Dear volunteers,
We update you on the status of the project and how the simulations are going. In recent weeks the search algorithm has been improving the model very little. This indicates us that the optimization is close to be finished. Once this is complete we will pass to the validation phase which we will be done outside of DENIS (DENIS is not yet prepare for the required simulations).

The improvement obtained is very considerable (you can see the graph with the evolution of the error below and we hope that the validation results turn out well). It can be improved, but not all the error can be removed with the optimization (it requires other type of improvements in the model).

On the other hand, looking at the results, last week we started a new optimization by changing an aspect of it. In the initial search, if one of the markers was in the experimentally observed range, we did not allow the algorithm to search where that marker was outside of the experimental range (criterion of keeping at least those markers that were already in the experimental range). In the new search we are allowing it in the hope that even if some marker goes out, the overall behavior will improve. In this case, the uncertainty about the result is higher, but as you can see in the graph below, after the first iterations of the algorithm, the results are quite promising.

Sincerely,
Jesus.





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Estimados voluntarios:
Os actualizamos el estado del proyecto y cómo van las simulaciones. En las últimas semanas el algoritmo de búsqueda ha ido mejorando muy poco el modelo. Esto nos indica que está a punto de terminarse la optimización. Una vez que esto se complete, pasaremos a una fase de validación de la simulación que haremos fuera de DENIS (DENIS no está preparado para ello).

La mejoría obtenida es muy considerable y esperamos que los resultados de la validación salgan bien (podéis ver la gráfica con la evolución del error debajo). Todavía hay margen de mejora, pero no todo el error se puede eliminar en la optimización (requiere otro tipo de mejoras en el modelo).

Por otro lado, viendo los resultados, la semana pasada comenzamos una nueva optimización cambiando un aspecto de la misma. En la búsqueda inicial, si uno de los marcadores estaba en el rango observado experimentalmente, no permitíamos al algoritmo buscar donde ese marcador saliera del rango experimental (criterio de mantener en rango experimental al menos los que ya estaban). En la nueva búsqueda estamos permitiéndolo con la esperanza de que aunque algún marcador salga fuera, el comportamiento global mejore. En este caso la incertidumbre sobre el resultado es algo mayor, pero como podéis ver en la gráfica de debajo, tras las primeras iteraciones del algoritmo, los resultados son bastante prometedores.

Atentamente,
Jesús.

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Jesús Carro
Universidad San Jorge
@InSilicoHeart

Good to hear! If I understand correctly, algorithm explores more space than the neighbourhood of local attractors defined by the specific correlation of parameters (correct me if I'm wrong). It looks like the trend will be more smooth and probably will decrease the error. The next weeks will be very exciting!

Hi Marcin,
Yes, the algorithm now explores more space, but based on an polinomical aproximation of the behavior of the model. The polinomical aproximation within the trust region is fixed with all the simulations you send to us.

I am also looking forward to the results of the third iteration.

Best,
Jesús.

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Jesús Carro
Universidad San Jorge
@InSilicoHeart

Jesus, when will there be new work from your project?

Yesterday... but you are too fast getting the tasks...
Probably, we will send more tasks tomorrow

Best,
Jesús.

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Jesús Carro
Universidad San Jorge
@InSilicoHeart

Hi, Jesus

I hope WU to dance on Apple Silicon (macOS Ventura).

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Chamiu (ΦωΦ)

I wish there were a way to supply more work, and more evenly.

When work becomes available, usually once a week, my machine downloads about 100 tasks. I could make it get more, but that would risk failure to complete some on time, so that is not the answer. Alternatively, you could send out work twice a week, perhaps every three or four days. As I understand it, this is not practical either because you need the results from one batch of work before you can send out the next set of work.

Perhaps if you had two related projects, each could send out the same size work once a week, but 3 or 4 days apart, so you could be studying the results of one project while we volunteers could be working on the other. That would probably increase the amount of work you would have to do, of course, and that might be too much to ask for.

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Hi Jean-David,
This is exactly our idea. Little by little, we want to add more optimizations to mantain an stable load of work. Currently, we are running 3 versions of the model optimization (each one with an small variation on the options of the algorithm). One of the limitations is that the postprocessing of your results is done out of the server, and it requieres a manual step, so the three tend to be synchronized because even if one finishes earlier, if that happens at night or during the weekend, the post-processing is done at the same time. Yesterday we sent a lot of work (from the three of them), but I guess they won't last long :-).

I will publish an update of the results the next week (we are finishing the validation process of the first version of the optimization), and I will explain there the new versions we have started (the validation of the first one does not look good, so we will still need your help).

Best,
Jesús.

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Jesús Carro
Universidad San Jorge
@InSilicoHeart

I will publish an update of the results the next week (we are finishing the validation process of the first version of the optimization), and I will explain there the new versions we have started (the validation of the first one does not look good, so we will still need your help).

You will continue getting my help if you continue sending me work units. Currently I have little over 100 DENIS tasks in my machine waiting to go, and I process them four at a time. They seem to take about 65 minutes each on my main machine. And I notice the current batch on your machine is quite large, so I may get some of those too.

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