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2015 China Green Low-Carbon City scorecard

In China’s rapid urbanization and industrialization, cities are playing important roles in helping the country reach its climate change mitigation goal of peaking CO2 emissions around 2030, and improving environmental quality. During the 12th Five-Year Plan (12th FYP) period (2011–2015), Chinese cities set ambitious goals and implemented diverse policies aimed at transitioning to a greener economy. The Chinese central government also set targets on a number of indicators, such economic energy intensity and carbon intensity (e.g., CO2 per unit GDP), and air quality (e.g., PM2.5 concentration). These targets are helpful for tracking implementation of individual policies or progress at a sectoral level. However, a more comprehensive and integrated approach is needed to assess progress and capture the multi-dimensional aspects of Chinese cities’ transition to a greener economy, an approach that offers comparison with international best practices, as well as working with data availability in China’s statistical system. This paper presents the development of a China Green LowCarbon City Index2 (CGLCCI, or City Index) and its application to 115 Chinese cities – the largest assessment of Chinese cities to date. The GCLCCI includes 23 key indicators across seven categories: economy, energy, industry, buildings, transportation, environment and land use, and climate policy and outreach. This paper applied the CGLCCI to benchmark the green and low-carbon development status of 115 Chinese cities in the year 2015. Data for the analysis came from government and publicly available data sources. The CGLCCI methodology provides a standardized method to benchmark each indicator, calculate overall city scores, and rank the cities.3 The results showed that the low-carbon transition in Chinese cities is still in its early stages. Compared to the best practices benchmarks, the 2015 City Index scores ranged from a low of 28 to a high score of 70 in 2015 (maximum score is 100). This paper also presents three top-performing cities in different stages of development and discusses how their scores across the index categories. Creating a green low-carbon index that relies on publicly available data in China, and regularly evaluating city performance, can encourage Chinese cities to learn best practices from each other, and to strengthen their goals and implementation efforts toward a green low-carbon transition.

Zhang, Jingjing↗

Nuclear-level effective theory of 𝜇→𝑒 conversion: Formalism and applications

Over the next decade new 𝜇→𝑒 conversion searches at Fermilab (Mu2e) and J-PARC (COMET, DeeMe) are expected to advance limits on charged lepton flavor violation (CLFV) by more than four orders of magnitude. Here, by considering the consequence of 𝑃 and 𝐶⁢𝑃 on elastic 𝜇→𝑒 conversion and the structure of possible charge and current densities, we show that rates are governed by six nuclear responses and a single scale, 𝑞/𝑚 𝑁 , where 𝑞 ≈ 𝑚 𝜇 is the momentum transferred from the leptons to the nucleus. To relate this result to microscopic formulations of CLFV, we construct in nonrelativistic effective theory (NRET) the CLFV nucleon-level interaction, pointing out the relevance of the dimensionless scales 𝑦=($^{𝑞⁢𝑏}_2$) 2 ⁢ > |$\overrightarrow{𝑣}_N$⁢|>|$\overrightarrow{𝑣}_μ$⁢|>|$\overrightarrow{𝑣}_T$| , where 𝑏 is the nuclear size, $\overrightarrow{𝑣}_N$ and $\overrightarrow{𝑣}_μ$ are the nucleon and muon intrinsic velocities, and $\overrightarrow{𝑣}_T$ is the target recoil velocity. We discuss previous work, noting the lack of a systematic treatment of the various small parameters. Because the parameter 𝑦 is not small, a proper calculation of 𝜇→𝑒 conversion requires a full multipole expansion of the nuclear response functions, an apparently daunting task with Coulomb-distorted electron partial waves. We demonstrate that the multipole expansion can be carried out to high precision by introducing a simplifying local momentum 𝑞 eff for the electron. Previous work has been limited to simple charge or spin interactions, thereby treating the nucleus effectively as a point particle. We show that such formulations are not compatible with the general form of the 𝜇→𝑒 conversion rate, failing to generate three of the six allowed nuclear response functions. The inclusion of the nucleon velocity $\overrightarrow{𝑣}_N$ yields an NRET with 16 operators and a rate of the general form. Consequently, in the current discovery era for CLFV, it provides the most sensible starting point for experimental analysis, defining what can and cannot be determined about CLFV from the highly exclusive process of 𝜇→𝑒 conversion. Finally, we expand the NRET operator basis to account for the effects of $\overrightarrow{𝑣}_μ$, associated with the muon's lower component, generating corrections to the CLFV coefficients of the point-nucleus response functions. Using advanced shell-model methods, we compute 𝜇→𝑒 conversion rates for a series of experimental targets, deriving bounds on the coefficients of the CLFV operators. These calculations are the first to include a general basis of CLFV operators, full evaluation of the associated nuclear response functions, and an accurate treatment of electron and muon Coulomb effects. We discuss target selection as an experimental “knob” that can be turned to probe the microscopic origins of CLFV. We describe two types of coherence that enhance certain CLFV operators and selection rules that blind elastic 𝜇→𝑒 conversion to others. We discuss the matching of the NRET onto higher level effective field theories, such as those constructed at the light quark level, noting opportunities to build on existing work in direct detection of dark matter. We discuss the relation of 𝜇→𝑒 conversion to 𝜇→𝑒+𝛾 and 𝜇→3⁢𝑒, showing how MEG II and Mu3e results will complement those of Mu2e and COMET. Finally we describe a accompanying script—in Mathematica and Python versions—that can be used to compute 𝜇→𝑒 conversion rates in various nuclear targets for the full set of NRET operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Motion as perturbation. II. Development of the method for dosimetric analysis of motion effects with fixed-gantry IMRT

