heartfelt | Cocos Creator 2.0 Material example

Guys I'm trying to put two buttons from two different forms on the same line. I tried to put an id on both buttons so that I can manage them in css. In particular, what I want to do is put the "delete" button next to the "update" button. This is what I tried to do but it doesn't work because the "delete" button stays under the "update" button.

Easy example: Taking as a reference the English abecedary (range A-Z). If I'm given a letter - let's say 'a' - and a number - let's say '2' - I would need to find out what's the letter 2 positions onwards. Answer would be 'c' ('a'--> 1 move:'b' --> 2 moves:'c')

Of course, you could be given a number larger than the size of the abecedary letters, which is 26. Since the rule is that after letter z comes letter a again, this means that if in the previous example number 26 was passed the letter we would need to find would be 'a'.

One last case scenario for the problem is that you may receive a negative number. So if letter 'a' is provided with number '-3', the answer would be 'x' ('a'--> 1 move:'z' --> 2 moves:'y' --> 3 moves:'x').

This is the code I have so far:

I have a collection in MongoDB of bands that have multiple albuns and genres. Here is a simplified example of collection:

I am a newbie to WPF and am trying to create a simple test app, while maintaining an MVVM architecture. So I split the application into two distinct projects: Tomato.UI (which contains the xaml files) and Tomato.ViewModels (which contains the classes to manage the interaction with the view).

For now I only have two files for one window: MainWindow.xaml and MainWindowViewModel.cs

In addition I added a reference to Tomato.ViewModels from Tomato.UI

So this is the MainWindow.xaml, where I've created a reference to the ViewModels namespace and where a Button is bound to a function on the MainWindowViewModel.cs file:

I have a large dataframe consisting of tweets, and keyword dictionaries loaded as values that have words associated with morality (kw_Moral) and emotion (kw_Emo). In the past I have used the keyword dictionaries to subset a dataframe to get only the tweets that have one or more of the keywords present.

For example, to create a subset with only those tweets that have emotional keywords, I loaded in my keyword dictionary...

We want elastic search to suggest words found within the index. We are using version: 5.6.4.

if I type "head" it should suggest "headquarters", a word found in the index. Preferably it should sort the suggestions by occurrence.

I have tried several tutorials, but they all return the entire content item instead of the word itself. The closest I came up with using the documentation is the following:

I have a large dataframe consisting of tweets, and a keyword dictionary loaded as a list that has words and word stems associated with emotion (kw_Emo). I need to find a way to count how many times any given word/word stem from kw_Emo is present each tweet. In kw_Emo, word stems are marked with an asterisk ( * ). For example, one word stem is ador*, meaning that I need to account for the presence of adorable, adore, adoring, or any pattern of letters that starts with ador….

From a previous Stack Overflow discussion (see previous question on my profile), I was greatly helped with the following solution, but it only counts exact character matches (Ex. only ador, not adorable):

1. Load relevant package.

   library(stringr)

2. Identify and remove the * from word stems in kw_Emo.

   for (x in 1:length(kw_Emo)) { if (grepl("[*]", kw_Emo[x]) == TRUE) { kw_Emo[x] <- substr(kw_Emo[x],1,nchar(kw_Emo[x])-1) } }

3. Create new columns, one for each word/word stem from kw_Emo, with default value 0.

   for (x in 1:length(keywords)) { dataframe[, keywords[x]] <- 0}

4. Split each Tweet to a vector of words, see if the keyword is equal to any, add +1 to the appropriate word/word stems' column.

   for (x in 1:nrow(dataframe)) { partials <- data.frame(str_split(dataframe[x,2], " "), stringsAsFactors=FALSE) partials <- partials[partials[] != ""] for(y in 1:length(partials)) { for (z in 1:length(keywords)) { if (keywords[z] == partials[y]) { dataframe[x, keywords[z]] <- dataframe[x, keywords[z]] + 1 } } } }

Is there a way to alter this solution to account for word stems? I'm wondering if it's possible to first use a stringr pattern to replace occurrences of a word stem with the exact characters, and then use this exact match solution. For instance, something like stringr::str_replace_all(x, "ador[a-z]+", "ador"). But I'm unsure how to do this with my large dictionary and numerous word stems. Maybe the loop removing [*], which essentially identifies all word stems, can be adapted somehow?

Here is a reproducible sample of my dataframe, called TestTweets with the text to be analysed in a column called clean_text:

dput(droplevels(head(TestTweets, 20)))

I'm learning SpringMVC. The version I use is 4.2.5.RELEASE. The filter I configure in web.xml doesn't seem to work

Server: Tomcat 7

Problem : When I use the GET method to pass in Chinese parameters, even if I configure the filter for UTF-8 encoding conversion, but the string I get is still garbled

web.xml:

I've been searching for a while now but still can't figure it out. I found expressions like ([一-龯])|([ぁ-んァ-ン]) but have no idea how to delete all except these.

What I like to do is something like this: