Hi, 

The present work is aimed to show how bayesian inference methods can be used to infer (= to assess) the probabilility that a person detected infected by the SARS-Cov2  has to die (remark I did not write "has to die if it" because one never be sure of the reason of the death).
A lot of details are avaliable in the attached pdf file (I tried to be pedagogic enough so that the people not familiar with bayesian inference can get a global understanding of the subject, many links are provided for quick access to the different notions).

In particular, I explain why simple mathematics cannot provide a reliable estimate of this probability of death (sometimes referred to as the "death rate") as long as the epidemic continues to spread.

Even if the approach presented here is rather original, this is not the purpose of this post. 
Since a long time I had in mind to post here an application concerning bayesian methods. The CoVid19 outbreak has only provided me with the most high-profile topic to do so.
I will say no more about the inference procedure itself (all the material is given in the attached pdf file) and I will only concentrate on the MAPLE implementation of the solution algorithm.

Bayesian Inference uses generally simple algorithms such as MCMC (Markov Chain Monte Carlo) or ABC (Approximate Bayesian Computation) to mention a few, and their corresponding pseudo code writes generally upon a few tens of lines.
This is something I already done with other languages but I found the task comparatively more difficult with Maple. Probably I was to obsess not to code in Maple as you code in Matlab or R for instance.
At the very end the code I wrote is rather slow, this because of the allocated memory size it uses.
In a question I posed weeks ago (How can I prevent the creation of random variables...) Preben gave a solution to limit the burst of the memory: the trick works well but I'm still stuked with memory size problems (Acer also poposed a solution but I wasn't capable to make it works... maybe I was too lazzy to modify deeply my code).

Anyway, the code is there, in case anyone would like to take up the challenge to make it more efficient (in which case I'll take it).

Note 1: this code contains a small "Maplet" to help you choose any country in the data file on which you would like to run the inference.
Note 2: Be careful: doing statistics, even bayesian statistics, needs enough data: some countries have history records ranging over a few days , or no recorded death at all; infering something from so loos date will probably be disappointing

The attached files:

• The pdf file is the "companion document" where all or most of it is explained.It has been written a few days ago for another purpose and the results it presents were not ontained from the lattest data (march 21, 2020 coronavirus)
• xls files are data files, they were loaded yesterday (march 28, 2020) from here coronavirus
• the mw file... well, I guess you know what it is.
   

Bayesian_inference.pdf

total-cases-covid-19_NF.xls

total-deaths-covid-19_NF.xls

Bayesian_Inference_ABC+MCMC_NF_2.mw

The following puzzle prompted me to write this post: "A figure is drawn on checkered paper that needs to be cut into 2 equal parts (the cuts must pass along the sides of the squares.)" (parts are called equal if, after cutting, they can be superimposed on one another, that is, if one of them can be moved, rotated and (if need to) flip so that they completely coincide) (see the first picture below). 
I could not solve it manually and wrote a procedure called  CutTwoParts  that does this automatically (of course, this procedure applies to other similar puzzles). This procedure uses my procedure  AreIsometric  published earlier  https://www.mapleprimes.com/posts/200157-Testing-Of-Two-Plane-Sets-For-Isometry  (for convenience, I have included its text here). In the procedure  CutTwoParts  the figure is specified by the coordinates of the centers of the squares of which it consists).

I advise everyone to first try to solve this puzzle manually in order to feel its non-triviality, and only then load the worksheet with the procedure for automatic solution.


For some reason, the worksheet did not load and I was only able to insert the link.

Cuttings.mw



 

With this application our students of science and engineering in the areas of physics will check the first condition of balance using Maple technology. Only with entering mass and angles we obtain graphs and data for a better interpretation.

First_equilibrium_condition.zip

Lenin AC

Ambassador of Maple

So here's something silly but cool you can do with Maple while you're "working" from home.

• Record a few seconds of your voice on a microphone that's close to your mouth (probably using a headset). This is your dry audio.
• On your phone, record a single clap of your hands in an enclosed space, like your shower cubicle or a closet. Trim this audio to the clap, and the reverb created by your enclosed space. This is your impulse response.
• Send both sound files to whatever computer you have Maple on.
• Using AudioTools:-Convolution, convolve the dry audio with the impulse response . This your wet audio and should sound a little bit like your voice was recorded in your enclosed space.

Here's some code. I've also attached my dry audio, an impulse response recorded in my shower (yes, I stood inside my shower, closed the door, and recorded a single clap of my hands on my phone), and the resulting wet audio.

with( AudioTools ):
dry_audio := Read( "MaryHadALittleLamb_sc.wav" ):
impulse_response := Read( "clap_sc.wav" ):
wet_audio := Normalize( Convolution( dry_audio, impulse_response ) ):
Write("wet_audio.wav", wet_audio );

A full Maple worksheet is here.

AudioSamplesForReverb.zip

Hi,

Two weeks ago, I started loading data on the CoVid19 outbreak in order to understand, out of any official communication from any country, what is really going on.

From february 29 to march 9 these data come from https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ and from 10 march until now from https://www.worldometers.info/coronavirus/#repro.In all cases the loading is done manually (copy-paste onto a LibreOffice spreadsheet plus correction and save into a xls file) for I wasn't capable to find csv data (csv data do exist here https://github.com/CSSEGISandData/COVID-19, by they end febreuary 15th).
So I copied-pasted the results from the two sources above into a LibreOffice spreadsheet, adjusted the names of some countries for they appeared differently (for instance "United States" instead of "USA"), removed the unnessary commas and saved the result in a xls file.

I also used data from https://www.worldometers.info/world-population/population-by-country/ to get the populations of more than 260 countries around the world and, finally, csv data from https://ourworldindata.org/coronavirus#covid-19-tests to get synthetic histories of confirmed and death cases (I have discovered this site only yesterday evening and I think it could replace all the data I initially loaded).

The two worksheet here are aimed to exploratory and visualization only.
An other one is in progress whose goal is to infer the true death rate (also known as CFR, Case Fatality Rate).

No analysis is presented, if for no other reason than that the available data (except the numbers of deaths) are extremely dependent on the testing policies in place. But some features can be drawn from the data used here.
For instance, if you select country = "China" in file Covid19_Evolution_bis.mw, you will observe very well known behaviour which is that the "Apparent Death Rate", I defined as the ratio of the cumulated number of death at time t by the cumulatibe number of confirmed cases at the same time, is always an underestimation of the death rate one can only known once the outbreak has ended. With this in mind, changing the country in this worksheet from China to Italy seems to lead to frightening  scary interpolations... But here again, without knowing the test policy no solid conclusion can be drawn: maybe Italy tests mainly elder people with accute symptoms, thus the huge "Apparent Death Rate" Italy seems to have?


The work has been done with Maple 2015 and some graphics can be improved if a newer version is used (for instance, as Maple 2015 doesn't allow to change the direction of tickmarks, I overcome this limitation by assigning the date to the vertical axis on some plots).
The second Explore plot could probably be improved by using newer versions or Maplets or Embeded components.

Explore data from https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ and https://www.worldometers.info/coronavirus/#repro
Files to use
Covid19_Evolution.mw
Covid19_Data.m.zip
Population.xls

Explore data from  https://ourworldindata.org/coronavirus#covid-19-tests
Files to use
Covid19_Evolution_bis.mw
daily-deaths-covid-19-who.xls
total-cases-covid-19-who.xls
Population.xls

I would be interested by any open collaboration with people interested by this post (it's not in my intention to write papers on the subject, my only motivation is scientific curiosity).

Playing mini-golf recently, I realized that my protractor can only help me so far since it can't calculate the speed of the swing needed.  I decided a more sophisticated tool was needed and modeled a trick-shot in MapleSim.

To start, I laid out the obstacles, the ball and club, the ground, and some additional visualizations in the MapleSim environment.

When running the simulation, my first result wasn't even close to the hole (similar to when I play in real life!).

The model clearly needed to be optimized. I went to the Optimization app in MapleSim (this can be found under Add Apps or Templates  on the left hand side).

Inside the app I clicked "Load System" then selected the parameters I wanted to optimize.

For this case, I'm optimizing 's' (the speed of the club) and 'theta' (the angle of the club). For the Objective Function I added a Relative Translation Sensor to the model and attached a probe to the Vector Norm of the output.