Purpose: In this work, the feasibility of implementing a motion-perturbation approach to accurately estimate volumetric dose in the presence of organ motion—previously demonstrated for VMAT-–is studied for static gantry IMRT. The method's accuracy is improved for the voxels that have very low planned dose but acquire appreciable dose due to motion. The study describes the modified algorithm and its experimental validation and provides an example of a clinical application. Methods: A contoured region-of-interest is propagated according to the predefined motion kernel throughout time-resolved 4D phantom dose grids. This timed series of 3D dose grids is produced by the measurement-guided dose reconstruction algorithm, based on an irradiation of a staticARCCHECK (AC) helical dosimeter array (Sun Nuclear Corp., Melbourne, FL). Each moving voxel collects dose over the dynamic simulation. The difference in dose-to-moving voxel vs dose-to-static voxel in-phantom forms the basis of a motion perturbation correction that is applied to the corresponding voxel in the patient dataset. A new method to synchronize the accelerator and dosimeter clocks, applicable to fixed-gantry IMRT, was developed. Refinements to the algorithm account for the excursion of low dose voxels into high dose regions, causing appreciable dose increase due to motion (LDVE correction). For experimental validation, four plans using TG-119 structure sets and objectives were produced using segmented IMRT direct machine parameters optimization in Pinnacle treatment planning system (v. 9.6, Philips Radiation Oncology Systems, Fitchburg, WI). All beams were delivered with the gantry angle of 0°. Each beam was delivered three times: (1) to the static AC centered on the room lasers; (2) to a static phantom containing a MAPCHECK2 (MC2) planar diode array dosimeter (Sun Nuclear); and (3) to the moving MC2 phantom. The motion trajectory was an ellipse in the IEC XY plane, with 3 and 1.5 cm axes. The period was 5 s, with the resulting average motion speed of 1.45 cm/s. The motion-perturbed high resolution (2 mm voxel) volumetric dose grids on the MC2 phantom were generated for each beam. From each grid, a coronal dose plane at the detector level was extracted and compared to the corresponding moving MC2 measurement, using gamma analysis with both global (G) and local (L) dose-error normalization. Results: Using the TG-119 criteria of (3%G/3 mm), per beam average gamma analysis passing rates exceeded 95% in all cases. No individual beam had a passing rate below 91%. LDVE correction eliminated systematic disagreement patterns at the beams’ aperture edges. In a representative example, application of LDVE correction improved (2%L/2 mm) gamma analysis passing rate for an IMRT beam from 74% to 98%. Conclusions: The effect of motion on the moving region-of-interest IMRT dose can be estimated with a standard, static phantom QA measurement, provided the motion characteristics are independently known from 4D CT or otherwise. The motion-perturbed absolute dose estimates were validated by the direct planar diode array measurements, and were found to reliably agree with them in a homogeneous phantom.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Operation of the NSLS-II Injector with a Lower Booster Injection Energy

