IMRT QA using machine learning: A multi-institutional validation.

PurposeTo validate a machine learning approach to Virtual intensity-modulated radiation therapy (IMRT) quality assurance (QA) for accurately predicting gamma passing rates using different measurement approaches at different institutions.MethodsA Virtual IMRT QA framework was previously developed using a machine learning algorithm based on 498 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3 mm with 10% threshold at Institution 1. An independent set of 139 IMRT measurements from a different institution, Institution 2, with QA data based on portal dosimetry using the same gamma index, was used to test the mathematical framework. Only pixels with ≥10% of the maximum calibrated units (CU) or dose were included in the comparison. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input.ResultsThe methodology predicted passing rates within 3% accuracy for all composite plans measured using diode-array detectors at Institution 1, and within 3.5% for 120 of 139 plans using portal dosimetry measurements performed on a per-beam basis at Institution 2. The remaining measurements (19) had large areas of low CU, where portal dosimetry has a larger disagreement with the calculated dose and as such, the failure was expected. These beams need further modeling in the treatment planning system to correct the under-response in low-dose regions. Important features selected by Lasso to predict gamma passing rates were as follows: complete irradiated area outline (CIAO), jaw position, fraction of MLC leafs with gaps smaller than 20 or 5 mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted average irregularity factor, and duty cycle.ConclusionsWe have demonstrated that Virtual IMRT QA can predict passing rates using different measurement techniques and across multiple institutions. Prediction of QA passing rates can have profound implications on the current IMRT process

Switching between dynamic states in intermediate-length Josephson junctions

The appearance of zero-field steps (ZFS’s) in the current-voltage characteristics of intermediate-length overlap-geometry Josephson tunnel junctions described by a perturbed sine-Gordon equation (PSGE) is associated with the growth of parametrically excited instabilities of the McCumber background curve (MCB). A linear stability analysis of a McCumber solution of the PSGE in the asymptotic linear region of the MCB and in the absence of magnetic field yields a Hill’s equation which predicts how the number, locations, and widths of the instability regions depend on the junction parameters. A numerical integration of the PSGE in terms of truncated series of time-dependent Fourier spatial modes verifies that the parametrically excited instabilities of the MCB evolve into the fluxon oscillations characteristic of the ZFS’s. An approximate analysis of the Fourier mode equations in the presence of a small magnetic field yields a field-dependent Hill’s equation which predicts that the major effect of such a field is to reduce the widths of the instability regions. Experimental measurements on Nb-NbxOy-Pb junctions of intermediate length, performed at different operating temperatures in order to vary the junction parameters and for various magnetic field values, verify the physical existence of switching from the MCB to the ZFS’s. Good qualitative, and in many cases quantitative, agreement between analytic, numerical, and experimental results is obtained

Resonant flux motion and I-V -characteristics in frustrated Josephson junctions

We describe the dynamics of fluxons moving in a frustrated Josephson junction with p, d, and f-wave symmetry and calculate the I-V characteristics. The behavior of fluxons is quite distinct in the long and short length junction limit. For long junctions the intrinsic flux is bound at the center and the moving integer fluxon or antifluxon interacts with it only when it approaches the junction's center. For small junctions the intrinsic flux can move as a bunched type fluxon introducing additional steps in the I-V characteristics. Possible realization in quantum computation is presented.Comment: 21 pages, 8 figure

Field-induced electronic phase separation in a cuprate high temperature superconductor

We present a combined neutron diffraction (ND) and high-field muon spin rotation ($\mu$SR) study of the magnetic and superconducting phases of the high-temperature superconductor La$_{1.94}$Sr$_{0.06}$CuO$_{4+y}$ ($T_{c} = 38$~K). We observe a linear dependence of the ND signal from the modulated antiferromagnetic order (m-AFM) on the applied field. The magnetic volume fraction measured with $\mu$SR increases linearly from 0\% to $\sim$40\% with applied magnetic field up to 8~T. This allows us to conclude, in contrast to earlier field-dependent neutron diffraction studies, that the long-range m-AFM regions are induced by an applied field, and that their ordered magnetic moment remains constant

PHANGS-MUSE: Detection and Bayesian classification of ~40000 ionised nebulae in nearby spiral galaxies

