Algorithm and performance of a clinical IMRT beam-angle optimization system

This paper describes the algorithm and examines the performance of an IMRT beam-angle optimization (BAO) system. In this algorithm successive sets of beam angles are selected from a set of predefined directions using a fast simulated annealing (FSA) algorithm. An IMRT beam-profile optimization is performed on each generated set of beams. The IMRT optimization is accelerated by using a fast dose calculation method that utilizes a precomputed dose kernel. A compact kernel is constructed for each of the predefined beams prior to starting the FSA algorithm. The IMRT optimizations during the BAO are then performed using these kernels in a fast dose calculation engine. This technique allows the IMRT optimization to be performed more than two orders of magnitude faster than a similar optimization that uses a convolution dose calculation engine.Comment: Final version that appeared in Phys. Med. Biol. 48 (2003) 3191-3212. Original EPS figures have been converted to PNG files due to size limi

On Component Forces in Physics: A Pragmatic View

Do component forces exist? I argue that the answer lies in the affirmative, on historical and operational grounds

Graph Neural Networks as Gradient Flows: understanding graph convolutions via energy

Gradient flows are differential equations that minimize an energy functional and constitute the main descriptors of physical systems. We apply this formalism to Graph Neural Networks (GNNs) to develop new frameworks for learning on graphs as well as provide a better theoretical understanding of existing ones. We derive GNNs as a gradient flow equation of a parametric energy that provides a physics-inspired interpretation of GNNs as learning particle dynamics in the feature space. In particular, we show that in graph convolutional models (GCN), the positive/negative eigenvalues of the channel mixing matrix correspond to attractive/repulsive forces between adjacent features. We rigorously prove how the channel-mixing can learn to steer the dynamics towards low or high frequencies, which allows to deal with heterophilic graphs. We show that the same class of energies is decreasing along a larger family of GNNs; albeit not gradient flows, they retain their inductive bias. We experimentally evaluate an instance of the gradient flow framework that is principled, more efficient than GCN, and achieves competitive performance on graph datasets of varying homophily often outperforming recent baselines specifically designed to target heterophily.Comment: First two authors equal contribution; 39 page

The PTW microSilicon diode: Performance in small 6 and 15 MV photon fields and utility of density compensation

PURPOSE: We have experimentally and computationally characterized the PTW microSilicon 60023-type diode's performance in 6 and 15 MV photon fields ≥5 × 5 mm2 projected to isocenter. We tested the detector on- and off-axis at 5 and 15 cm depths in water, and investigated whether its response could be improved by including within it a thin airgap. METHODS: Experimentally, detector readings were taken in fields generated by a Varian TrueBeam linac and compared with doses-to-water measured using Gafchromic film and ionization chambers. An unmodified 60023-type diode was tested along with detectors modified to include 0.6, 0.8, and 1.0 mm thick airgaps. Computationally, doses absorbed by water and detectors’ sensitive volumes were calculated using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Detector response was characterized using K^{fdin, 4cm}_{Qclin, 4cm}, a factor that corrects for differences in the ratio of dose-to-water to detector reading between small fields and the reference condition, in this study 5 cm deep on-axis in a 4 × 4 cm2 field. RESULTS: The greatest errors in measurements of small field doses made using uncorrected readings from the unmodified 60023-type detector were over-responses of 2.6% ± 0.5% and 5.3% ± 2.0% determined computationally and experimentally, relative to the reading-per-dose in the reference field. Corresponding largest errors for the earlier 60017-type detector were 11.9% ± 0.6% and 11.7% ± 1.4% over-responses. Adding even the thinnest, 0.6 mm, airgap to the 60023-type detector over-corrected it, leading to under-responses of up to 4.8% ± 0.6% and 5.0% ± 1.8% determined computationally and experimentally. Further, Monte Carlo calculations indicate that a detector with a 0.3 mm airgap would read correctly to within 1.3% on-axis. The ratio of doses at 15 and 5 cm depths in water in a 6 MV 4 × 4 cm2 field was measured more accurately using the unmodified 60023-type detector than using the 60017-type detector, and was within 0.3% of the ratio measured using an ion chamber. The 60023-type diode's sensitivity also varied negligibly as dose-rate was reduced from 13 to 4 Gy min–1 by decreasing the linac pulse repetition frequency, whereas the sensitivity of the 60017-type detector fell by 1.5%. CONCLUSIONS: The 60023-type detector performed well in small fields across a wide range of beam energies, field sizes, depths, and off-axis positions. Its response can potentially be further improved by adding a thin, 0.3 mm, airgap

Classification of Systemic Lupus Erythematosus Using Raman Spectroscopy of Blood and Automated Computational Detection Methods: A Novel Tool for Future Diagnostic Testing

The aim of this study was to explore the proof of concept for using Raman spectroscopy as a diagnostic platform in the setting of systemic lupus erythematosus (SLE). We sought to identify unique Raman signatures in serum blood samples to successfully segregate SLE patients from healthy controls (HC). In addition, a retrospective audit was undertaken to assess the clinical utility of current testing platforms used to detect anti-double stranded DNA (dsDNA) antibodies (n = 600). We examined 234 Raman spectra to investigate key variances between SLE patients (n = 8) and HC (n = 4). Multi-variant analysis and classification model construction was achieved using principal component analysis (PCA), PCA-linear discriminant analysis and partial least squares-discriminant analysis (PLS-DA). We achieved the successful segregation of Raman spectra from SLE patients and healthy controls (p-value < 0.0001). Classification models built using PLS-DA demonstrated outstanding performance characteristics with 99% accuracy, 100% sensitivity and 99% specificity. Twelve statistically significant (p-value < 0.001) wavenumbers were identified as potential diagnostic spectral markers. Molecular assignments related to proteins and DNA demonstrated significant Raman intensity changes between SLE and HC groups. These wavenumbers may serve as future biomarkers and offer further insight into the pathogenesis of SLE. Our audit confirmed previously reported inconsistencies between two key methodologies used to detect anti-dsDNA, highlighting the need for improved laboratory testing for SLE. Raman spectroscopy has demonstrated powerful performance characteristics in this proof-of-concept study, setting the foundations for future translation into the clinical setting

'Word from the street' : when non-electoral representative claims meet electoral representation in the United Kingdom

Taking the specific case of street protests in the UK – the ‘word from the street’– this article examines recent (re)conceptualizations of political representation, most particularly Saward’s notion of ‘representative claim’. The specific example of nonelectoral claims articulated by protestors and demonstrators in the UK is used to illustrate: the processes of making, constituting, evaluating and accepting claims for and by constituencies and audiences; and the continuing distinctiveness of claims based upon electoral representation. Two basic questions structure the analysis: first, why would the political representative claims of elected representatives trump the nonelectoral claims of mass demonstrators and, second, in what ways does the ‘perceived legitimacy’ of the former differ from the latter

What is theoretical progress of science?

The epistemic conception of scientific progress equates progress with accumulation of scientific knowledge. I argue that the epistemic conception fails to fully capture scientific progress: theoretical progress, in particular, can transcend scientific knowledge in important ways. Sometimes theoretical progress can be a matter of new theories ‘latching better onto unobservable reality’ in a way that need not be a matter of new knowledge. Recognising this further dimension of theoretical progress is particularly significant for understanding scientific realism, since realism is naturally construed as the claim that science makes theoretical progress. Some prominent realist positions (regarding fundamental physics, in particular) are best understood in terms of commitment to theoretical progress that cannot be equated with accumulation of scientific knowledge