Tavo @tavoglc@social.cleverlibre.org

Soooo, it ‘appears’ that “the largest egg producer in the US,” has seen their profit margin soar, showing a massive increase since last year. Avian flu seems to have played an insignificant role. Inflation seems to have played a zero role. Greed seems to be the bottom line. Just another example of what folks with money are willing to do to the little guy to increase their profits. Geez, maybe we should reward these big egg producers with some hefty tax cuts. 🤬 https://mindly.social/@annie/109755900547807890

From our awesome ☕ workgroup:

☕️We are almost ready for the next #ReproCoffee! ☕️
On Jan 31st at 3 pm (CET) we will be discussing "Measurement Schmeasurement" by Flake & Fried (2020) to learn more on how to avoid questionable practices. Sign in in our website at the link below and spread the news!👇
https://www.itrn.org/initiatives/reprocoffee

“I said I was a web developer in a social media environment, and a man told me that ‘cutting and pasting a man’s code doesn’t make you a developer.’”

"In our research, we... found that most women don’t know how to respond to these undervaluing statements, and most men don’t understand how to respond as allies, either."

https://www.forbes.com/sites/forbescoachescouncil/2023/01/25/how-women-are-valued-in-the-workplace-why-what-you-say-matters/

😬

"Using novel humanized IBC mouse models, we discovered that EGFR-targeted therapy remodels the IBC TME by increasing cytotoxic T cells and reducing immunosuppressive regulatory T cells and M2 macrophages. These changes were due to diminishing immunosuppressive chemokine expression regulated by transcription factor EGR1. We also showed that induction of an immunoactive IBC TME by an anti-EGFR antibody improved the antitumor efficacy of an anti–PD-L1 antibody."

#Immunology #Immunotherapy #EGFR #DrugDevelopment #MonoclonalAntibody

https://www.science.org/doi/10.1126/sciadv.abn7983

The robot apocalypse has been delayed.

#AI #machinelearning #cartoonlogic #silly

In #bioinformatics, and #scientific #computing generally, raw #data is never ever in a usable form.

This is one of the many things #Hollywood persistently gets wrong: the #scientist / #hacker / omni-computer-geek opens up the file, stares at a bunch of #numbers or #symbols, and says, "Ah hah! If I #compile the #HTML to reverse the #polarity on the #IP #gateway, I can #deconvolve the #DNA sequence to #backpropagate the #cellular #metabolism of the #alien #plague! Oh, and make #dinosaurs if you want, but that's extra."

Bonus points if the screen projects on said scientist's face and reflects from the inevitable chunky-framed glasses. Scribbling equations backward on a transparent whiteboard may also be involved.

#Scientists, as I have said many times before and no doubt will need to say many times again, are people. We're pretty good with numbers, yes, as a rule. But what we're good at doing with those numbers is not reading and understanding them. It's using them as the raw materials for product which makes sense to the human brain. Words, pictures, and a MUCH SMALLER number of numbers is our goal. Also continued #funding, which is about the kind of numbers everyone understands.

Before we process the numbers, we need to "#preprocess" them. There are several intermediate steps between the really raw data and the cover story for next week's issue of _Nature_. Preprocessing is where we turn the glowing symbols projected onto our faces into something that kinda-sorta makes sense. It's still not really readable, but people looking at it, who know what they're looking at, can tell what it represents.

Usually this is in the form of one or more #tables: for a familiar example, think of an #Excel workbook with several large #spreadsheets. (In reality, storing data in Excel is a terrible idea, but I'll stick with that metaphor.) Nobody's going to read and digest everything in the workbook. You can look at the headers and a few of the values and at least have an idea where to start. Preprocessing gets you to that point.

For most types of data, preprocessing is fairly standardized. You don't have to write your own code: someone else has already done that work for you. Just pick a #software #package, run the raw data through it, glance at the output to make sure nothing went horribly wrong. Now you're ready to write the code only you can write, to discover the Secrets of Life Itself. Now is the time for SCIENCE.

