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Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method

The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the σ-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, g{sub p}(E{sub p}) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called “corrected EAM” (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients S{sub ij} are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature T{sub m} is plotted in terms of the cluster atom number N{sub at}. The standard N{sub at}{sup −1/3} linear dependence (Pawlow law) is observed for N{sub at} >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For N{sub at} <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

WE-A-17A-12: The Influence of Eye Plaque Design On Dose Distributions and Dose- Volume Histograms

Purpose: To investigate the effect of slot design of the model EP917 plaque on dose distributions and dose-volume histograms (DVHs). Methods: The dimensions and orientation of the slots in EP917 plaques were measured. In the MCNP5 radiation simulation geometry, dose distributions on orthogonal planes and DVHs for a tumor and sclera were generated for comparisons. 27 slot designs and 13 plaques were evaluated and compared with the published literature and the Plaque Simulator clinical treatment planning system. Results: The dosimetric effect of the gold backing composition and mass density was < 3%. Slot depth, width, and length changed the central axis (CAX) dose distributions by < 1% per 0.1 mm in design variation. Seed shifts in the slot towards the eye and shifts of the {sup 125} I-coated Ag rod within the capsule had the greatest impact on CAX dose distribution, increasing by 14%, 9%, 4%, and 2.5% at 1, 2, 5, and 10 mm, respectively, from the inner sclera. Along the CAX, dose from the full plaque geometry using the measured slot design was 3.4% ± 2.3% higher than the manufacturer-provided geometry. D{sub 10} for the simulated tumor, inner sclera, and outer sclera for the measured plaque was also higher, but 9%, 10%, and 20%, respectively. In comparison to the measured plaque design, a theoretical plaque having narrow and deep slots delivered 30%, 37%, and 62% lower D{sub 10} doses to the tumor, inner sclera, and outer sclera, respectively. CAX doses at −1, 0, 1, and 2 mm were also lower by a factor of 2.6, 1.4, 1.23, and 1.13, respectively. Conclusion: The study identified substantial sensitivity of the EP917 plaque dose distributions to slot design. However, it did not identify substantial dosimetric variations based on radionuclide choice ({sup 125}I, {sup 103}Pd, or {sup 131}Cs). COMS plaques provided lower scleral doses with similar tumor dose coverage.

60 APPLIED LIFE SCIENCES↗

SU-E-T-294: Dosimetric Analysis of Planning Phase Using Overlap Volume Histogram for Respiratory Gated Radiotherapy

Purpose: End-of-exhale (EOE) phase is generally preferred for gating window because tumor position is more reproducible. However, other gating windows might be more appropriate for dose distribution perspective. In this pilot study, we proposed to utilize overlap volume histogram (OVH) to search optimized gating window and demonstrated its feasibility. Methods: We acquired 4DCT of 10 phases for 3 lung patients (2 with a target at right middle lobe and 1 at right upper lobe). After structures were defined in every phase, the OVH of each OAR was generated to quantify the three dimensional spatial relationship between the PTV and OARs (bronchus, esophagus, heart and cord etc.) at each phase. OVH tells the overlap volume of an OAR according to outward distance from the PTV. Relative overlap volume at 20 mm outward distance from the PTV (ROV-20) was also defined as a metric for measuring overlap volume and obtained. For dose calculation, 3D CRT plans were made for all phases under the same beam angles and objectives (e.g., 95% of the PTV coverage with at least 100% of the prescription dose of 50 Gy). The gating window phase was ranked according to ROV-20, and the relationship between the OVH and dose distribution at each phase was evaluated by comparing the maximum dose, mean dose, and equivalent uniform dose of OAR. Results: OVHs showed noticeable difference from phase to phase, implying it is possible to find optimal phases for gating window. For 2 out of 3 patients (both with a target at RML), maximum dose, mean dose, and EUD increased as ROV-20 increased. Conclusion: It is demonstrated that optimal phases (in dose distribution perspective) for gating window could exist and OVH can be a useful tool for determining such phases without performing dose optimization calculations in all phases. This work was supported by the Radiation Technology R&D program (No. 2013M2A2A7043498) and the Mid-career Researcher Program (2012-007883) through the National Research Foundation (NRF) funded by the Ministry of Science, ICT & Future Planning (MSIP) of Korea.

