Just added to my radio archive (click on date for link):

August 4, 2022 Simon Kuper, Financial Times columnist and author of Chums, on the upper-class caste that’s been ruling Britain for a decade • James Meadway, director of the Progressive Economy Forum, on the dispiriting economics of the leader of the Labour Party, the drab Kier Starmer

Krystal and Saagar break down the FBI's raid of Trump's Mar-a-Lago compound, the GOP reaction, Dark Brandon memes, Maddow's next steps, 'stop the steal' backfiring, GOP ignoring mainstream media, and the legal implications of the FBI raid!

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Koustuv Sinha is a PhD student in machine learning and natural language processing. Because much of his time is devoted to reading research papers in his field, he’s devoted significant effort into optimizing his workflow.

The TL;DR is that he’s used Emacs and Org-mode to develop an efficient method of discovering and curating interesting papers. It starts with the discovery. For this he uses Elfeed to subscribe to various Arxiv feeds in his areas of interest. He uses the elfeed-score package to rank these papers in the approximate order of his interest in them.

When he reads an abstract in the Elfeed results that seems interesting, he fires off a process that captures the paper’s metadata to his bibliography file; grabs a copy of the paper, renaming it to the bibtext key, and storing it in a central repository; and adds it to an Org file listing the papers we wants to read.

A lot of this is accomplished by leveraging John Kitchin’s org-ref. He calls org-ref functions directly to get and store the paper’s data. It’s a nice example of reusing someone else’s codebase in your own.

Sinha provides a huge number of details in his post so be sure to take a look. If you have similar needs, this is an excellent starting point for your own workflow or even something worth stealing wholesale.

Krystal and Saagar report on Democrats legislation, China tensions rising, weapons flowing to Ukraine, gay marriage vote, Dick Cheney's ad for Liz, Monkeypox hypocrisy, & media fawning!

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Lindsey Snell, journalist at ishgal.com, crossed the Ukraine border to talk to soldiers and civilians. What she found surprised her:

There are Ukrainian forces who are “openly Neonazis, and we’re still giving them weapons and calling them something that they’re not.” All across the frontlines Lindsey found swastikas, SS symbols, and Wolfsangels. But negative news in Ukraine undermines the West’s mission to bleed Russia and sell more weapons, so corporate US media paints over it.

Lindsey also found that while the western mercenaries who flew over to kill Russians are loving the war, most of the Ukrainians she spoke to, both soldiers and citizens, want it to end.

“The corruption and lack of equipment is worse in Ukraine than anywhere I’ve been, Syria, Iraq, Libya. It’s just so bad.” And for the Ukrainians who are starving, losing their homes, and dying, “there’s no end in sight.”

What’s worse — as is the norm with guests on Useful Idiots — no one in western media will report on Lindsey’s story. “Journalists come and see how corrupt everything is and that the soldiers have nothing, but none of is is reflected in mainstream reporting. It’s very well known but it’s just not getting past the filter of western media.”

Plus, subscribe for the full interview, where Lindsey shares the story of getting kidnapped in Syria, how the war is hurting Europeans, and Turkey’s potential invasion of Syria (that you probably won’t hear about).

It’s all this, and more, on this week’s episode of Useful Idiots. Check it out.

Subscribe now

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Topical satire show, featuring characters drawn from the worlds of celebrity and politics.

Click here for the extended episode, including the full interview where Claire and Mick discuss abortion rights in Ireland and the US, mainstream media’s constant attacks and misinformation about them, and why our government and media are too afraid to talk about Assange, the realities of the Ukraine proxy war, and US hegemony.

“Democracy is about having a say in how your country is run. Right now, that’s not happening. The way the system works, the politicians don’t feel under pressure to answer to the majority of the people.”

Mick Wallace and Clare Daly, members of the European Parliament, are Irish progressives. This means they speak out against the proxy war in Ukraine, Julian Assange’s torture, and the Syria dirty war. Elected progressives in the US are quite different.

“From what we can see,” they tell us. “You don’t have any left politics in the US. The Democrats are indistinguishable from the Republicans and Bernie would be seen as just right of center in Europe.”

And what does it take to get actual progressives like Clare and Mick in office?

“Until people take to the streets, it’s going to be very hard for any left wing party to show its head in America.”

Plus, subscribe for the extended interview where Claire and Mick discuss abortion rights in Ireland and the US, mainstream media’s constant attacks and misinformation about them, and why our government and media are too afraid to talk about Assange, the realities of the Ukraine proxy war, and US hegemony.

As Mick always says, “democracy means you can say what you like, but you’ll do what you’re told.”

And that’s this week’s episode of Useful Idiots. Check it out.

