e)          (e)          (e)          (e)      |
|LIFE TABLE             |  P=0.230N     P=0.500      P=0.766      P=0.500N   |  P=0.785N       (e)        P=0.500        (e)      |
|INCIDENTAL TUMOR       |  P=0.230N     P=0.500      P=0.766      P=0.500N   |  P=0.785N       (e)        P=0.500        (e)      |
|LOGISTIC REGRESSION    |  P=0.230N     P=0.500      P=0.766      P=0.500N   |  P=0.785N       (e)        P=0.500        (e)      |
|FISHER EXACT           |               P=0.500      P=0.763N     P=0.500N   |                 (e)        P=0.500        (e)      |
|OVERALL (a)            |                                                    |  0/10 (0%)    0/10 (0%)    8/10 (80%)  10/10 (100%)|
|INTERIM SACRIFICE 1 (c)|                                                    |  0/10 (0%)    0/10 (0%)    8/10 (80%)  10/10 (100%)|
|TERMINAL (d)           |                                                    |  0/0          0/0          0/0          0/0        |
|FIRST INCIDENCE (DAYS) |                                                    |   ---          ---          548 (I)      548 (I)   |
|LIFE TABLE             |                                                    |  P<0.001 **     (e)        P<0.001 **   P<0.001 ** |
|INCIDENTAL TUMOR       |                                                    |  P<0.001 **     (e)        P<0.001 **   P<0.001 ** |
|LOGISTIC REGRESSION    |                                                    |  P<0.001 **     (e)        P<0.001 **   P<0.001 ** |
|FISHER EXACT           |                                                    |                 (e)        P<0.001 **   P<0.001 ** |
|OVERALL (a)            |                                                    |  3/10 (30%)   1/10 (10%)   1/10 (10%)   1/10 (10%) |
|INTERIM SACRIFICE 1 (c)|                                                    |  3/10 (30%)   1/10 (10%)   1/10 (10%)   1/10 (10%) |
|FIRST INCIDENCE (DAYS) |                                                    |   548 (I)      548 (I)      548 (I)      548 (I)   |
|INCIDENTAL TUMOR       |                                                    |  P=0.366N     P=0.293N     P=0.293N     P=0.293N   |
|OVERALL (a)            |  1/10 (10%)   2/10 (20%)   2/10 (20%)   0/10 (0%)  |  1/10 (10%)   0/10 (0%)    0/10 (0%)    0/10 (0%)  |
|ADJUSTED (b)           |  10.0%        20.0%        20.0%         0.0%      |  10.0%         0.0%         0.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)|  1/10 (10%)   2/10 (20%)   2/10 (20%)   0/10 (0%)  |  1/10 (10%)   0/10 (0%)    0/10 (0%)    0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      ---       |   548 (I)      ---          ---          ---       |
|INCIDENTAL TUMOR       |  P=0.214N     P=0.500      P=0.500      P=0.500N   |  P=0.517N     P=0.500N     P=0.500N     P=0.500N   |
|OVERALL (a)            |  2/10 (20%)   0/10 (0%)    0/10 (0%)    0/9 (0%)   |  2/10 (20%)   1/9 (11%)    2/10 (20%)   1/10 (10%) |
|ADJUSTED (b)           |  20.0%         0.0%         0.0%         0.0%      |  20.0%        11.1%        20.0%        10.0%      |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   0/10 (0%)    0/10 (0%)    0/9 (0%)   |  2/10 (20%)   1/9 (11%)    2/10 (20%)   1/10 (10%) |
|FIRST INCIDENCE (DAYS) |   548 (I)      ---          ---          ---       |   548 (I)      548 (I)      548 (I)      548 (I)   |
|LIFE TABLE             |  P=0.377N     P=0.234N     P=0.234N     P=0.257N   |  P=0.473N     P=0.539N     P=0.707      P=0.500N   |
|INCIDENTAL TUMOR       |  P=0.377N     P=0.234N     P=0.234N     P=0.257N   |  P=0.473N     P=0.539N     P=0.707      P=0.500N   |
|LOGISTIC REGRESSION    |  P=0.377N     P=0.234N     P=0.234N     P=0.257N   |  P=0.473N     P=0.539N     P=0.707      P=0.500N   |
|OVERALL (a)            |  2/10 (20%)   3/10 (30%)   2/10 (20%)   1/9 (11%)  |  1/10 (10%)   1/9 (11%)    0/10 (0%)    2/10 (20%) |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   3/10 (30%)   2/10 (20%)   1/9 (11%)  |  1/10 (10%)   1/9 (11%)    0/10 (0%)    2/10 (20%) |
|LIFE TABLE             |  P=0.334N     P=0.500      P=0.707      P=0.539N   |  P=0.341      P=0.743      P=0.500N     P=0.500    |
|INCIDENTAL TUMOR       |  P=0.334N     P=0.500      P=0.707      P=0.539N   |  P=0.341      P=0.743      P=0.500N     P=0.500    |
|LOGISTIC REGRESSION    |  P=0.334N     P=0.500      P=0.707      P=0.539N   |  P=0.341      P=0.743      P=0.500N     P=0.500    |
|FISHER EXACT           |               P=0.500      P=0.709N     P=0.542N   |               P=0.737      P=0.500N     P=0.500    |
|OVERALL (a)            | 10/10 (100%)  8/10 (80%)   9/10 (90%)   8/10 (80%) |  0/0 (0%)     0/0 (0%)     0/0 (0%)     0/0 (0%)   |
|ADJUSTED (b)           | 100.0%        80.0%        90.0%        80.0%      |   0.0%         0.0%         0.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)| 10/10 (100%)  8/10 (80%)   9/10 (90%)   8/10 (80%) |  0/0          0/0          0/0          0/0        |
|OVERALL (a)            |  2/10 (20%)   2/10 (20%)   0/10 (0%)    0/10 (0%)  |                                                    |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   2/10 (20%)   0/10 (0%)    0/10 (0%)  |                                                    |