60 APPLIED LIFE SCIENCES↗

SU-F-T-348: The Impact of Model Library Population On RapidPlan Based Dose-Volume Histograms (DVHs) Prediction for Rectal Cancer Patients Treated with Volumetric-Modulated Radiotherapy (VMAT)

Purpose: RapidPlan uses a library consisting of expert plans from different patients to create a model that can predict achievable dose-volume histograms (DVHs) for new patients. The goal of this study is to investigate the impacts of model library population (plan numbers) on the DVH prediction for rectal cancer patients treated with volumetric-modulated radiotherapy (VMAT) Methods: Ninety clinically accepted rectal cancer patients’ VMAT plans were selected to establish 3 models, named as Model30, Model60 and Model90, with 30,60, and 90 plans in the model training. All plans had sufficient target coverage and bladder and femora sparings. Additional 10 patients were enrolled to test the DVH prediction differences with these 3 models. The predicted DVHs from these 3 models were compared and analyzed. Results: Predicted V40 (Vx, percent of volume that received x Gy for the organs at risk) and Dmean (mean dose, cGy) of the bladder were 39.84±13.38 and 2029.4±141.6 for the Model30,37.52±16.00 and 2012.5±152.2 for the Model60, and 36.33±18.35 and 2066.5±174.3 for the Model90. Predicted V30 and Dmean of the left femur were 23.33±9.96 and 1443.3±114.5 for the Model30, 21.83±5.75 and 1436.6±61.9 for the Model60, and 20.31±4.6 and 1415.0±52.4 for the Model90.There were no significant differences among the 3 models for the bladder and left femur predictions. Predicted V40 and Dmean of the right femur were 19.86±10.00 and 1403.6±115.6 (Model30),18.97±6.19 and 1401.9±68.78 (Model60), and 21.08±7.82 and 1424.0±85.3 (Model90). Although a slight lower DVH prediction of the right femur was found on the Model60, the mean differences for V30 and mean dose were less than 2% and 1%, respectively. Conclusion: There were no significant differences among Model30, Model60 and Model90 for predicting DVHs on rectal patients treated with VMAT. The impact of plan numbers for model library might be limited for cancers with similar target shape.

60 APPLIED LIFE SCIENCES↗

SU-F-T-359: Incorporating Dose Volume Histogram Prediction Into Auto-Planning for Volumetric-Modulated Arc Therapy in Rectal Cancer

Purpose: To incorporate dose volume histogram (DVH) prediction into Auto-Planning for volumetric-modulated arc therapy (VMAT) treatment planning and investigate the benefit of this new technique for rectal cancer. Methods: Ninety clinically accepted VMAT plans for patients with rectal cancer were selected and trained in the RapidPlan for DVH prediction. Both internal and external validations were performed before implementing the prediction model. A new VMAT planning method (hybrid-VMAT) was created with combining the DVH prediction and Auto-Planning. For each new patient, the DVH will be predicted and individual DVH constrains will be obtained and were exported as the original optimization parameters to the Auto-Planning (Pinnacle3 treatment planning system, v9.10) for planning. A total of 20 rectal cancer patients previously treated with manual VMAT (manual-VMAT) plans were replanned using this new method. Dosimetric comparisons were performed between manual VMAT and new method plans. Results: Hybrid-VMAT shows similar PTV coverage to manual-VMAT in D2%, D98% and HI (p>0.05) and superior coverage in CI (p=0.000). For the bladder, the means of V40 and mean dose are 36.0% and 35.6Gy for hybrid-VMAT and 42% and 38.0Gy for the manual-VMAT. For the left (right) femur, the means of V30 and mean dose are 10.6% (11.6%) and 17.9Gy (19.2Gy) for the hybrid-VMAT and 25.6% (24.1%) and 27.3Gy (26.2Gy) for the manual-VMAT. The hybrid-VMAT has significantly improved the organs at risk sparing. Conclusion: The integration of DVH prediction and Auto-Planning significantly improve the VMAT plan quality in the rectal cancer radiotherapy. Our results show the benefit of the new method and will be further investigated in other tumor sites.

60 APPLIED LIFE SCIENCES↗

SU-F-T-454: Dose-Mass-Histogram Sensitivity to Anatomical Changes During Radiotherapy for HNSCC

