It's not a problem of reflectivity, it's a problem of resolution. In order to detect something distinctly from other things (i.e. resolve that thing), you must be able to distinguish its reflected energy from that of other things by separating them along one or more dimension. Range is usually a good discriminator, but there are many things at (nearly) equal range to the radar. Azimuth is typically not great, because azimuth resolution requires a physically wide aperture, and real estate on the bumper is expensive. Doppler is great for moving things because it's easy to design a waveform with a small doppler resolution, and most moving things (cars, bikes, people) don't move at exactly the same speed as other moving things. However, nonmoving things have a very consistent velocity of precisely 0, and there are lots of them. So they can be very hard to resolve, and thus to detect.
In practice, the difference between pulsed radar and continuous wave radar is a continuum rather than a dichotomy. Historically, FMCW (frequency modulated continuous wave) had a high duty cycle (though not 100%, the ramp generators need finite time to reset (though you can alternate between up and downramps and get closer)). For some applications, though, requirements force you to short ramps and long PRIs, thus low duty cycles, but the name (FMCW) sticks.
This is true for some earlier lofi radars, but as driver assistance and self-driving have developed, so have the requirements and capabilities of the radar systems. Newer systems generally have shorter PRIs for higher doppler bandwidth, and much higher duty cycles for more energy on target - the FCC limits power, so you've got to get energy from the time axis. Both of these things make the interference problem harder.
I agree that you can't know what is "real" without looking at our universe from outside it, but that, in and of itself, doesn't imply that every model must be flawed, in the sense that its predictions must not be 100% consistent with observation. We could stumble across the "real" model, or something equivalent to it (in the sense of identical predictions) - we'd have no way of knowing whether the model is "real", but it could still be right.
I find laying of blame to be the most egregious waste of time, for work as well as personal issues. People who insist on it are, by and large, not people you want to spend time or money with.
I was confused by that terminology at first, too, but it appears their product has an "offer" phase where the meeting organizer suggests multiple times, and a "book" phase in which the invitees accept the meeting and it's booked. Which doesn't necessarily mean that the meeting is attended, but it is a higher level of confirmation/buy-in from the invitees than what happens at my work (FANG) where organizers just throw meetings on everyone's calendar.
Aliasing makes more sense (to me, anyway) if you think about the spectrum of complex signals, in which signals of real samples are modeled as the sum of positive and negative frequencies.
In the sampling operation, all sinusoids are shifted down to the "natural baseband" by adding or subtracting some multiple of the sampling frequency that places the resulting frequency within +/- half of the sampling frequency. So for your example of 22kHz, that real frequency has two components: +22kHz that gets shifted down to -18kHz=22kHz-40kHz, and -22kHz that gets shifted up to +18kHz=-22kHz+40kHz.
Note that this "natural baseband" is an abstraction of our own invention. You can just as easily think of the spectrum as ranging from 0Hz to the sampling frequency f_s, rather than -f_s/2 to f_s/2. The fact that some prefer one over the other is precisely why fftshift exists.
From an information theoretic perspective (which is the perspective Nyquist was originally coming from, though it didn't yet have that name), you don't need to mix the signal down. Assuming it is truly band-limited, you can sample the signal directly at RF, and reproduce it from those samples. Additionally, you will need to modulate the reproduced signal into the original band, which means you need to know where that band is - perhaps this is the detail you're pointing out?
Another way of looking at it is that sampling inherently does the mixing down to baseband. Although it may not be exactly the baseband you want if the spectrum isn't cleanly symmetric about a multiple of the sample frequency.
I'm not necessarily arguing against you, but "problematic" is too generic a term to be useful. Genocide is "problematic". Having to run to the bathroom every 5 minutes to blow my runny nose is "problematic". What do you actually mean?
OP argues that branches aren’t “just refs”, they’re a sequence of commits. I’d argue that a ref _is_ a sequence of commits. (Or, to be pedantic, it uniquely identifies a sequence of commits.)
Apologies if you consider this pedantic, but I prefer to phrase it in terms of the wavefunctions in position and momentum, rather than position and momentum, unadorned:
At a quantum-mechanical level, the wavefunction in the position domain is the Fourier transform of the wavefunction in the momentum domain, and vice versa - anything that constrains the position wavefunction to a narrow interval inherently also smears the momentum wavefunction...
Again, apologies if this seems pedantic. I know enough about quantum mechanics to be dangerous, but am no expert, so pedantic wording helps me keep things straight.
Another way to phrase my response to #1 above is that sinusoids are the natural modes of many systems. That is, you put a sinusoid in, and you get a sinusoid of the same frequency out. It may change in amplitude and/or phase, but it still has the same fundamental shape. This is again because these systems act like harmonic oscillators or systems of harmonic oscillators.
So why harmonic oscillators? The same analysis shows up any time you have a restoring force proportional to, and in the opposite direction of, the displacement. This shows up in springy things (recall the old mechanical engineer's adage: everything's a spring until it breaks), and fields of all sorts (electric, gravitational, magnetic, pressure).
There are a couple of incorrect assertions near the beginning that should be addressed:
1. "That is, sound waves are not made out of sines as real-word phenomena."
Sinusoids are the solutions to the harmonic oscillator differential equation (\ddot{x} = -w^2 x). The harmonic oscillator is an excellent model, or a component of excellent models, for many natural phenomena, including vibrating strings and columns of air, pressure waves in fluids, the list goes on. The utility of sinusoids is not due simply to their convenient mathematical properties, it's because many natural signals are sparse in the frequency domain, precisely because sinusoids do describe real world phenomena.
2. "A piston on a crankshaft produces "pure" sinusoidal up-and-down motion when operating at constant angular velocity."
Uh, no. The motion of a piston is approximately sinusoidal as you decrease the radius of the crank, but in no case is it a "pure" sinusoid.
The issue is that many don't know they're donating to a charity, regardless of alignment. The popups make it sound like donations go to the running of Wikipedia as a web service, not to political activism.