|TERMINAL (d)           |  0/0          0/0          0/0          0/0        |                                                    |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      ---          ---       |                                                    |
|LIFE TABLE             |  P=0.160N     P=0.707      P=0.234N     P=0.234N   |                                                    |
|INCIDENTAL TUMOR       |  P=0.160N     P=0.707      P=0.234N     P=0.234N   |                                                    |
|LOGISTIC REGRESSION    |  P=0.160N     P=0.707      P=0.234N     P=0.234N   |                                                    |
|OVERALL (a)            |  2/10 (20%)   1/10 (10%)   2/10 (20%)   3/10 (30%) |                                                    |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   1/10 (10%)   2/10 (20%)   3/10 (30%) |                                                    |
|FIRST INCIDENCE (DAYS) |   548 (I)      548 (I)      548 (I)      548 (I)   |                                                    |
|LIFE TABLE             |  P=0.290      P=0.500N     P=0.707      P=0.500    |                                                    |
|FISHER EXACT           |               P=0.500N     P=0.709N     P=0.500    |                                                    |
|FISHER EXACT           |               P=0.291N     P=0.089      P=0.500    |                                                    |
|LIFE TABLE             |  P=0.048N*    P=0.500      P=0.111N     P=0.111N   |                                                    |
|INCIDENTAL TUMOR       |  P=0.048N*    P=0.500      P=0.111N     P=0.111N   |                                                    |
|LOGISTIC REGRESSION    |  P=0.048N*    P=0.500      P=0.111N     P=0.111N   |                                                    |
|COCHRAN-ARMITAGE       |  P=0.046N*                                         |                                                    |
|FISHER EXACT           |               P=0.500      P=0.105N     P=0.105N   |                                                    |
|OVERALL (a)            |  2/10 (20%)   0/10 (0%)    0/9 (0%)     1/10 (10%) |  0/10 (0%)    0/9 (0%)     0/10 (0%)    0/9 (0%)   |
|ADJUSTED (b)           |  20.0%         0.0%         0.0%        10.0%      |   0.0%         0.0%         0.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)|  2/10 (20%)   0/10 (0%)    0/9 (0%)     1/10 (10%) |  0/10 (0%)    0/9 (0%)     0/10 (0%)    0/9 (0%)   |
|FIRST INCIDENCE (DAYS) |   548 (I)      ---          ---          548 (I)   |   ---          ---          ---          ---       |
|LIFE TABLE             |  P=0.678      P=0.234N     P=0.257N     P=0.500N   |    (e)          (e)          (e)          (e)      |
|INCIDENTAL TUMOR       |  P=0.678      P=0.234N     P=0.257N     P=0.500N   |    (e)          (e)          (e)          (e)      |
|LOGISTIC REGRESSION    |  P=0.678      P=0.234N     P=0.257N     P=0.500N   |    (e)          (e)          (e)          (e)      |
|OVERALL (a)            |  0/10 (0%)    0/10 (0%)    0/10 (0%)    1/10 (10%) |  1/10 (10%)   0/10 (0%)    2/10 (20%)   0/10 (0%)  |
|ADJUSTED (b)           |   0.0%         0.0%         0.0%        10.0%      |  10.0%         0.0%        20.0%         0.0%      |
|INTERIM SACRIFICE 1 (c)|  0/10 (0%)    0/10 (0%)    0/10 (0%)    1/10 (10%) |  1/10 (10%)   0/10 (0%)    2/10 (20%)   0/10 (0%)  |
|FIRST INCIDENCE (DAYS) |   ---          ---          ---          548 (I)   |   548 (I)      ---          548 (I)      ---       |
|LIFE TABLE             |  P=0.235        (e)          (e)        P=0.500    |  P=0.472N     P=0.500N     P=0.500      P=0.500N   |
|INCIDENTAL TUMOR       |  P=0.235        (e)          (e)        P=0.500    |  P=0.472N     P=0.500N     P=0.500      P=0.500N   |
|LOGISTIC REGRESSION    |  P=0.235        (e)          (e)        P=0.500    |  P=0.472N     P=0.500N     P=0.500      P=0.500N   |
|FISHER EXACT           |                 (e)          (e)        P=0.500    |               P=0.500N     P=0.500      P=0.500N   |
|OVERALL (a)            |                                                    |  3/10 (30%)   0/10 (0%)    0/10 (0%)    2/10 (20%) |
|ADJUSTED (b)           |                                                    |  30.0%         0.0%         0.0%        20.0%      |
|INTERIM SACRIFICE 1 (c)|                                                    |  3/10 (30%)   0/10 (0%)    0/10 (0%)    2/10 (20%) |
|FIRST INCIDENCE (DAYS) |                                                    |   548 (I)      ---          ---          548 (I)   |
|LIFE TABLE             |                                                    |  P=0.506      P=0.111N     P=0.111N     P=0.500N   |
|INCIDENTAL TUMOR       |                                                    |  P=0.506      P=0.111N     P=0.111N     P=0.500N   |
|LOGISTIC REGRESSION    |                                                    |  P=0.506      P=0.111N     P=0.111N     P=0.500N   |