Inside the app, I switched to the Objective Function section.  Selecting Probes, I added the new probe as the Objective Function by giving it a weight of 1.

Scrolling down to "Execute Parameter Optimization", I checked the "Use Global Optimization Toolbox" checkbox, and clicked Run Parameter Optimization.

Following a run time of 120 seconds, the app returns the graph of the objective function. 

Below the plot, optimal values for the parameters are given. Plugging these back into the parameter block for the simulation we see that the ball does in fact go into the hole. Success!

Mini_golf_Global_Optimization.msim

Can you guess what P() produces, without executing it?

P:=proc(N:=infinity) local q,r,t,k,n,l,h, f;
q,r,t,k,n,l,h := 1,0,1,1,3,3,0:
while h<N do 
   if 4*q+r-t < n*t
   then f:=`if`(++h mod 50=0,"\n",`if`(h mod 10=0," ","")); printf("%d"||f,n);   
        q,r,t,k,n,l := 10*q,10*(r-n*t),t,k,iquo(10*(3*q+r),t)-10*n,l
   else q,r,t,k,n,l := q*k,(2*q+r)*l,t*l,k+1,iquo(q*(7*k+2)+r*l,t*l),l+2
   fi
od: NULL
end:

I hope you will like it (maybe after execution).

FeynmanDiagrams_and_the_Scattering_Matrix.PDF

FeynmanDiagrams_and_the_Scattering_Matrix.mw

FeynmanDiagrams_-_help_page.mw

Edgardo S. Cheb-Terrab
Physics, Differential Equations and Mathematical Functions, Maplesoft

with(plots):
S:=cat("Happy New Year 2020!   "$3):
N:=length(S): a:=0.77*Pi: h:=2*Pi/N:
display(seq(textplot([cos(a-k*h), sin(a-k*h),S[k+1]], 
        rotation=-Pi/2+a-k*h, 'font'=["times","roman",24]), k=0..N-4), axes=none);

When plotted, these parametric equations say "happy new year" (and were constructed with this worksheet)

Here is a little animation to wish all of you a Merry Christmas

FireWorks.mw

Here we simulate the motion of a container with a flat bottom that can slide on a horizontal surface subject to dry friction (Coulomb friction).  Installed inside the container is an ordinary mass/spring/damper system where the mass slides horizontally.  We impart an initial velocity to the container.  That sets the mass into motion which then affects the container's motion.  Under certain conditions the container will undergo a stick-slip motion which is evident in the simulation.

This simulation very roughly approximates the motion of a partially filled bucket of water that slides on the floor when kicked.  The idea arose in a discussoin with Carl Love and mmcdara:
https://www.mapleprimes.com/posts/211677-Mass-Spring-Conveyor-Belt-And-Dry-Friction

In the animation below, the container is shown in dark color when it slides against the floor, and light color when it sticks.

Worksheet: slosh.mw

Here is an animation of a mass-spring system where the mass slides horizontally on a steadily moving conveyor belt.

The contact between the block of mass and the belt is of the dry friction kind (Coulomb's friction). Consequently the block periodically sticks to the belt and moves forward with it until the force of the stretching spring overcomes the force of friction and yanks it back, making it to slip against the belt. In the animation the block is shown in a dark color while slipping, and a light color while sticking.

The fully executed Maple worksheet can be slow to load and requires a good deal of memory. Therefore I have attached two versions which are identical in all respects except that in one of them I have removed the Maple output to make is easy to load if your computer has limitations.

Download worksheet (no Maple output) block-sliding-on-conveyor-belt-stripped.mw

Doiwnload worksheet (with Maple output) (sorry, exceeds MaplePrime's size limit)

Here is two solutions with Maple of the problem A2 of  Putnam Mathematical Competition 2019 . The first solution is entirely based on the use of the  geometry  package; the second solution does not use this package. Since the triangle is defined up to similarity, without loss of generality, we can set its vertices  A(0,0) , B(1,0) , C(x0,y0)  and then calculate the parameters  x0, y0  using the conditions of the problem. 

Download Putnam.mw

Download putnam2019-b4.mw