Or _Nature_. Or _The Journal Of Obscure Subfield Ten People In The World Know Exists_. Or a tech report. You know, whatever.

Careful readers will have noticed the word "fairly" above. In fact there are multiple #algorithms to choose from, and multiple packages implementing those algorithms, and #documentation written at 3:00 AM by an exhausted #postdoc who really just wanted to check the #cell cultures one last time and grab the remaining half a chicken salad sandwich from the break room fridge and go home and crawl into bed for a few hours' sleep before dragging ass back in tomorrow. Shower optional.

Other exhausted postdocs and their harassed #principal #investigators, who get somewhat more sleep and a somewhat finer grade of chicken salad but are much more worried about upcoming funding application deadlines, may or may not bother to write down which package they use to preprocess their data. Or what specific parameters they tuned. Or if they even know how they're supposed to use the damned thing: there's a really good chance they just ran the data through on the default settings, got something that looked reasonable, and called it a day.

Amazingly, most of the time this doesn't really matter. Data has a life of its own. The bigger the data set gets, and these days nearly all data are "big data," the more likely it is that any reasonable method will produce similar results. Good thing too, otherwise science (and _Science_) would grind to a screeching, shuddering, smoking halt.

Sometimes it matters a lot. Careful scientists check, just in case. I try to be one of those, and when I'm not, my coworkers pick up the slack. Luckily for me, for most of my career I've found myself in the company of those who live up to that standard, and I can mostly convince myself I do the same. Another item on Hollywood's long list of sins: science is not a solo enterprise. In fact it's deeply social, which is one of several reason why the stereotype of scientists as loners is a load of crap. But I digress.

In case you're wondering if this has a point, yes it does, and here it is: all the above is why my boss recently sent me a message saying, "Woah yeah ok so maybe you do need to process from raw after all. B/c idk wtf that is."

Without any irony at all: I love my job.

Minnesota 🌨️ COVID-19 current stats for Tue Jan 24 2023

Cases: 1,747,751
Deaths: 14,476
Recovered: 0
Active: 0
Tests: 24,087,418
Doses: 12,616,632

#covid_minnesota
https://covid.yanoagenda.com/states/Minnesota

Colorado 🏔️ COVID-19 current stats for Tue Jan 24 2023

Cases: 1,742,917
Deaths: 14,684
Recovered: 0
Active: 26,864
Tests: 21,068,549
Doses: 12,826,568

#covid_colorado
https://covid.yanoagenda.com/states/Colorado

@BaylessMarilyn @catsladder @HappyHeathen

Kentucky 🏇 COVID-19 current stats for Tue Jan 24 2023

Cases: 1,685,679
Deaths: 17,838
Recovered: 0
Active: 40,977
Tests: 13,675,281
Doses: 7,439,071

#covid_kentucky
https://covid.yanoagenda.com/states/Kentucky

Alabama 🏴 COVID-19 current stats for Tue Jan 24 2023

Cases: 1,596,149
Deaths: 20,820
Recovered: 0
Active: 54,870
Tests: 8,840,429
Doses: 6,957,265

#covid_alabama
https://covid.yanoagenda.com/states/Alabama

@catsladder @spacebarbarian

Louisiana 🏴 COVID-19 current stats for Tue Jan 24 2023

Cases: 1,533,257
Deaths: 18,479
Recovered: 0
Active: 22,798
Tests: 17,584,584
Doses: 6,899,017

#covid_louisiana
https://covid.yanoagenda.com/states/Louisiana

Maryland 🦀 COVID-19 current stats for Tue Jan 24 2023

Cases: 1,337,975
Deaths: 16,173
Recovered: 0
Active: 26,577
Tests: 24,164,742
Doses: 14,518,935

#covid_maryland
https://covid.yanoagenda.com/states/Maryland

@aktbar @kurtote @thereal_renaissance_man

#Genealogy Happy dance! My #FamilyHistory blog caught the eye of a distant cousin who wrote me with details to flesh out my hubby's #FamilyTree. Blogs are easily searchable and a great way to document ancestors as well as serve as #CousinBait

"Humans cultivate only about 150 of an estimated 30,000 edible plant species worldwide, with only 30 plant species comprising the vast majority of our diets."