redpajama_set_name: RedPajamaCommonCrawl


The Benedictine Sisters of Erie uphold all those affected by the tragedy that unfolded at Tree of Life Synagogue in Squirrel Hill. There are no words to express our deep sadness at the senseless violence that took the lives of 11 innocent victims and inflicted injuries of body, mind heart and soul on so many. We stand in solidarity with our sisters and brothers of the Jewish faith helping them to bear their grief with our prayer and support. May they know God's peace.


text:
"use strict";

import * as go from "../release/go"

// HTML + JavaScript text editor menu, using HTML radio inputs and HTMLInfo.
// This file exposes one instance of HTMLInfo, window.TextEditorRadioButtons
// see /samples/customTextEditingTool.html
// see also textEditorSelectBox.js for another custom editor
// see also textEditor.html for a re-implementation of the default text editor
((window: any) => {
  // Use the following HTML:
  var customText = document.createElement("div");
  customText.id = "customTextEditor";
  customText.style.cssText = "border: 1px solid black; background-color: white;";
  customText.innerHTML =
  '  One <input type="radio" name="group1" id="One" value="One">
' +
  '  Two <input type="radio" name="group1" id="Two" value="Two">
' +
  '  Three <input type="radio" name="group1" id="Three" value="Three">
' +
  '  Four <input type="radio" name="group1" id="Four" value="Four">';

  var customEditor = new go.HTMLInfo();

	var myDiagram: go.Diagram;

  customEditor.show = (textBlock, diagram, tool) => {
    if (!(textBlock instanceof go.TextBlock)) return;
    var startingValue = textBlock.text;

    // Populate the select box:
    customText.innerHTML = "";

    var list = textBlock.choices;
    // Perhaps give some default choices if textBlock.choices is null
    if (list === null) list = ["Default A", "Default B", "Default C"];
    var l = list.length;
    for (var i = 0; i < l; i++) {
      var value = list[i];
      var label = document.createElement("label");
      var input = document.createElement("input");
      label.htmlFor = value;
      label.textContent = value;
      input.type = "radio";
      input.name = "group1";
      input.id = value;
      input.value = value;
      customText.appendChild(label);
      customText.appendChild(input);
      if (i !== l-1) customText.appendChild(document.createElement("br"));
    }

