XPost: alt.ufo.reports   
      
   In a prev post I looked at what the data shows about ufo sighting   
   distribution across the US vis a vis military bases.   
      
   It seems sighting density (e.g. per mn capita local pop) drops off in   
   areas with more army bases, but drops off even more in regions with   
   lots of AF bases.   
      
   Kinda rational behavior, you might think.   
      
   In a doc under prep for my UFO website I break that data down by UFO   
   type ("shape") -- something that might suggest which kind of sightings   
   respond most to presence of military bases and which least.   
      
   This may indicate which of the core sightings that corresp to the kind   
   of "aerial vehicles" seen hovering over the Pentagon or buzzing around   
   nr carrier groups off the Cal coast believe they are best armed or   
   armored and which least.   
      
   We can also presume some kinds of vehicles are more disposable that   
   others as far as (whatever/whomever) are concerned.   
      
   But today I want to look at data that might suggest how the UAP see us.   
      
   If UAP drop off near military bases, is the drop off linear with   
   distance, the square of the distance or what?   
      
   The form of the function can give us clues what UAP are likely avoiding.   
      
   If they don't want to tangle with military aircraft -- whether they can   
   easily out-perform or suddenly go radar invisible or not -- then the   
   flight time from the air base to current position should appear in the   
   function. I.e. the sighting density should fall off around 1/r.   
      
   If the UAP are concerned about e.g. running into regular patrols then   
   maybe the density function will drop off as 1/r^2.   
      
   If we screw around enough with the numbers can we figure out which?   
   Or do we get a surprising result?   
      
   First off we have to calculate the "sighting density" for each region.   
   The US is by happy coincidence a gold mine to data scientists because   
   it's divided up into well-documented states.   
      
   So we can take e.g. the NUFORC data and chop it up into number of   
   sightings since 1900 per mn capita of current state population.  I   
   also tend to adjust the numbers to account for "weekday correlations"   
   that seem to indicate people are WAY more likely to see something   
   later in the week than earlier in the week. Sat is often the favored   
   date for sightings and Mon the least favored. For some reason. ;)   
      
   Dropping in all these adjustments I get the following sighting density   
   for each state:   
      
   State	Sightings 1900-2020 per mn (current) state pop   
   AK	828.4   
   AL	234.6   
   AR	276.7   
   AZ	522.8   
   CA	337.8   
   CO	461.0   
   CT	482.7   
   DE	385.6   
   FL	366.9   
   GA	204.5   
   HI	388.8   
   IA	310.3   
   ID	686.0   
   IL	283.6   
   IN	302.5   
   KS	328.9   
   KY	302.5   
   LA	199.7   
   MA	357.6   
   MD	263.2   
   ME	774.6   
   MI	331.0   
   MN	390.0   
   MO	392.6   
   MS	205.9   
   MT	861.9   
   NC	280.7   
   ND	290.2   
   NE	280.9   
   NV	436.5   
   NY	256.4   
   OH	385.3   
   OK	274.5   
   OR	699.9   
   PA	392.3   
   RI	639.0   
   SC	494.0   
   SD	447.4   
   TN	273.7   
   TX	170.7   
   UT	431.9   
   VA	288.9   
   VT	927.1   
   WA	731.9   
   WI	396.1   
   WV	430.3   
   WY	528.6   
      
   (Interestingly you can see density increases north and toward the   
   E&W coasts, particularly the Pacific, indicating perhaps the "source" of   
   some chunk of UFO's is the Arctic ocean. There are quite a bit of data that   
   point in similar direction).   
      
   We can now take the distribution of military bases state by state to   
   produce a theoretical sighting density function based on UFO's trying   
   to optimize the threat they might perceive from (whatever) associated   
   with those bases.   
      
   I.e. we assume   
   sightingDensity(state) =   
   		A   
   		- B * sum(overStates) #airbases/dist^r   
   		- C * sum(overStates) #armybases/dist^r   
      
   IOW the sighting density for a given state tends to be uniform over   
   the entire US apart from subtractions related to perceived threats   
   from air and army bases in all other states.   
      