The NSLS-II injector consists of a 200 MeV linac and a 3 GeV full-energy booster synchrotron. The linac contains five traveling-wave S-band accelerating structures driven by two high-power klystrons. Optimization of the NSLS-II injector has continued since user operation started in October 2014. Beam losses have been minimized by the injector tuning and stabilization, and high level software has been developed to characterize the booster and injection parameters. However, due to the recently increased frequency of klystrons arcing which shortens the lifetime of the klystron, operation of the linac with lowered klystron output power would allow injection to be maintained with fewer trips and extended lifetime of klystrons. Apart from the energy difference, the low energy klystron operation is quite similar to the nominal 200 MeV operation. Injection trials were carried out with scaled magnet settings of the linac, linac-to- booster (LtB) transport line, and the booster. The beam was successfully injected into the booster on May 31, 2017 at the low energy mode of the 170 MeV LtB injection. Overall transfer efficiency from the linac to the storage ring is identical to the standard 200 MeV operation. The 170 MeV injection mode has been adopted in NSLS-II user operation ever since the beam study. In the most recent injector studies on June 28 and July 3, 2017, the booster injection energy was further decremented to the final target value of 100 MeV via applying the same method established in the 170 MeV operation. The ultimate value of 100 MeV is determined by the special requirement of operating the injector at single klystron while repairing the other klystron or with two klystrons with significantly reduced outputs for the purpose of maximizing klystron lifetimes.

36 MATERIALS SCIENCE↗

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

Purpose: To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI. Materials and methods: This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm{sup 2}) and one higher b value (aHBV at 2000 s/mm{sup 2}). The acquired data were postprocessed to generate two different types of trace-weighted images—using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm{sup 2}) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm{sup 2}) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores. Results: Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm{sup 2} sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time). Conclusion: Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C α and C β atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of ‘hard’ degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Finally, quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.