    // consider also adding the current value, if it is not in the choices list

    var children = customText.children
    var l = children.length;
    for (var i = 0; i < l; i++) {
      var child = children[i];
      if (!(child instanceof HTMLInputElement)) continue;
      // Make sure the radio button that equals the text is checked
      if (child.value == startingValue) {
        child.checked = true;
      }

      // Finish immediately when a radio button is pressed
      customText.addEventListener("change", (e) => {
        (<any>tool).acceptText(go.TextEditingTool.Tab);
      }, false);

    }

    // Do a few different things when a user presses a key
    customText.addEventListener("keydown", (e) => {
      var keynum = e.which;
      if (keynum == 13) { // Accept on Enter
        (<any>tool).acceptText(go.TextEditingTool.Enter);
        return;
      } else if (keynum == 9) { // Accept on Tab
        (<any>tool).acceptText(go.TextEditingTool.Tab);
        e.preventDefault();
        return false;
      } else if (keynum === 27) { // Cancel on Esc
        tool.doCancel();
        if (tool.diagram) tool.diagram.focus();
      }
    }, false);

    var loc = textBlock.getDocumentPoint(go.Spot.TopLeft);
    var pos = myDiagram.transformDocToView(loc);
    customText.style.left = pos.x + "px";
    customText.style.top  = pos.y + "px";
    customText.style.position = 'absolute';
    customText.style.zIndex = (100).toString(); // place it in front of the Diagram
    diagram.div.appendChild(customText);
  }

  customEditor.hide = (diagram, tool) => {
    diagram.div.removeChild(customText);
  }

  // customText is a div and doesn't have a "value" field
  // So we will make value into a function that will return
  // the "value" of the checked radio button
  customEditor.valueFunction = () => {
    var children = customText.children
    var l = children.length;
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redpajama_set_name: RedPajamaGithub


We bought this dehydrator in NYC and took it to Costa Rica to dehydrate coconut meat, kale and tomatoes. We loved it especially because it's so easy to take apart and to clean with a water hose. In Germany, this one wouldn't work without an extra huge power adapter.


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The Significance of British Film in the Chinese Imagination
British knowledge of Chinese culture is dire. Chinese soft power is almost non-existent. China has given the world neither Rock and Roll, Coca Cola or Hollywood, however, it is through a shared appreciation of Western culture that Britain has a lot more in common with the Chinese collective imagination then one might imagine. Figures since 2010 demonstrate that films written by British authors, films set in Britain and films by British directors were consistently popular in China. Despite British liberalism being consistently antagonized by Chinese authoritarianism, it is likely the citizens in both countries derive energy from the dreams and visions demonstrated through British cinema. This level of cultural liberalism was completely banned in Stalinist Russia where Stalin used film to strengthen his cult of personality, removing Trotsky from Eisenstein's 1928 film October and banning some 37 films between 1935 and 1936. Therefore, the shared experience of film should be utilised to create a common language between Britain and China to achieve future realities on a wide range of eventualities frum environmental sustainability to nuclear warfare.
Christopher Nolan seems to be the most significant director in China. In 2010 Inception was the 3rd biggest film. In 2012, the Dark Knight Rises was the 7th biggest film. In 2014, Inception was the 4th biggest film in China. In 2020, Interstellar re-released as the 24th biggest film and Inception re-released as the 47th biggest film. Collectively Nolan films made approximately 264 million dollars at the Box Office, promoting themes on law and order through Dark Knight Rises, Western Intelligence through Inception and climate disaster through Interstellar.
Like Britain, China hold a mutual infatuation with the worlds created by JRR Tolkien and JK Rowling. In 2010 Harry Potter and the Deathly Hallows Part One was the 7th biggest film. In 2011, Harry Potter and the Deathly Hallows Part Two was the 3rd biggest film. In 2013, the Hobbit: An Unexpected Journey was the 20th biggest film. In 2014 the Hobbit: The Desolation of Smaug was the 17th biggest film. In 2020 the rerelease of Harry Potter and the Philosophers Stone was the 19th biggest film. These alternative realities envisioned by JRR Tolkien and JK Rowling are arguably the two most popular in the modern collective British imagination. Growing up in Britain one was either experiencing the world through one of these authors. My entire imagination of the natural landscape got monopolized through the Lord of the Rings Trilogy. In light of vicious conflict over Chinese investigations into Coronavirus, the genocide of the Uighur population and the repression of Hong Kong protestors, most recently in regard to the 30th anniversary of the Tiananmen Square massacre it seems weird that Britain can explore similar imaginative landscapes.
Visions of Britain are not confined towards the world of Dragons, Hobbits, Witches and Wizards. The Chinese seemingly show an infatuation with more quotidian and prosaic English films. In 2017, Torquay's very own Agatha Christie had a Box Office hit with Murder on the Orient Express being the 56th biggest film in China and Paddington 2 was the 62nd biggest film. In 2018 the 62nd biggest film was Beatrix Potter's Peter Rabbit and the 63rd biggest film was Rowan Atkinson's Johnny English Strikes Again. Collectively these peculiarly British films made $115 million at the Chinese Box Office, emphasising the collective Chinese delight at stories that one associates with Chocolate Box Villages in May time Somerset.
Without yet mentioning James Bond, Skyfall and Spectre making approximately $ 143 million dollars through the Chinese box office, it is clear that the powerful images of Britain found in film are shared by all the Chinese people that have enjoyed these same cultural artefacts. It is said Thomas Paine learnt the Bible off by heart to effectively communicate ideas and stories with the masses. Whether in co-operation over climate or conversation over the pandemic, British film should create the foundation for effective communication with the Chinese, because, if we are able to collectively imagine the stories, characters and images in Nolan, Tolkien, Rowling, Christie, Potter, Rowan Atkinson and Paddington, then we might have a good chance at moving to a language and world we all like to imagine.


