If you shine light of high enough energy on to a metal, electrons will be emitted from the metal.

🤫

During a normal pregnancy, oxidative stress enhances antioxidant mechanisms that are capable of reacting by way of enzyme activity and non-enzyme free radical deactivators. However, pregnancy is also a state in which this adaptation and balance may be easily disrupted.

There is strong evidence that a chronicin flammatory reaction combined with the presence of a local oxidizing environment may play a vital role in the etiology and development of complications during pregnancy.

In late pregnancy, damage to DNA (especially when it is caused by oxidative stress) is associated with pre-eclampsia(PE), intrauterine growth restriction (IUGR), and the death of mothers in developing countries; it largely determines pregnancy – related susceptibility to diseases

The referential values of ROS and NOS and their minimal and safe concentrations or physiologically beneficial concentrations are yet to be determined.

The measurement of oxidative stress in vivo is perceived as controversial,

as the sen-sitivity and specificity of various oxidative stress markers is unknown.. .

This nonspecific cation channel opens when illuminated with blue light, depolarizing the cell [4, 6] to trigger action potentials cells with high temporal precision [5]. Since the initial discovery of ChR2, many modifications have been made to refine the kinetic properties.

For example, ChETA, engineered to address limitations of spike fidelity with ChR2, has faster temporal kinetics and can maintain reliable spike precision up to 200 Hz [7].

Halorhodopsins (NpHR), light-gated chloride pumps activated by yellow light, allow for temporally specific hyperpolarization with single spike precision [8–10].

Archaerhodopsin-3 (Arch), a yellow light-activated outward proton pump, is an increasingly popular tool for light-induced hyperpolarization to inhibit cellular activity. Arch recovers spontaneously from inactivation with a much shorter recovery time than NpHRs [11].

Arch currents continue to increase with increasing light intensity, while NpHRs saturate [11]. The increased light sensitivity of the ArchT variant, along with better membrane targeting, allows for improved neural silencing both at cell bodies and terminals [12].

So where are we at with this virus people?

Let's talk about Avi Loeb and his theory about alien

First, I should disclose that I work at the fame research facility as Dr. Loeb, though I work in a different department and to my recollection we've never met.

He's a scientist; I'm in computer support.

With that out of the way...
The interview above is worth a read, and a lot of serious thought, because there's an idea there that's really critical to science, and it isn't whether or not aliens have visited (exactly).

It's about how fashion and culture and taboo have an unfortunately strong effect on science.

In particular he compares his theory on alien visitation with the multiverse theory.

Which of these is more deserving of ridicule?

Science is fundamentally a structure for forming hypotheses and then (critically) testing these hypotheses to see if they should be kept, rejected, or modified.

1/ Today is #BlackHoleFriday, an annual science outreach event that, by complete coincidence I’m sure, is done on #BlackFriday. You’ll read lots of cool stuff about black holes on the hashtag. Here’s mine.

2/ Black holes are weird. Duh. People like to think of them as something like incredibly dense nuggets of stuff that sucks other stuff in. But they’re not like that.

3/ If you squeeze enough mass into a small enough volume, the gravity gets so intense that it’s impossible to escape them *if you get too close*. From far away, though, gravitationally they more or less act like anything with that much mass.

4/ So if the Sun turns into a black hole we wouldn’t get drawn in. In fact, we’d orbit it almost exactly the same way as we do now, though we’d freeze to death pretty rapidly, which, in the end, would still kinda suck.

5/ Black holes get weird *when you get close*. Anything with mass warps space — we feel that warp as gravity! — but black holes stretch space to its limit.

In a number of Sunday papers:
Scientific advisers said it was “hard to see” when the restrictions would end as new variants continued to emerge, delivering a potentially devastating blow to the travel industry. The prime minister said that after progress with vaccinations...

...”what we don’t want to see is all that work undone by the arrival of a new variant that is vaccine-busting”.
The idea is planted in people’s mind that this virus is mutating in such a way as to evade prior immunity. This is completely unfounded, certainly as regards immunity..

...gained naturally, after repelling the virus (which well around 99.9% of the population do, fewer, obviously in the very elderly & already ill, more in those younger & well). It’s important to appreciate that upon infection, the human immune system cuts up an infectious...

...agent into short pieces. Each of these short pieces of protein are presented to other cells in the immune system, like an identity parade. Our cells have a truly astonishing range of abilities to recognise different protein structures, and there will be some which recognise...

...each of the pieces of the invader. The cells which recognise a piece are instructed to multiply selectively so that, after a few days to a couple of weeks, our bodies contain large numbers of virus piece specific cells. These have a range of functions. Some make antibodies...

Next up at #enigma2021, Sanghyun Hong will be speaking about "A SOUND MIND IN A VULNERABLE BODY: PRACTICAL HARDWARE ATTACKS ON DEEP LEARNING"

(Hint: speaker is on the

In recent years ML models have worked from research labs to production, which makes ML security important. Adversarial ML research studies how to mess with ML

For example by messing with the training data (c.f. Tay which became super-racist super-fast) or by foiling ML models by changing inputs in ways humans can't see.

Prior work considers ML models in a standalone, mathematical way
* looks at the robustness in an isolated manner
* doesn't look at the whole ecosystem and how the model is used -- ML models are running in real hardware with real software which has real vulns!

This talk focuses on hardware-level vulnerabilities. This is particularly interesting because these can break cryptographic guarantees (because those are outside of their threat models)
e.g. fault injection attacks, side-channel attacks