Purpose: To determine the sensitivity of dose-mass-histogram (DMH) due to anatomical changes of head-and-neck squamous cell carcinoma (HNSCC) radiotherapy (RT). Methods: Eight patients undergoing RT treatment for HNSCC were scanned during the third and sixth week of RT. These second (CT2) and third (CT3) CTs were co-registered to the planning CT (CT1). Contours were propagated via deformable registration from CT1 and doses were re-calculated. DMHs were extracted for each CT set. DMH sensitivity was assessed by dose-mass indices (DMIs), which represent the dose delivered to a certain mass of and anatomical structure. DMIs included: dose to 98%, 95% and 2% of the target masses (PTV1, PTV2, and PTV3) and organs-at-risk (OARs): cord DMI2%, brainstem DMI2%, left- and right-parotid DMI2% and DMI50%, and mandible DMI2%. A two-tailed paired t-test was used to compare changes to DMIs in CT2 and CT3 with respect to CT1 (CT2/CT1 and CT3/CT1). Results: Changes to DMHs were found for all OARs and PTVs, but they were significant only for the PTVs. Maximum dose to PTVs increased significantly for CT2/CT1 in all three PTVs, but CT3/CT1 changes were only significantly different for PTV1 and PTV2. Dose coverage to the three PTVs was also significantly different, DMI98% was lower for both CT2/CT1 and CT3/CT1. DMI95% was significantly lower for PTV1 for CT2/CT1, PTV2 for CT2/CT1 and CT3/CT1, and PTV3 for CT3/CT1. Conclusion: Changes in anatomy significantly change dose-mass coverage for the planning targets, making it necessary to re-plan in order to maintain the therapeutic goals. Maximum dose to the PTVs increase significantly as RT progresses, which may not be problematic as long as the high dose remains in the gross tumor volume. Doses to OARs were minimally affected and the differences were not significant.

60 APPLIED LIFE SCIENCES↗

WE-FG-202-04: Decomposition of FDG-PET Based Differential Uptake Volume Histograms in Rectal Cancer Patients

Purpose: The goal of this study is to test the possible use of the analytical decomposition of differential uptake volume histograms (dUVHs) obtained from FDG-PET/CT data to isolate sub-volumes within a tumor known as biological target volumes (BTVs). Methods: : A retrospective study was conducted on a cohort of 20 histo-pathologically confirmed rectal adenocarcinoma patients having PET/CT scans for staging. All patients (T3N0) underwent pre-operative endorectal brachytherapy. After surgery, patients were restaged: 10 patients were T0N0 and 10 were restaged as remaining T3N0. The extent of the disease was sampled in order to create dUVHs; subsequently decomposed into the fewest number of analytical Gaussian functions. Results: With the assumption that each function fit corresponded to a single sub-volume within the tumor, six sub-volumes were found to consistently emerge. The first two sub-volumes were influenced by contouring and were not considered in the analysis. For the T3N0 population, abundances for volumes V3-V6 were 63.6%±11.3%, 25.7%±8.4%, 6.1%±4.9%, and 4.7%±2.6%. For the T0N0 population, they were 50.2%±6.8%, 33.4%±4.3%, 11.8%±7.6%, and 4.7%±2.4%. The two populations were compared using two tailed T-tests: volumes 3 and 4 were statistically different with p values of 0.021 and 0.056 respectively. V6 was located at 8.63 ± 2.2 for T0N0 and 6.14 ± 0.78 for T3N0 group (p=0.016). Conclusion: We described a method for dUVH decomposition using FDG-PET images of rectal adenocarcinoma patients that subsequently went for pre-operative brachytherapy. In addition to extracting different sub-volumes corresponding to different FDG uptake levels, we observed different abundances of two sub-volumes as well as positions of the maximum uptake between the two patient groups. In addition to opening the door to further investigation into underlying physiological phenotypes of segmented subvolumes and their use for biological radiotherapy treatment planning, this method may also provide parameters that could correlate to clinical outcomes in radiotherapy patients.

60 APPLIED LIFE SCIENCES↗

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

97 MATHEMATICS AND COMPUTING↗

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗

Dynamic color mapping with a multi-scale histogram: A design study with physical scientists

Many research and development activities for scientific data analysis have focused on scalability challenges and data-driven features. Conversely, data visualization that focus on models requiring human interaction rarely involve practical and largescale scientific data analysis. Therefore, a gap exists between interactive data visualization and scientific data analysis applications. In this paper, we present a design study of interactive data visualization to support scientists who visually analyze data from neutron scattering experiments. This study was conducted in multiple phases: 1) problem characterization; 2) initial design and formative evaluation; and 3) iterative design. We characterize the problems and the design requirements for the analysis of the specific physical science data. We discuss the design, development, evaluation of our visual analytics tool and as well as our iterative developments with physical scientists. We show how to bridge the gap between the two disciplines uncovering new potential to solve their challenges in this design study. We focus on a specific challenge, finding an optimal color mapping, which plays a critical role in neutron scattering science and is broadly applicable to other scientific domains. To address the challenge, we propose two interactive visualization techniques: a dynamic color scale bar (DCSB) and a multi-scale histogram (MSH).

