I once read an article about SQL and how reordering the sections of a query would make it more ergonomic for users (iirc things like specifying what you want first and then how to present it last, more like a pipeline). I searched many times over the years but have not been able to find it again.
I mean that the body most won't respond to signals to reabsorb water from the bladder because of weak QVPR2 activity.
AVPR2 only shows up (significantly) in the kidneys. It pumps water back from the bladder to the bloodstream. AVPR1 and AVPR3 show up in the brain (and drive/control any hormonal response tied to water availability/quality/safety-to-access. Including territorial mammals marking territory.)
Vasopressin is actually a mirror-image of oxytocin, with a few hundred million years of divergent mutations. Unique to mammals. That's why mammals are the only vertebrates that independently, separately, regulate water and ions. (Thus, sweating, lactation, crying, uncalcified placenta vs egg, etc.)
So the brain keeps pumping out vasopressin (in response to dehydration-induced corticotropin-releasing factor). This leads to water "running right through". And high baseline vasopressin levels that go even higher with dehydration.
Less commonly, especially for men, the body overreacts to vasopressin. Excessive vasopressin 2 receptor efficacy or transcription leads to low baseline vasopressin. Low vasopressin 'magnifies' any oxytocin activity. Leads to "human-hyperstimulated" autism and high innate trust in unfearful situations. Also often leads to low territory/spatial mapping capacity.
A. Research dates back to the 90s. Thousands of researchers have added their perspectives.
B. Look at what vasopressin does, in humans and other mammals.
C. Consider that Vasopressin Receptor 2, is right by the X pseudoautosomal region, so is mutated 15x-20x more frequently. Compare how often you've seen other pseudoautosomal differences in people with Vasopressin transcription differences.
Or just start searching for random genes from around the pseudoautosomal region + autism. Transcription differences in one pseudoautosomal gene are so closely tied to differences in others, you see a very unusually high number of correlations between autism-uninvolved genes and autism.
(Just as so many genes around TNF-alpha/6p21.3 are spuriously tied to autoinflammatory issues; major histocompatibility complex issues; tenascin-X-tied disorders including Ehlers-Danlos; and 17-hydroxysteroid-dehydrogenase-8 variance [which deactivates androgens+estrogens, and synthesizes moderate estradiol].
Or how so many genes near the adjacent corticotropin-releasing-hormone-receptor-1 (CRHR1) and Tau protein (MAPT), in the same area as DNA-repair-gene breast-cancer-associated1 (BRCA1), are spuriously tied to irrecoverable oxidative cell damage and neurodegeneration.)
C...Some very important pseudoautosomal genes include the final stage of melatonin synthesis (ASMT & ASMTL); antiviral and anti-small-pathogen signal receptors, for interleukin 9 and interleukin 3; SPRY3 lymphoid-to-myeloid switch granulocyte-macrophage colony stimulating factor (GM-CSF); cytokine-like-receptor 2 (CLRF); glycogenin 2 (starting-point for muscle fibers); steroid sulfatase (activates androgens, estrogens, progestogens); sex receptor Y and protocadherin-11-Y (PCDH11Y) in men [causing heritable father-to-daughter changes in protocadherin-11-X and near-adhacent androgen receptor].
D. Also, check out the research from the last head of the Kinsey Institute. They hired her for that vasopressin+oxytocin triggers pair-bonding, and monogamy in monogamous mammals.
I have used a few of these for testing at work (I'm a developer). They're pretty solid devices, well built, audio quality is _subjectively_ pretty good and they have headset ports.
I dunno about "multiway merge". But your standard 2-way merge is SIMD-optimized by having a binary-search across the "diagonals" of the so-called mergepath.
Leading to O(lg(p * sqrt(2))) time for the longest comparison diagonal, where "p" is the number of processors. Including thread divergence, that's O(N/p * lg(p * sqrt(2))) total work done, or assuming constant-p, O(N) of work per 2-way SIMD merge (with a large "p" providing an arbitrarily large speedup: but in practice is probably limited to 1024 for modern GPU architectures. Since modern GPUs only really "gang up" into 1024-CUDA thread blocks / workgroups efficiently)
Still looking for a microcontroller that can fit on my wrist [watch-like form factor] with built in microphone, deep sleep, quick wake, and quick push audio to wifi or BLE...
