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Abstract Purpose. To investigate the relationship between spatial parotid dose and the risk of xerostomia in patients undergoing head-and-neck cancer radiotherapy, using machine learning (ML) methods.Methods. Prior to conducting voxel-based ML analysis of the spatial dose, two steps were taken: (1) The parotid dose was standardized through deformable image registration to a reference patient; (2) Bilateral parotid doses were regrouped into contralateral and ipsilateral portions depending on their proximity to the gross tumor target. Individual dose voxels were input into six commonly used ML models, which were tuned with ten-fold cross validation: random forest (RF), ridge regression (RR), support vector machine (SVM), extra trees (ET), k-nearest neighbor (kNN), and naïve Bayes (NB). Binary endpoints from 240 patients were used for model training and validation: 0 (N = 119) for xerostomia grades 0 or 1, and 1 (N = 121) for grades 2 or higher. Model performance was evaluated using multiple metrics, including accuracy, F₁score, areas under the receiver operating characteristics curves (auROC), and area under the precision–recall curves (auPRC). Dose voxel importance was assessed to identify local dose patterns associated with xerostomia risk.Results. Four models, including RF, SVM, ET, and NB, yielded average auROCs and auPRCs greater than 0.60 from ten-fold cross-validation on the training data, except for a lower auROC from NB. The first three models, along with kNN, demonstrated higher accuracy and F₁scores. A bootstrapping analysis confirmed test uncertainty. Voxel importance analysis from kNN indicated that the posterior portion of the ipsilateral gland was more predictive of xerostomia, but no clear patterns were identified from the other models.Conclusion. Voxel doses as predictors of xerostomia were confirmed with some ML classifiers, but no clear regional patterns could be established among these classifiers, except kNN. Further research with a larger patient dataset is needed to identify conclusive patterns. 

High-quality and brilliant structural colors have been successfully produced using solution-based process over the past decade. 

Abstract Iridescent color-shift pigments have been used in some industrial applications, e.g., for cosmetics and packaging. To achieve environmental-friendly and lasting color, thin-film interference is used to generate structural color. By maximizing the refractive index (RI) difference between the thin films (i.e., using an ultralow RI film), super-iridescent structural color can be produced. While the lowest refractive index of a naturally occurring solid dielectric is close to 1.37 (i.e., MgF₂), we synthesized highly porous dielectric SiO₂aerogel to achieve ultralow-RI (n ~ 1.06) and demonstrated a high-refractive index/low-refractive index/absorber (HLA) trilayer structural color. The achieved structural color is highly iridescent and capable of tracing a near-closed loop in CIE color space. By tuning the refractive index, thickness, and geometry of the aerogel layer, we control the reflection dip’s shape, therefore producing a wide range of vivid and iridescent colors. 

Abstract In nuclear collisions at RHIC energies, an excess of$$\Omega$$ $\Omega$hyperons over$$\bar{\Omega }$$ $\overline{\Omega }$is observed, indicating that$$\Omega$$ $\Omega$has a net baryon number despitesand$$\bar{s}$$ $\overline{s}$quarks being produced in pairs. The baryon number in$$\Omega$$ $\Omega$may have been transported from the incident nuclei and/or produced in the baryon-pair production of$$\Omega$$ $\Omega$with other types of anti-hyperons such as$$\bar{\Xi }$$ $\overline{\Xi }$. To investigate these two scenarios, we propose to measure the correlations between$$\Omega$$ $\Omega$andKand between$$\Omega$$ $\Omega$and anti-hyperons. We use two versions, the default and string-melting, of a multiphase transport (AMPT) model to illustrate the method for measuring the correlation and to demonstrate the general shape of the correlation. We present the$$\Omega$$ $\Omega$-hadron correlations from simulated Au+Au collisions at$$\sqrt{s_\text{NN}} = 7.7$$ $\sqrt{s_{\text{NN}}}=7.7$and$$14.6 \ \textrm{GeV}$$ $14.6\text{GeV}$and discuss the dependence on the collision energy and on the hadronization scheme in these two AMPT versions. These correlations can be used to explore the mechanism of baryon number transport and the effects of baryon number and strangeness conservation on nuclear collisions.