Chae, Junghoon↗

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

Li, Ying Wai↗

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining a plurality of bins; defining an array of elements; dividing the sampled data points into a plurality of sections; assigning a plurality of polynomial equations, one polynomial equation to each section, each polynomial equation having a waveform that fits the data points of the associated section; determining a plurality of section bin times, one section bin time for each bin in each section, each section bin time determined using the polynomial equation and indicating an amount of time that the waveform has values in the range of one of the bins; and adding the section bin time for each bin in each section to the histogram data in the array element pointed to by the number of the bin.

Tohlen, Michael Aaron↗

Register-Like Storage Block Used as Histograms, Cluster Buffers, and Hough Transform Accumulators for HEP Trigger Systems

In high energy physics experiment trigger systems, block memories are utilized for various purposes, especially in binned searching algorithms. In these algorithms, the storages are demanded to perform like a large set of registers. The writing and reading operation must be performed in single clock cycle and once an event is processed, the memory must be globally reset. These demands can be fulfilled with registers but the cost of using registers for large memory is unaffordable. Another common requirement is the boundary coverage feature during reading process. Additionally, when a memory bin is addressed, the stored contents in the addressed bin and its neighboring bin must be output simultaneously. In this paper, a register-like block storage design scheme is described, which allows updating memory locations in single clock cycle, reading two adjacent bins, and effectively refreshing entire memory within a single clock. The implementation and test results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Method of predicting the mean lung dose based on a patient's anatomy and dose-volume histograms

The aim of this study was to propose a method to predict the minimum achievable mean lung dose (MLD) and corresponding dosimetric parameters for organs-at-risk (OAR) based on individual patient anatomy. For each patient, the dose for 36 equidistant individual multileaf collimator shaped fields in the treatment planning system (TPS) was calculated. Based on these dose matrices, the MLD for each patient was predicted by the homemade DosePredictor software in which the solution of linear equations was implemented. The software prediction results were validated based on 3D conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT) plans previously prepared for 16 patients with stage III non–small-cell lung cancer (NSCLC). For each patient, dosimetric parameters derived from plans and the results calculated by DosePredictor were compared. The MLD, the maximum dose to the spinal cord (D{sub max} {sub cord}) and the mean esophageal dose (MED) were analyzed. There was a strong correlation between the MLD calculated by the DosePredictor and those obtained in treatment plans regardless of the technique used. The correlation coefficient was 0.96 for both 3D-CRT and VMAT techniques. In a similar manner, MED correlations of 0.98 and 0.96 were obtained for 3D-CRT and VMAT plans, respectively. The maximum dose to the spinal cord was not predicted very well. The correlation coefficient was 0.30 and 0.61 for 3D-CRT and VMAT, respectively. The presented method allows us to predict the minimum MLD and corresponding dosimetric parameters to OARs without the necessity of plan preparation. The method can serve as a guide during the treatment planning process, for example, as initial constraints in VMAT optimization. It allows the probability of lung pneumonitis to be predicted.

61 RADIATION PROTECTION AND DOSIMETRY↗

Structure–property relationships in atomic-scale junctions: Histograms and beyond

Over the past 10 years, there has been tremendous progress in the measurement, modeling and understanding of structure–function relationships in single molecule junctions. Numerous research groups have addressed significant scientific questions, directed both to conductance phenomena at the single molecule level and to the fundamental chemistry that controls junction functionality. Many different functionalities have been demonstrated, including single-molecule diodes, optically and mechanically activated switches, and, significantly, physical phenomena with no classical analogues, such as those based on quantum interference effects. Experimental techniques for reliable and reproducible single molecule junction formation and characterization have led to this progress. In particular, the scanning tunneling microscope based break-junction (STM-BJ) technique has enabled rapid, sequential measurement of large numbers of nanoscale junctions allowing a statistical analysis to readily distinguish reproducible characteristics. Furthermore, harnessing fundamental link chemistry has provided the necessary chemical control over junction formation, enabling measurements that revealed clear relationships between molecular structure and conductance characteristics.

36 MATERIALS SCIENCE↗

Flat-histogram extrapolation as a useful tool in the age of big data

In this work, we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling techniques enables the prediction of free energy landscapes and other detailed information, such as structural properties, of the system in question. Remarkably accurate estimates of physical properties across a broad range of conditions have been achieved using this approach, greatly reducing the number of simulations needed to explore a given system's behaviour. While approximate, these extrapolations significantly amplify the amount of reasonably accurate information that can be extracted from simulations enabling a small set of them to feed data-intensive regression algorithms such as neural networks. Thus, this extrapolation methodology represents a useful tool for performing tasks such as high-throughput screening of physical properties, optimising force field parameters, exploring equilibrium phase behaviour, and enabling theory-guided data science for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