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IndyCar's Mikhail Aleshin released from Indianapolis hospital
By Chris EstradaSep 16, 2014, 4:00 PM EDT
Some very good news to report from the IndyCar world: Mikhail Aleshin was released today from Methodist Hospital in Indianapolis to continue his recovery from injuries sustained in a big practice crash at Auto Club Speedway on Aug. 29.
Aleshin did not compete in the next day's season finale, the MAV TV 500, after being diagnosed with a concussion, chest injuries, fractured ribs, and broken clavicle.
The Russian was taken to Loma Linda (Calif.) University Medical Center and remained there until he was transferred to Methodist on Sept. 9.
Following the transfer, Aleshin was evaluated by INDYCAR medical consultants Dr. Terry Trammell and Dr. Kevin Scheid, as well as doctors at Methodist. INDYCAR also reports that he underwent a minor surgical procedure on his right shoulder.
"I'm feeling better each day," Aleshin said in a series release. "I'm very happy to be back in Indianapolis with my friends and the team. The doctors are taking very good care of me.
"Everything is going as planned with my recovery, and before you know it I'll be back behind the steering wheel."
Aleshin will remain in Indianapolis to continue rehab work under the consultation of INDYCAR medical personnel.
In his crash, Aleshin lost control and spun into the path of the oncoming Charlie Kimball. Following their initial collision, Aleshin's No. 7 Honda went over Kimball's No. 83 Chip Ganassi Racing Chevrolet and into the catch fence; the impact tore a giant hole in the fencing at Turn 4 and left behind a wheel tangled in it.
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Located within walking distance of Kokusai Street, Yogi Park is the place to enjoy cherry blossoms in Naha. In spite of the central location, the park features a tranquil, natural setting with about 400 cherry trees lining the walkway and giant banyan and palm trees growing throughout the park. There is a preserved D51-type steam locomotive displayed in the park.