Subscribe now

Topical satire show, featuring characters drawn from the worlds of celebrity and politics.

In 1984, Godzilla rose from Tokyo Bay for the first time in nine years for THE RETURN OF GODZILLA. In 1985, an American distributor dramatically recut the movie into GODZILLA 1985. We're joined at long last by Important Cinema Club co-host Justin Decloux to discuss the many structural and ideological changes that were imposed upon Godzilla's big comeback.

Michael and Us is a podcast about political cinema and our crumbling world hosted by Will Sloan and Luke Savage.

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We’re joined by special investigator Brace Belden to look into the increasingly bizarre saga of the Black Hammer group, which recently made news as subject of a police raid, a suspicious death among their group members, criminal accusations against their leader, and now accusations of being part of a foreign influence operation. We discuss all this as well as the political value of Being Normal.

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Streaming tickets for our Pickathon fest set at Noon (PST) next Saturday, 8/6 are available at: https://frqncy.live/pickathon/?r=52e3

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We sit down with Jacobin's Europe editor David Broder to discuss the future of Italy, Meloni, the future of the world and of course we talk shit about Argentina

FIND OUR GUEST AND HIS WORK:
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https://www.nytimes.com/2022/07/22/opinion/italy-draghi-meloni-government.html

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Support Corner Späti

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Marxist historian, commentator, author, and executive-director of Tricontinental: Institute for Social Research Vijay Prasad joins Bad Faith this week to talk about what global revolutions in Sri Lanka, India, Colombia, and other locales around the world can teach Americans trying to cultivate a left revolution here at home. How should the left put pressure on captured union leadership, and how can it hold left politician's accountable? Does the left "eat itself," or is it in a necessary processes of developing a more adversarial theory of change? How does Vijay believe he will see revolution in his lifetime even as he observes the enormous structural barriers to change?

Subscribe to Bad Faith on YouTube for video of this episode. Find Bad Faith on Twitter (@badfaithpod) and Instagram (@badfaithpod).

Produced by Armand Aviram.

Theme by Nick Thorburn (@nickfromislands).

Featuring Matt Christman on how American history brought us to this awful present.

Support this podcast at Patreon.com/TheDig 

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dired-rsync is a great additional to my Machine Learning workflow in Emacs

Table of Contents

• File Manager GUI
• Rsync Tool in CLI
• Emacs’ Way: dired-rsync
• Setup for dired=rsync
• Enhance dired-rsync with compilation mode

For machine learning projects, I tweaked my workflow so the interaction with remote server is kept as less as possible. I prefer to do everything locally on my laptop (M1 Pro) where I have all the tools for the job to do data analysis, visualisation, debugging etc and I can do all those without lagging or WI-FI.

The only usage of servers is running computation extensive tasks like recursive feature selection, hyperparameter tuning etc. For that I ssh to the server, start tmux, git pull to update the codebase, run a bash script that I prepared locally to fire hundreds of experiments. All done in Emacs of course thanks to Lukas Fürmetz’s vterm.

The only thing left is getting the experiment results back to my laptop. I used two approaches for copying the data to local: file manager GUI and rsync tool in CLI.

Recently I discovered dired-rsync that works like a charm - it combines the two approaches above, providing a interactive way of running rsync tool in Emacs. What’s more, it is integrated seamlessly into my current workflow.

They all have their own use case. In this post, I brief describe those three approaches for coping files with a focus on dired-rsync in terms of how to use it, how to setup, and my thoughts on how to enhance it.

Note the RL stands for remote location, i.e. a folder a in remote server, and LL stands for local location, the RL’s counterpart. The action in discussion is how to efficiently copying files from RL to LL.

File Manager GUI

This is the simplest approach requires little technical skills. The RL is mounted in the file manager which acts as an access point so it can be used just like a local folder.

I usually have two tabs open side by side, one for RL, and one for LL, compare the differences, and then copy what are useful and exists in RL but not in LL.

I used this approach on my Windows work laptop where rsync is not available so I have to copy files manually.

Rsync Tool in CLI

The rsync tool is similar to cp and scp but it is much more power:

1. It copies files incrementally so it can stop at anytime without losing progress
2. The output shows what files are copied, what are remaining, copying speed, overall progress etc
3. Files and folders can be included/excluded by specifying patterns

I have a bash function in the project’s script folder as a shorthand like this

copy_from_debian_to_laptop () {
    # first argument to this function
    folder_to_sync=$1
    # define where the RL is 
    remote_project_dir=debian:~/Projects/2022-May
    # define where the LL is 
    local_project_dir=~/Projects/2022-May          
    rsync -avh --progress \
	  ${remote_project_dir}/${folder_to_sync}/ \
	  ${local_project_dir}/${folder_to_sync}
}

To use it, I firstly cd (change directory) to the project directory in terminal, call copy_from_debian_to_laptop function, and use the TAB completion to quickly get the directory I want to copy, for example

copy_from_debian_to_laptop experiment/2022-07-17-FE

This function is called more often from a org-mode file where I kept track of all the experiments.