59 BASIC BIOLOGICAL SCIENCES↗

Application of the Principle of Maximum Conformality to Top-Pair Production

A major contribution to the uncertainty of finite-order perturbative QCD predictions is the perceived ambiguity in setting the renormalization scale {mu}{sub r}. For example, by using the conventional way of setting {mu}{sub r} {element_of} [m{sub t}/2, 2m{sub t}], one obtains the total t{bar t} production cross-section {sigma}{sub t{bar t}} with the uncertainty {Delta}{sigma}{sub t{bar t}}/{sigma}{sub t{bar t}} {approx} (+3%/-4%) at the Tevatron and LHC even for the present NNLO level. The Principle of Maximum Conformality (PMC) eliminates the renormalization scale ambiguity in precision tests of Abelian QED and non-Abelian QCD theories. By using the PMC, all nonconformal {l_brace}{beta}{sub i}{r_brace}-terms in the perturbative expansion series are summed into the running coupling constant, and the resulting scale-fixed predictions are independent of the renormalization scheme. The correct scale-displacement between the arguments of different renormalization schemes is automatically set, and the number of active flavors n{sub f} in the {l_brace}{beta}{sub i}{r_brace}-function is correctly determined. The PMC is consistent with the renormalization group property that a physical result is independent of the renormalization scheme and the choice of the initial renormalization scale {mu}{sub r}{sup init}. The PMC scale {mu}{sub r}{sup PMC} is unambiguous at finite order. Any residual dependence on {mu}{sub r}{sup init} for a finite-order calculation will be highly suppressed since the unknown higher-order {l_brace}{beta}{sub i}{r_brace}-terms will be absorbed into the PMC scales higher-order perturbative terms. We find that such renormalization group invariance can be satisfied to high accuracy for {sigma}{sub t{bar t}} at the NNLO level. In this paper we apply PMC scale-setting to predict the t{bar t} cross-section {sigma}{sub t{bar t}} at the Tevatron and LHC colliders. It is found that {sigma}{sub t{bar t}} remains almost unchanged by varying {mu}{sub r}{sup init} within the region of [m{sub t}/4, 4m{sub t}]. The convergence of the expansion series is greatly improved. For the (q{bar q})-channel, which is dominant at the Tevatron, its NLO PMC scale is much smaller than the top-quark mass in the small x-region, and thus its NLO cross-section is increased by about a factor of two. In the case of the (gg)-channel, which is dominant at the LHC, its NLO PMC scale slightly increases with the subprocess collision energy {radical}s, but it is still smaller than m{sub t} for {radical} {approx}< 1 TeV, and the resulting NLO cross-section is increased by {approx}20%. As a result, a larger {sigma}{sub t{bar t}} is obtained in comparison to the conventional scale-setting method, which agrees well with the present Tevatron and LHC data. More explicitly, by setting m{sub t} = 172.9 {+-} 1.1 GeV, we predict {sigma}{sub Tevatron, 1.96 TeV} = 7.626{sub -0.257}{sup +0.265} pb, {sigma}{sub LHC, 7 TeV} = 171.8{sub -5.6}{sup +5.8} pb and {sigma}{sub LHC, 14 TeV} = 941.3{sub -26.5}{sup +28.4} pb.

43 PARTICLE ACCELERATORS↗

Automated detection of vessel lumen and stent struts in intravascular optical coherence tomography to evaluate stent apposition and neointimal coverage

Purpose: Intravascular optical coherence tomography (IV-OCT) is a high-resolution imaging method used to visualize the microstructure of arterial walls in vivo. IV-OCT enables the clinician to clearly observe and accurately measure stent apposition and neointimal coverage of coronary stents, which are associated with side effects such as in-stent thrombosis. In this study, the authors present an algorithm for quantifying stent apposition and neointimal coverage by automatically detecting lumen contours and stent struts in IV-OCT images. Methods: The algorithm utilizes OCT intensity images and their first and second gradient images along the axial direction to detect lumen contours and stent strut candidates. These stent strut candidates are classified into true and false stent struts based on their features, using an artificial neural network with one hidden layer and ten nodes. After segmentation, either the protrusion distance (PD) or neointimal thickness (NT) for each strut is measured automatically. In randomly selected image sets covering a large variety of clinical scenarios, the results of the algorithm were compared to those of manual segmentation by IV-OCT readers. Results: Stent strut detection showed a 96.5% positive predictive value and a 92.9% true positive rate. In addition, case-by-case validation also showed comparable accuracy for most cases. High correlation coefficients (R > 0.99) were observed for PD and NT between the algorithmic and the manual results, showing little bias (0.20 and 0.46 μm, respectively) and a narrow range of limits of agreement (36 and 54 μm, respectively). In addition, the algorithm worked well in various clinical scenarios and even in cases with a low level of stent malapposition and neointimal coverage. Conclusions: The presented automatic algorithm enables robust and fast detection of lumen contours and stent struts and provides quantitative measurements of PD and NT. In addition, the algorithm was validated using various clinical cases to demonstrate its reliability. Therefore, this technique can be effectively utilized for clinical trials on stent-related side effects, including in-stent thrombosis and in-stent restenosis.

