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

Innovation, dynamic capabilities and family firms operating in an emerging economy

Drawing on the dynamic capabilities framework (DCF), this exploratory study examines family firms\u27 involvement in innovation practices, including reasons and ways to innovate. The cases of four family firms operating in an emerging economy (Uruguay) are investigated. Semi-structured, face-to-face and telephone interviews were conducted with owners and managers, and complemented with e-mail correspondence. Based on the imperative need to solve problems in their industry, firms\u27 managements were intensively involved in various innovative processes. These processes included quality improvements, responding to a dynamic and competitive business and consumer environment, and extending the life and survival of the family enterprise for future generations. Notably, the importance of sensing and learning in the form of identifying and assimilating key information, and seizing and applying such information to develop or adopt innovation, including new technologies, emerged strongly. The findings also highlight the usefulness of the DCF to understand firms\u27 integration, and transformation of learning

Quantum Dot in 2D Topological Insulator: The Two-channel Kondo Fixed Point

In this work, a quantum dot couples to two helical edge states of a 2D topological insulator through weak tunnelings is studied. We show that if the electron interactions on the edge states are repulsive, with Luttinger liquid parameter $K < 1$, the system flows to a stable two-channel fixed point at low temperatures. This is in contrast to the case of a quantum dot couples to two Luttinger liquid leads. In the latter case, a strong electron-electron repulsion is needed, with $K<1/2$, to reach the two-channel fixed point. This two-channel fixed point is described by a boundary Sine-Gordon Hamiltonian with a $K$ dependent boundary term. The impurity entropy at zero temperature is shown to be $\ln\sqrt{2K}$. The impurity specific heat is $C \propto T^{\frac{2}{K}-2}$ when $2/3 < K < 1$, and $C \propto T$ when $K<2/3$. We also show that the linear conductance across the two helical edges has non-trivial temperature dependence as a result of the renormalization group flow.Comment: 4+\epsilon page

Photonic Band Gaps in 3D Network Structures with Short-range Order

We present a systematic study of photonic band gaps (PBGs) in three-dimensional (3D) photonic amorphous structures (PAS) with short-range order. From calculations of the density of optical states (DOS) for PAS with different topologies, we find that tetrahedrally connected dielectric networks produce the largest isotropic PBGs. Local uniformity and tetrahedral order are essential to the formation of PBGs in PAS, in addition to short-range geometric order. This work demonstrates that it is possible to create broad, isotropic PBGs for vector light fields in 3D PAS without long-range order.Comment: 6 pages, 8 figure

Personal destination pattern analysis with applications to mobile advertising

Many researchers expect mobile advertising to be the killer application in mobile business. In this paper, we introduce a trajectory prediction algorithm called personal destination pattern analysis (P-DPA) to analyse the different destinations in various trajectories of an individual, and to predict a trajectory or a set of destinations that could be visited by that individual. The P-DPA algorithm works on an individual level. Every destination-pattern analysis is related to the self-history and the personal profile of a targeted individual, not on what others do. In addition, we developed a prototype system called SmartShopper. SmartShopper is a personal destination-pattern-aware pervasive system for mobile advertising in (outdoor and indoor) retail environments. The predicted destinations from the P-DPA algorithm will be used by SmartShopper to generate a list of relevant advertisements adapted to the personal profile of previous destinations of a targeted individual. We tested the destination prediction accuracy of the P-DPA algorithm with a synthetic dataset of a virtual mall and a real GPS dataset

Double scattering of light from biophotonic nanostructures with short-range order

We investigate the physical mechanism for color production by isotropic nanostructures with short-range order in bird feather barbs. While the primary peak in optical scattering spectra results from constructive interference of singly-scattered light, many species exhibit secondary peaks with distinct characteristic. Our experimental and numerical studies show that these secondary peaks result from double scattering of light by the correlated structures. Without an analog in periodic or random structures, such a phenomenon is unique for short-range ordered structures, and has been widely used by nature for non-iridescent structural coloration.Comment: 10 pages, 4 figure

The effects of PTSD treatment during pregnancy: systematic review and case study

Background: PTSD in pregnant women is associated with adverse outcomes for mothers and their children. It is unknown whether pregnant women with PTSD, or symptoms of PTSD, can receive targeted treatment that is safe and effective. Objective: The purpose of the present paper was to assess the effectiveness and safety of treatment for (symptoms of) PTSD in pregnant women. Method: A systematic review was conducted in accordance with the PRISMA guidelines in Pubmed, Embase, PsychINFO, and Cochrane. In addition, a case is presented of a pregnant woman with PTSD who received eye-movement desensitization and reprocessing (EMDR) therapy aimed at processing the memories of a previous distressing childbirth. Results: In total, 13 studies were included, involving eight types of interventions (i.e. trauma-focused cognitive behavioural therapy, exposure therapy, EMDR therapy, interpersonal psychotherapy, explorative therapy, self-hypnosis and relaxation, Survivor Moms Companion, and Seeking Safety Intervention). In three studies, the traumatic event pertained to a previous childbirth. Five studies reported obstetrical outcomes. After requesting additional information, authors of five studies indicated an absence of serious adverse events. PTSD symptoms improved in 10 studies. However, most studies carried a high risk of bias. In our case study, a pregnant woman with a PTSD diagnosis based on DSM-5 no longer fulfilled the criteria of PTSD after three sessions of EMDR therapy. She had an uncomplicated pregnancy and delivery. Conclusion: Despite the fact that case studies as the one presented here report no adverse events, and treatment is likely safe, due to the poor methodological quality of most studies it is impossible to allow inferences on the effects of any particular treatment of PTSD (symptoms) during pregnancy. Yet, given the elevated maternal stress and cortisol levels in pregnant women with PTSD, and the fact that so far no adverse effects on the unborn child have been reported associated with the application of trauma-focused therapy, treatment of PTSD during pregnancy is most likely safe