Emacs’ Way: dired-rsync

This approach is a blend of the previous two, enable user to enjoy the benefits of GUI for exploring and the power of rsync.

What’s more, it integrates so well into the current workflow by simply switching from calling dired-copy to calling dired-rsync, or pressing r key instead of C key by using the configuration in this post.

To those who are not familiar with copying files using dired in Emacs, here is the step by step process:

1. Open two dired buffer, one at RL and one at LL, either manually or using bookmarks
2. Mark the files/folders to copy in the RL dired buffer
3. Press r key to invoke dired-rsync
4. It asks for what to copy to. The default destination is LL so press Enter to confirm.

After that, a unique process buffer, named *rsync with a timestamp suffix, is created to show the rsync output. I can stop the copying by killing the process buffer.

Setup for dired=rsync

The dired-rsync-options control the output shown in the process buffer. It defaults to “-az –info=progress2”. It shows the overall progress in one-line, clean and neat (not in MacOS though, see Issue 36). Sometimes I prefer “-azh –progress” so I can see exactly which files are copied.

There are other options for showing progress in modeline (dired-rsync-modeline-status), hooks for sending notifications on failure/success (dired-rsync-failed-hook and dired-rsync-success-hook).

Overall the library is well designed, and the default options work for me, so I can have a bare-minimal configuration as below (borrowed from ispinfx):

(use-package dired-rsync
  :demand t
  :after dired
  :bind (:map dired-mode-map ("r" . dired-rsync))
  :config (add-to-list 'mode-line-misc-info '(:eval dired-rsync-modeline-status 'append))
  )

There are two more things to do on the system side:

1. In macOS, the default rsync is a 2010 version. It does not work with the latest rsync I have on Debian server so I upgrade it using brew install rsync.

2. There no way of typing password as a limitation of using process buffer so I have to ensure I can rsync without remote server asking for password. It sounds complicated but fortunately it takes few steps to do as in Setup Rsync Between Two Servers Without Password.

Enhance dired-rsync with compilation mode

It’s such a great library that makes my life much easier. It can be improved further to provide greater user experience, for example, keep the process buffer alive as a log after the coping finished because the user might want to have a look later.

At the moment, there’s no easy way of changing the arguments send to rsync. I might want to test a dry-run (adding -n argument) so I can see exactly what files are going to be copied before running, or I need to exclude certain files/folders, or rerun the coping if there’s new files generated on RL.

If you used compilation buffer before, you know where I am going. That’s right, I am thinking of turning the rsync process buffer into compilation mode, then it would inherit these two features:

1. Press g to rerun the rsync command when I know there are new files generated on the RL
2. Press C-u g (g with prefix) to change the rsync arguments before running it for dry-run, inclusion or exclusion

I don’t have much experience in elisp but I had a quick look at source code, it seems there’s no easy of implementing this idea so something to add to my ever-growing Emacs wish-list.

In fact, the limitation comes from using lower level elisp functions. The Emacs Lisp manual on Process Buffers states that

Many applications of processes also use the buffer for editing input to be sent to the process, but this is not built into Emacs Lisp.

What a pity. For now I enjoy using it and look for opportunities to use it.

Krystal, Saagar, and friends talk about Kamala Harris, John Fetterman's campaign, Americans moving to Mexico, Olbermann podcast, PTSD, Instagram changes, Saudis & Biden, Taiwan tension, & more!

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We have on David Adler from the Progressive International to talk about drift-backs in the Aegean Sea that Forensic Architecture reported on (https://aegean.forensic-architecture.org/) and lighten up the episode with a little talk about Crazy Frog and Nick's new career as a 'Heat Influencer'

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Support Corner Späti

Emacs is the most user friendly piece of software ever invented by humanity. I use it for 90% of my computing task, including keeping my digital knowledge garden with notes. Several notes packages exist, with Org Roam as the most popular and fully-featured. I have used this package for a while now, but it relies on a database and has grown a feature set far beyond my needs.