   We then need to run a bunch of models varying "r" and see which is "best".   
      
   How well does the model fit and what does it say about the UAP?   
      
   Here's part of the summary output from my model runs:   
      
      
   "r"    	    R2 of model ("explanation power" == proportion of variation   
   	       	  	covered by the model)   
   0.549        0.56256	<-best model   
   0.578        0.56202   
   0.583        0.56179   
   0.584        0.56174   
   0.510        0.56138   
   0.608        0.56010   
   0.438        0.55405   
   0.430        0.55287   
   0.429        0.55272   
   0.669        0.55184   
   0.707        0.54372   
   0.374        0.54291   
   0.314        0.52944   
   ...   
   2.900        0.15629   
   2.956        0.15597   
   2.972        0.15588   
   2.974        0.15587   
   2.982        0.15583	<-worst model   
      
      
   It seems the BEST model has an r approx the sqrt of the distance!   
   Certainly r==1 (UAP avoiding intercept from scrambled military   
   aircraft) and r==2 (UAP avoiding daily air patrols) are nowhere near   
   as good as r ~= .6.   
      
   (The relatively high R2 suggests the proportion of sightings of   
   random lights-in-the-sky and other flying knickknacks may be much   
   higher than the estimated "10% of sightings are interesting").   
      
   But what the heck does r ~= .6 indicate the UAP are avoiding?   
      
   What kind of thing maybe travels over a distance according to the sqrt   
   of the distance?   
      
   One possibility: a continuously accelerating missile.   
      
   We've seen some well-documented cases of UAP zipping around pulling   
   40g turns and supercruising at 100 ft at 1 km/s. But some missiles go   
   (last time I was in school) at 1.5 km/s and tend to start slow and   
   just keep accelerating until they hit something.   
      
   So it seems the UAP are being defensive. Despite apparent super air   
   performance and super stealth capability, they are mostly avoiding air   
   bases and apparently mostly concerned about being bothered by g2a missiles.   
      
   Again, it's probably instructive to break this calculation down by   
   sighting type. Do the triangles behave more defensive than the cylinders?   
      
   I'll leave that as an exercise for the energetic reader.   
      
   --   
   Weather Underground @wunderground 12 Dec 2020 0:31Z   
   The Mpemba Effect is a phenomenon in which hot water freezes faster   
   than cold water. And when you get the setting sun as a backdrop, you   
   get something that looks spectacular pic.twitter.com/58FIB3V5nd   
      
   Geminid meteor shower dazzles night skies   
   BBC News, 14 Dec 2020 11:25Z   
      
   'New variant' of coronavirus identified in England   
   BBC News, 14 Dec 2020 17:24Z   
   The new strain may be growing faster in some parts of the country, Health   
   Secretary tells MPs.   
      
   New York Nurse First Person To Receive Covid Vaccine In US   
   NDTV, 14 Dec 2020 15:24Z   
   A nurse in New York became the first person in the United States to receive   
   the coronavirus vaccine Mon.   
      
   Gmail, YouTube, Google Docs, and other Google services hit by massive outage   
   The Verge, 14 Dec 2020 13:23Z   
   Multiple Google services and websites including YouTube, Gmail, Google   
   Assistant, and Google Docs have been hit with a widespread outage.   
   DownDetector ...   
      
   Bill Gates says US entering worse phase of COVID pandemic and predicts   
   lockdowns will last into 2022   
   [#unreliablesource]   
   Daily Mail, 14 Dec 2020 13:15Z   
   Bill Gates offered his predictions during an interview on Sun as the US   
   set new records for new cases, hospitalizations and deaths over a seven-day   
   period.   
      
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   [continued in next message]   
      
   --- SoupGate-Win32 v1.05   
    * Origin: you cannot sedate... all the things you hate (1:229/2)