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Rafael Ayala

Publications and source records attributed to Rafael Ayala.

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The number of labeled partial orders and topologies on 19 points

We report the exact value of the number of labeled partially ordered sets (equivalently, labeled $T_0$ topologies) on 19 points, P(19) = 646099441937791106493755218560442089979, a 39-digit integer extending OEIS A001035, whose largest previously computed term was P(18) (Brinkmann and McKay). By the Stirling transform we also obtain the number of labeled topologies on 19 points, A000798(19) = 689054943207246404281592791142107048261. Our route is the Erné-Stege moment reduction, which expresses P(19) through a few sums of antichain counts over the posets on at most 16 points. All of these are available from the posets on at most 15 points (whose number is catalogued, and which standard software generates on demand), except a single moment over the 16-point posets. That moment is obtained not by enumerating the 16-point posets but by inserting a single element into the 15-point ones, with a per-parent kernel that advances the sum at the cost of computing the parent's own antichain count. The result passes several independent checks, among them the residue predicted by the modular periodicity of A001035 and the recovery from the same sweep of the known count P(16) and the Erné-Stege moments G(16,1) and G(16,2). We also report the moments G(16,3) and G(16,4), the latter an input to the analogous computation for 20 points.

math.CO

Automatizing a non-scripting TPS for optimizing clinical workflow and re-optimization of IMRT/VMAT plans

A toolkit for interacting with the Elekta Monaco (Clements et al 2018) treatment planning system (TPS) has been designed without the need of a dedicated Application Programming Interface (API). It provides automatization of the radiotherapy planning procedure allowing the TPS to calculate or optimize plans during non-working hours. The software is based on an open source library that mimics human interaction with Microsoft Windows applications. The impact on the clinical workflow is important not only providing better efficiency but also increasing treatment quality. Successful inverse planning depends on the tweaking of many parameters that can be explored more exhaustively with this tool without significantly increasing planning time. Furthermore, a simple way to analyze calculated plans and the impact of the cost functions in the optimization has been implemented. The Autoflow sequence has been developed allowing fully automated planning; it works analyzing the relative impact of different cost functions in the optimization and modifying constraints accordingly. It also changes segmentation parameters to fit more complex treatments. A prostate study has been conducted, comparing automatically created plans with already treated ones. The Autoflow sequence has proved to reduce dose to organs at risk with a negligible decrease in target coverage. Implementing this tool has enabled an efficient use of the TPS, allowing research and clinical use to coexist in a friendly way. It is surely of great use in clinics with little resources. It provides consistency and efficiency throughout the treatment planning process.

physics.med-ph