In this work, we present a new catalogue of >40000 ionised nebulae distributed across the 19 galaxies observed by the PHANGS-MUSE survey. The nebulae have been classified using a new model-comparison-based algorithm that exploits the odds ratio principle to assign a probabilistic classification to each nebula in the sample. The resulting catalogue is the largest catalogue containing complete spectral and spatial information for a variety of ionised nebulae available so far in the literature. We developed this new algorithm to address some of the limitations of the traditional classification criteria, such as their binarity, the sharpness of the involved limits, and the limited amount of data they rely on for the classification. The analysis of the catalogue shows that the algorithm performs well when selecting H II regions. We can recover their luminosity function, and its properties are in line with what is available in the literature. We also identify a rather significant population of shock-ionised regions (mostly composed of supernova remnants), an order of magnitude larger than any other homogeneous catalogue of supernova remnants currently available in the literature. The number of supernova remnants we identify per galaxy is in line with results in our Galaxy and other very nearby sources. However, limitations in the source detection algorithm result in an incomplete sample of planetary nebulae, even though their classification seems robust. Finally, we demonstrate how applying a correction for the contribution of the diffuse ionised gas to the nebulae's spectra is essential to obtain a robust classification of the objects and how a correct measurement of the extinction using DIG-corrected line fluxes prompts the use of a higher theoretical Ha/Hb ratio (3.03) than what is commonly used when recovering the E(B-V) via the Balmer decrement technique in massive star-forming galaxies.Comment: 58 pages, 46 figures. Paper accepted for pubblications in A&A. The catalogue will be available via the CDS or at the following link: http://dx.doi.org/10.11570/23.000

Guardians of the Galaxy: Content Moderation in the InterPlanetary File System

The InterPlanetary File System (IPFS) is one of the largest platforms in the growing “Decentralized Web”. The increasing popularity of IPFS has attracted large volumes of users and content. Unfortunately, some of this content could be considered “problematic”. Content moderation is always hard. With a completely decentralized infrastructure and administration, content moderation in IPFS is even more difficult. In this paper, we examine this challenge. We identify, characterize, and measure the presence of problematic content in IPFS (e.g. subject to takedown notices). Our analysis covers 368,762 files. We analyze the complete content moderation process including how these files are flagged, who hosts and retrieves them. We also measure the efficacy of the process. We analyze content submitted to denylist, showing that notable volumes of problematic content are served, and the lack of a centralized approach facilitates its spread. While we identify fast reactions to takedown requests, we also test the resilience of multiple gateways and show that existing means to filter problematic content can be circumvented. We end by proposing improvements to content moderation that result in 227% increase in the detection of phishing content and reduce the average time to filter such content by 43%

Quantifying the energetics of molecular superbubbles in PHANGS galaxies

Star formation and stellar feedback are interlinked processes that redistribute energy and matter throughout galaxies. When young, massive stars form in spatially clustered environments, they create pockets of expanding gas termed superbubbles. As these processes play a critical role in shaping galaxy discs and regulating the baryon cycle, measuring the properties of superbubbles provides important input for galaxy evolution models. With wide coverage and high angular resolution (50-150 pc) of the PHANGS-ALMA $^{12}$CO (2-1) survey, we can now resolve and identify a statistically representative number of superbubbles with molecular gas in nearby galaxies. We identify superbubbles by requiring spatial correspondence between shells in CO with stellar populations identified in PHANGS-HST, and combine the properties of the stellar populations with CO to constrain feedback models and quantify their energetics. We visually identify 325 cavities across 18 PHANGS-ALMA galaxies, 88 of which have clear superbubble signatures (unbroken shells, central clusters, kinematic signatures of expansion). We measure their radii and expansion velocities using CO to dynamically derive their ages and the mechanical power driving the bubbles, which we use to compute the expected properties of the parent stellar populations driving the bubbles. We find consistency between the predicted and derived stellar ages and masses of the stellar populations if we use a supernova blast wave model that injects energy with a coupling efficiency of 10%, whereas continuous models fail to explain stellar ages we measure. Not only does this confirm molecular gas accurately traces superbubble properties, but it also provides key observational constraints for superbubble models. We also find evidence that the bubbles sweep up gas as they expand and speculate that these sites have the potential to host new generations of stars.Comment: 21 pages, 15 figures, 3 tables. Accepted to A&A. Abstract abridged for arXi

Mutations in ASXL1 are associated with poor prognosis across the spectrum of malignant myeloid diseases

The ASXL1 gene is one of the most frequently mutated genes in malignant myeloid diseases. The ASXL1 protein belongs to protein complexes involved in the epigenetic regulation of gene expression. ASXL1 mutations are found in myeloproliferative neoplasms (MPN), myelodysplastic syndromes (MDS), chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML). They are generally associated with signs of aggressiveness and poor clinical outcome. Because of this, a systematic determination of ASXL1 mutational status in myeloid malignancies should help in prognosis assessment