Protesilaos (Prot) Stavrou is developing the Denote package that goes back to the basics of Emacs. The defining feature of this package is a file-naming convention that acts as metadata to find your notes. The basic structure is: YYYMMDDTHHMMSS--file-name-dashed__keyword1_keyword2.extension. The filename starts with a timestamp at one second resolution to ensure unique file names (unless you create more than one per second). This timestamp also acts as the unique identifier to link notes. The timestamp is followed by two dashes and the sluggified file name. Two underscores after the file name indicate the start of the keywords, separated by one underscore. This convention provides a convenient heuristics to find notes based on dates, title and keywords. Denote supports either Org mode, plain text or Markdown files.

The simplicity of Denote allows for it to be easily integrated with other Emacs packages and it can be easily extended with some Emacs Lisp code. I am working on a package to integrate it with Citar so that notes can be linked to a bibliography.

I decided to have a play with this package and considered moving away from Org Roam to the monastic simplicity of Denote. But before I decided to convert my existing knowledge base, I wanted to see how it behaves with thousands of files in a single folder. Rather then converting my existing files, I decided to generate some random files to see how it performs.

  ## Simulate n files in denote folder

  ## Initiation
  library(stringr)

  n <- 10000
  k <- 50

  wordlist <- readLines("collins-scrabble-words-2019.txt")
  wordlist <- tolower(words)
  tag_words <- sample(words[nchar(wordlist) <= 5], k)
  timestamps <- Sys.time() + sample(600E6:666E6, n)
  template <- c("#+title:      ",
                "#+date:       ",
                "#+filetags:   ",
                "#+identifier: ")
  denote_directory <- "~/denote-sim/"
  dir.create(denote_directory)

  ## Generate n random posts

  for(i in 1:n) {
      title <- paste(sample(wordlist, sample(2:5, 1)), collapse = "-")
      tags <- paste(sample(tag_words, sample(4, 1)), collapse = "_")
      identifier <- format(timestamps[i], "%Y%m%dT%H%M%S")
      front_matter <- c(paste0(template[1],
                               str_to_title(str_replace_all(title, "-", " "))),
                        paste0(template[2],
                               paste0("[", format(timestamps[i], "%F %a %H:%M"), "]")),
                        paste0(template[3],
                               paste0(":", str_replace_all(tags, "_", ":"), ":")),
                        paste0(template[4], identifier))
      links_list <- vector()
      for (j in 1:(sample(1:5, 1))) {
          links_list[j] <- paste0("- ", "[[denote:",
                                  sample(format(timestamps, "%Y%m%dT%H%M%S"), 1), "]]")
      }
      content <- c(front_matter,
                   "",
                   stringi::stri_rand_lipsum(1),
                   "",
                   paste("*", str_to_title(paste(sample(wordlist,
                                                        sample(1:3, 1)),
                                                 collapse = " "))),
                   links_list)
      filename <- paste0(denote_directory, identifier, "--", title, "__", tags, ".org")
      writeLines(content, filename)
  }

Guest: Sarah Riccardi-Swartz on Between Heaven and Russia: Religious Conversion and Political Apostasy in Appalachia published by Fordham University Press.

The post Russian Orthodox Converts in Appalachia appeared first on SRB Podcast.

Democracy Now! 2022-07-27 Wednesday

• Headlines for July 27, 2022
• A Pelosi Visit to Taiwan Could Inflame Tensions Between U.S. & China, with Little Benefit to Taiwanese
• Economist Jayati Ghosh: Global Debt Crisis Is Perfect Storm of Unrest, Economic Disaster, Starvation
• Richard Wolff: Fed Rate Hikes Are "Body Blow" to Workers Reeling from Pandemic, Growing Inequality

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Editors’ Highlights are summaries of recent papers by AGU’s journal editors.

Source: Journal of Advances in Modeling Earth Systems

The mixing between cumulus clouds and the nearby environment is one of the greatest sources of uncertainty in climate modeling. The air mass flux that crosses into a cloud is called “entrainment” and out of a cloud is called “detrainment”. Entrainment and detrainment rates are highly stochastic and complex functions of properties of cumulus clouds and the nearby environment.

Shin and Baik [2022] develop a stochastic mixing model using a machine learning (ML) technique that models the mixing process of convection. The authors found that the ML model predicts entrainment and detrainment rates better than previously proposed parameterizations, with the inputs of cloud and environment properties.

The single-column model simulations with the new mixing model produce realistic mean and variance of various shallow cumulus properties. The simulation results also suggest that most of the cloud variabilities are generated from the mixing process. This paper is an example of the cutting-edge integration of physical understanding and machine learning techniques.

Citation: Shin, J., & Baik, J.-J. (2022). Parameterization of stochastically entraining convection using machine learning technique. Journal of Advances in Modeling Earth Systems, 14, e2021MS002817. https://doi.org/10.1029/2021MS002817

—Jiwen Fan, Editor, Journal of Advances in Modeling Earth Systems

Text © 2022. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.