Say yes to #biodiversity

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723411/

Almost 3 years of suffering from #LongCOVID (still without an official diagnosis mostly because back in march 2020 there were no tests), i realize how much my political perception has shifted. Today i am mostly disillusioned in regards to huge junks of the so-called radical left.

Chronically ill and therefore disabled, i was shocked to notice how deep ableism is not only ingrained in our societies at large, in fact it has to be considered one of the major structural problems that we should address in late stage capitalism, but how the radical left seems mostly unaware of this issue, in stark contrast to other structural problems like racism, sexism etc. against which the radical left at least tries to position itself. I am of course also humbled, because disability activists have been shouting this for years and i also mostly ignored the issue, until it has hit me personally. So shame on me as well.

What most people don't realize is how it was a moment of hope and perspective for disabled and immunocompromised comrades, when early in the pandemic many events started to happen remote, via streams and video chat. Because it finally offered them (or i should say it allowed us = the people forced to live in self-isolation on a permanent basis) a way to participate. The hope was, that at the very least everybody could plainly see how easy it was to implicate this option. All you need is an internet connection, a device with camera, done.

But later in the pandemic it was just as shocking and disheartening to see, how quickly all these possibilities were forgotten when the mitigating protective measures were walked back by the state, when the pandemic was declared to be over (which it still is not!).

In fact the radical left, at least here in Switzerland, were some of the earliest groups to hold in person meetings again without in parallel offering a stream for remote access. Technically, as we could have understood, this would have been no problem at all.

Protective masks were dropped soon after the state dropped its mandates, which excluded even more people from in person participation. People like myself and the many of us suffering from LongCOVID, who were chronically ill BECAUSE of this pandemic and who now had to try and avoid re-infection as best we could.

As an anarchist i simply don't understand how what the state decides and claims is followed so obediently or without questioning it by my former anarchist comrades. Especially during a pandemic, during what many call a mass disabling event. The health implications of COVID are still not fully understood, many will suffer from a debilitating weakened immune systems for years, maybe decades to come.

Yes, there were some interesting voices on the radical left, the long-term disability activists of course, the death panel podcast, peste magazine and a few more. But what again is shocking to me as an anarchist was to notice that most of them were marxists.

The anarchist or insurrectionist left was mostly absent in theory crafting against ableist panxemic politics. Quite the opposite here in Europe, where Agamben and the folks around the comitee invisible in France or Wu-Ming in Italy came out with atrocious conspiracy riddled articles and manifestos, that were well received by the far right covid-deniers. It seems the individualist strain of anarchism is what dominates in these parts. Stirner is winning.

But what we need is more Kropotkin. More mutual aid. More communal solutions. Especially during a pandemic. Especially when so many of us could end (and have ended) up disabled. What could have been happening in mutual aid was shown early on, when neighborhoods started to organize, when people made masks and went shopping for each other, cooked soup for the homeless, defying the lockdowns. Many of these initiatives petered out fast. But they could have evolved as the pandemic and the state response progressed.

Now mutual aid would still easily be possible. It would mean to keep focusing on communal health and care. To make all events inclusive for the disabled and the chronically ill. To keep the masks on. To counter the state narrative that the pandemic is over. To stream all events and moderate them so people can participate remotely. The model exists. Chaos Computer Club has been streaming all their events for years and allowed people to participate through IRC or "social" media.

As a disabled anarchist forced into self-isolation by the selfish behavior of many of my former comrades i am deeply disillusioned and frankly confused. This is not at all what i signed up for.

I called this. Most automated jobs, once mass automation of white collar professions sets in, will involve some third-worlder filtering undesired outputs while 'managing' three or four different AIs.

He won't really have to be good at it, companies just need someone to blame when something bad gets through.

Tory MPs, lords and even Downing Street advisers have been shamelessly accepting money from private healthcare firms as the NHS is on its knees.

https://www.mirror.co.uk/news/politics/tories-raking-money-private-health-29017569