slowly marching towards a better me

Cranquis: Hey, what’s the name of that new cardiologist?

Colleague: Dr Hartman.

Cranquis: Ok, tha– wait.

Colleague:

Cranquis:

“But that’s unfair to the people who submitted on time!”

I didn’t say you had to give everybody full credit. Drop the grade for each individual assignment by 5% for every day late until it gets down to 20%. Never, ever take it below 20%.

Here’s my rationale:

1. If you are a good educator, then you created that assignment in the first place because YOU WANTED YOUR STUDENTS TO LEARN SOMETHING. You still want them to have an incentive to complete that learning experience even if it’s not “on time.”

2. You want to prepare your students for the the real world, right? Well, if you missed a deadline (for example, submitting report cards), would your boss throw away everything you’d worked on, dock your paycheck, and tell you to try again next time? No. They would be upset with you, but they would ask you to take time out of your schedule to finish the project as quickly as possible. It wouldn’t cease to exist.

3. Based on point #2, if you are teaching high school or below, not accepting late work is holding children (who by the way, generally do not have full control over their schedules or what materials they have access to) to a higher standard than adults. 

4. If you are teaching college or graduate school, you are working with adults who are taking years out of their lives and paying thousands of dollars to learn from you. Why make it harder for them than it already is?

5. You have or will teach students with extenuating life circumstances that they don’t tell you about (e.g. chronic illness, caring for children or sick relatives, abusive relationships) because they are embarrassed to share this information or have already been taught to shut up and stop making excuses.

6. You have or will teach students with learning disabilities that they don’t even know about. I was diagnosed with ADHD in high school after years of being treated like I was just a bad kid. I suffered from depression and anxiety for over ten years before I went on medication. I did not even learn the words “executive dysfunction” until I was in grad school.

Ah, 2019….so full of promise :’)

Does your lab have a Wall of Shame? If not, you definitely need one…

Rerouting Nerves During Amputation Reduces Phantom Limb Pain Before it Starts

Doctors are pioneering the use of primary targeted muscle reinnervation (TMR) to prevent or reduce debilitating phantom limb and stump pain in amputees.

Content regulation algorithms tell me that sci-fi authors are overly generous in these depictions.

“Why did cop bot arrest that nice elderly woman?”

“It insists she’s the mafia.”

“It thinks she’s in the mafia?”

This is why a lot of people say AI are so dangerous. Not because they will one day wake up and be conscious and overthrow humanity, but that they (or at least this type of AI) are not and never will be conscious, and yet we’re relying on them to do things that require such human characteristics as logic and any sort of thought process whatsoever. Humans have a really bad tendency to anthropomorphize, and we’d like to think the AI is “making decisions” or “thinking,” but the truth is that what it’s doing is fundamentally different from either of those things. What we see as, say, a field of grass, a neural network may see as a bus stop. Not because there is actually a bus stop there, or that anything in the photo resembles a bus stop according to our understanding, but because the exact right pixels in the photo were shaded in the exact right way so that they just so happened to be statistically correlated with the arbitrary functions it created when it was repeatedly exposed to pictures of bus stops over and over. It doesn’t know what grass is, what a bus stop is, but it sure as hell will say with 99.999% certainty that one is in fact the other, for reasons you can’t understand, and will drive your automated bus off the road and into a ditch because of this undetectable statistical overlap. Because a few pixels were off in just the right way in just the right places and it got really, really confused for a second.

There, I even caught myself using the word “confused” to describe it. That’s not right, because “confused” is a human word. What’s happening with the AI is something we don’t have the language to describe.

Anyway what’s more, this sort of trickery can be mimicked. A human wouldn’t be able to figure it out, but another neural network can easily guess the statistical filters it uses to identify things and figure out how to alter images with some white noise in exactly the right way to make the algorithm think it’s actually something else. It’ll still look like the original image, just with some pixelated artifacts, but the algorithm will see it as something completely different. This is what’s known as a “single pixel attack.” I am fairly confident porn bot creators might end up cracking the content flagging algorithm and start putting up some weirdly pixelated porn anyway, and all of this will be in vain. All because Tumblr staff decided to rely on content moderation via slot machine.

Hyperkalaemia ECG changes in 15 seconds. 

High levels of potassium destabilise the cardiac membrane causing arrhythmia’s which lead to cardiac arrest. This can be a real life-saving opportunity if you can catch and treat it!

These Bacteria May Be the Key to Treating Clinical Depression

A new generation of organic light-emitting diodes

Another major success for the University of Bayreuth: over the next four years, the university will be coordinating an intercontinental research network that has 3.9 million euros in funding. Taking an interdisciplinary approach, this network will enable international doctoral students to study and carry out interdisciplinary research in the field of organic light-emitting diodes (OLEDs). It seeks to boost the efficiency and durability of the diodes, which are crucial for television and smartphone screens, and to foster innovations such as curved or foldable displays.

This EU project is known as a Marie Słodowska-Curie Innovative Training Network (ITN). The core of the network consists of universities and research institutes as well as companies in Europe (companies account for one third of the network). Together, the project partners are seeking to expand and optimize the technological potential of organic light-emitting diodes. For this purpose, 15 positions are being advertised for doctoral researchers. Research work will range from basic and applied research to innovative developments. OLEDs are made from carbon-containing semiconductors which, as components of displays, can emit light with high colour contrast and ensure that the screens have very wide viewing angles.