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Trump moving forward with border wall and other immigration issues
By Yucatan Times on January 25, 2017
A U.S. Border Patrol agent stands next to the existing fence at the Mexican border. (PHOTO: reuters.com)
WASHINGTON — President Donald Trump will begin rolling out executive actions on immigration Wednesday Jan. 25, beginning with steps to build his proposed wall along the U.S.-Mexico border, according to two administration officials. He's also expected to target so-called sanctuary cities and is reviewing proposals that would restrict the flow of refugees to the United States.
The Associated Press reported the president is expected to sign the first actions — including the measure to jumpstart construction of the wall — Wednesday during a trip to the Department of Homeland Security. Additional actions will be announced out over the next few days, according to one official.
Trump is said to still be weighing the details of plans to restrict refugees coming to the U.S. The current proposal includes at least a four-month halt on all refugee admissions, as well as temporary ban on people coming from some Muslim majority countries, according to a representative of a public policy organization that monitors refugee issues. The person was briefed on the details of that proposed action by a government official and outlined the expected steps for The Associated Press.
The officials and the public policy organization's representative insisted on anonymity in order to outline the plans ahead of Trump's official announcements.
On his personal Twitter account Tuesday night, Trump tweeted: "Big day planned on NATIONAL SECURITY tomorrow. Among many other things, we will build the wall!"
Trump campaigned on pledges to tighten U.S. immigration policies, including strengthening border security and stemming the flow of refugees. He also called for halting entry to the U.S. from Muslim countries, but later shifted the policy to a focus on what he called "extreme vetting" for those coming from countries with terrorism ties.
While the specific of Trump's orders were unclear, both administration officials said Wednesday's actions would focus in part on the president's plans to construct a wall along the southern border with Mexico. He's also expected to move forward with plans to curb funding of cities that don't arrest or detain immigrants living in the U.S. illegally, — localities dubbed "sanctuary" cities — which could cost individual jurisdictions millions of dollars.
Trump's insistence that Mexico would pay for the wall was among his most popular proposals on the campaign trail, sparking enthusiastic cheers at his raucous rallies. Mexico has repeatedly said it will not pay for any border wall.
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Source: bigstory.ap.org


Among the top landscape designers in Calgary, Taz calls himself a visionary as he has transformed the way people think about residential landscaping in Calgary. Read about his education, experience and background that brought him to where he is today. Taz: An Expert Landscape Designer!
When searching for a Landscape designer in Calgary you will find many professionals offering great services but trying to find a professional landscape designer that can understand your particular needs can prove to be very difficult.
Formal training and good experience in landscaping ideas help immensely and that is why we believe qualified professionalism should be at the top of your priority list when you are looking to find someone to provide you with a carefully thought out landscape design for your Calgary home.
Calgary based landscape designer, Mumtaz Mirza Aka. Taz, started out his journey in landscape design back in the University of Manitoba where he studied in the department of landscape architecture.
He obtained his bachelors of Environmental Design (B.Env.D) and went onto pursue a Master's degree in Landscape Architecture (M.LA) from the faculty of Architecture and Design.
During his education, he was able to fully grasp and understand the underlying foundations of landscape design theory and psychology that sought to recognize how people engage with their natural surroundings every day, thus allowing him to have a unique perspective as a professional landscape designer when compared to other residential landscapers.
Throughout his education, Taz was able to gain experience in many different areas of landscape design and construction; this included starting as a crew member for a landscape construction company, to a junior residential and eventually commercial landscape designer.
During his Master's degree, Taz had the opportunity to work for a prestigious architectural firm in Manitoba: Friesen Tokar Architects as a junior landscape architect. Following that, He worked for a number of landscape design and construction companies as a lead landscape designer.
In 2013, he moved to Calgary, Alberta to work as a senior landscape designer before finally deciding to start his own landscape design and construction company in the spring of 2015: Tazscapes Incorporated.
We are happy to report that in just a short amount of time, we have been rated and reviewed as one of the best landscaping company in Calgary!
As a lead landscape designer in Calgary, coupled with his experience in landscape management and landscape construction, Taz has developed a unique ability to envision outdoor retreats in residential backyards and front yards to set himself apart in creative landscaping solutions for the Calgary market.
With his strong skill-set to compliment his paramount academic background, Taz will personally meet with each of his clients and work with you from the initial consultation through onto the final landscape installation of the project, ensuring your dream truly becomes a reality.
Contact Tazscapes Inc today if you want to talk about your landscaping vision!
Tazscapes Inc is a Calgary landscaping company providing full-service landscape design and construction that thrives on providing quality landscaping services by professional and qualified Calgary landscapers.
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Darian has been an Alaskan resident since day one. Born in Palmer, AK and moved to Juneau at a very young age. She graduated from Thunder Mountain High School in 2011, where she played for the TMHS Softball team for three years. Shortly after graduation she moved to Fairbanks, Alaska to continued her education at the University of Alaska Fairbanks. After six years in the Interior, she decided it was time to return home to be near family.
Darian likes to go boating and fishing throughout the Inside Passage of Southeast Alaskan waters. She likes to spend quality time with her family at their cabin, surrounding herself with nature. She continues to follow her interest in softball during the summer time, and hike local trails around her home town.
Although she may be new to the chiropractic field, she is not new to customer service! Darian is a spunky, social, energetic person who is ready to take on new challenges and meet our patients. She loves meeting new people and is excited to be a part of the Arctic family!