t6 | IoT platform to connect physical Objects

I am new to MIPS assembly. I am trying to convert a java code to MIPS code but I can't figure it out that how can I load and store double values in MIPS. I get this error "address not aligned on doubleword boundary 0x10010001". Here is the java code:

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This is a follow-up question from this thread.

As per advised from the thread, the possible cause for why my Python code is not working is because I was to connect to a remote server in WSL2. And there could be unknown issues with WSL2 Ubuntu.

So I am testing that hypothesis with the following two approaches of communicating within WLS2 Ubuntu locally (i.e. via localhost:9092):

Note that, for both approaches below, I already have zookeeper running in one terminal (T1) with:

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I have data in devanagari that needs some extraction to be done. This is an example of a few lines

तत् इदम् K7 <<<<K1-अर्थ>T6-सार>T6-संग्रह>T6-भूतम्>T2 K1 <T6-आविष्करणाय>T6 अनेकैः <<T6-T6>Di-न्यायम्>T6>Bs6 अपि <K1-K1>K1 त्वेन लौकिकैः गृह्यमाणम् उपलभ्य अहम् विवेकतः <T6-अर्थम्>T4 संक्षेपतः विवरणम् करिष्यामि

T4 अपि यः Bs6 धर्मः वर्णान् आश्रमान् च उद्दिश्य विहितः सः <<<Bs6-स्थान>T6-प्राप्ति>T6-हेतुः>T6 अपि सन् <T6-बुद्ध्या>T6 अनुष्ठीयमानः T6 भवति <T6-वर्जितः>T3

The alphanumerics are the tags of the text. I need to extract the binary compounds along with their tags (the alphanumerics immediately after the compound) from the line. Binary compounds are the two words hyphenated in the angular brackets.

<<T6-T6>Di-न्यायम्>T6>Bs6

The first two are both examples of binary compounds whereas the last one is not. The simplest way to identify a binary compound is to find two words hyphenated enclosed by one set of angular brackets and followed by a single tag. So after extraction, of say the first line, I should get a list with this in it K7, K1

The code that I tried was this

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I am printing scorecard using global variables. For some reason the loop is getting terminated after 9 iterations even with an infinite loop.

Here is my code:

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I'm looking for help with R. I want to add three columns to existing data frames that contain time series data and have a lot of NA values. The data is about test scores. The first column I want to add is the first test score available. In the second column, I want the last test score available. In the third column, I want to calculate the derivative for each row by dividing the difference between the first and last scores by the number of tests that have passed. Important is that some of these past tests have NA values but I still want to include these when dividing. However, NA values that come after the last available test score I don't want to count.

Some explanation of my data: A have a couple of data frames that all have test scores of different people. The different people are the rows and each column represents a test score. There are multiple test scores per person for the same test in the data frame. Column T1 shows their first score, T2 the second score, which was gathered a week later, and so on. Some people have started sooner than others and therefore have more test scores available. Also, some scores at the beginning and the middle are missing for various reasons. See the two example tables below where the index column is the actual index of the data frame and not a separate column. Some numbers are missing from the index (like 3) because this person had only NA values in their row, which I removed. It is important for me that the index stays this way.

Example 1 (test A):

INDEX T1 T2 T3 T4 T5 T6 1 NA NA NA 3 4 5 2 57 57 57 57 NA NA 4 44 NA NA NA NA NA 5 9 11 11 17 12 NA

Example 2 (test B):

INDEX T1 T2 T3 T4 1 NA NA NA 17 2 11 16 20 20 4 1 20 NA NA 5 20 20 20 20

My goal now is to add to these data frames the three columns mentioned before. For example 1 this would look like:

INDEX T1 T2 T3 T4 T5 T6 FirstScore LastScore Derivative 1 NA NA NA 3 4 5 3 5 0.33 2 57 57 57 57 NA NA 57 57 0 4 44 NA NA NA NA NA 44 44 0 5 9 11 11 17 12 NA 9 12 0.6

And for example 2:

INDEX T1 T2 T3 T4 FirstScore LastScore Derivative 1 NA NA NA 17 17 17 0 2 11 16 20 20 11 20 2.25 4 1 20 NA NA 1 20 9.5 5 20 20 20 20 20 20 0

I hope I have made myself clear and that someone can help me, thanks in advance!

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This is my data:

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I'm studying about bootstrap two sample t test with boot package. In gene expression matrix, I want to compare genes between conditions and my aim is to find expressed genes. I have a matrix 5*12(5 control, 7 treatment and 5 genes) and firstly I converted this data matrix to tibble format as two long vector in order to understand the tibble structure and make it easier for me.:

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I have some data from an experiment to analyse with R but I have a problem and after days of search I can't find a solution.

I need to run multiple permutation t-tests and Mann-Whitney tests on my data grouped for different variables.

For examples, I have to say if there are differences in my response variable (exparat) between treatments (treat) on each experimental day (t).

This is how my dataset looks like:

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I am struggling to create a new data frame in Python (pandas) that keeps all of the existing columns in my DataFrame whilst multiplying only certain columns by 100,000.

The code I am using is:

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