60 APPLIED LIFE SCIENCES↗

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Characterization of a Unique Pair of Ferredoxin and Ferredoxin NADP+ Reductase Isoforms That Operates in Non-Photosynthetic Glandular Trichomes

Our recent investigations indicated that isoforms of ferredoxin (Fd) and ferredoxin NADP+ reductase (FNR) play essential roles for the reductive steps of the 2C-methyl-D-erythritol 4-phosphate (MEP) pathway of terpenoid biosynthesis in peppermint glandular trichomes (GTs). Based on an analysis of several transcriptome data sets, we demonstrated the presence of transcripts for a leaf-type FNR (L-FNR), a leaf-type Fd (Fd I), a root-type FNR (R-FNR), and two root-type Fds (Fd II and Fd III) in several members of the mint family (Lamiaceae). The present study reports on the biochemical characterization of all Fd and FNR isoforms of peppermint (Mentha × piperita L.). The redox potentials of Fd and FNR isoforms were determined using photoreduction methods. Based on a diaphorase assay, peppermint R-FNR had a substantially higher specificity constant (kcat/Km) for NADPH than L-FNR. Similar results were obtained with ferricyanide as an electron acceptor. When assayed for NADPH–cytochrome c reductase activity, the specificity constant with the Fd II and Fd III isoforms (when compared to Fd I) was slightly higher for L-FNR and substantially higher for R-FNR. Based on real-time quantitative PCR assays with samples representing various peppermint organs and cell types, the Fd II gene was expressed very highly in metabolically active GTs (but also present at lower levels in roots), whereas Fd III was expressed at low levels in both roots and GTs. Our data provide evidence that high transcript levels of Fd II, and not differences in the biochemical properties of the encoded enzyme when compared to those of Fd III, are likely to support the formation of copious amounts of monoterpene via the MEP pathway in peppermint GTs. This work has laid the foundation for follow-up studies to further investigate the roles of a unique R-FNR–Fd II pair in non-photosynthetic GTs of the Lamiaceae.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of Lobe Power Calculator and Indication System with Physics and Cycle Based Models

The Advanced Test Reactor (ATR) at INL measures reactor power through two methods, thermal and Nitrogen-16 (N-16) activity. Water power calculator (WPC) is a thermal power system that measures flow and temperature to determine the thermal quadrant powers. The N-16 system utilizes a beta chamber detector that outputs reactivity levels to calculate lobe power through an algorithm called lobe power calculation and indication system (LPCIS). The LPCIS utilizes the N-16 system and the WPC system to determine reactor core power levels. The WPC provides accurate calculations of quadrant and total reactor thermal power. With the use of WPC measurements, thermal-to-N-16 (T2N) power ratios are produced to determine if the two indication systems agree on core power. Relative magnitude equations are used to utilize N-16 coefficients and multipliers to improve the indications of the LPCIS. This is crucial for maintaining safety limits. Currently, the LPCIS system uses linear equations and matrices to calculate lobe power through multipliers and coefficients. Advancements in technology and system upgrades have assisted system engineers at INL with the objective to reach a more dynamic system. In return the system demonstrates an increase in the accuracy of power reading while maintaining safety margins. The new proposed coefficient and multiple method implements a cycle specific, and a physics-based model intended for changing coefficients during operation. This calibration experiment focuses on power splitting, outer shim and neck shim, as well as fuel burning into the RDAS weighting factors. Results show that the Physics learning method yields a smaller error margin inside of the desired power range for the data set 166-A. This proved true for both constrained and unconstrained testing. This is most likely due to the physics data fitting approach that resulted in favorable coefficients and multipliers for 166-A. Continuing to improve the physics-based model will help improve the power accuracy of the LPCIS system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of fracture diagnostic methods for fluid distribution based on quantitative interpretation of distributed acoustic sensing and distributed temperature sensing

Multistage hydraulic fracturing design on horizontal wells has significantly evolved with larger fluid volume, more fracturing stages, and tighter perforation cluster spacing to efficiently stimulate unconventional reservoirs. From the published field observations, the recent fracturing design results in complex fracture networks or swarm of fractures. Fracture treatment evaluation is extremely challenging in such a case because of the large amount of variables in well completion and stimulation design. Combined measurements from different technologies can help in fracture diagnosis. Fluid distribution, either during fracture injection or during production, directly relates to the stimulation efficiency at the cluster level and at the stage level. Because it is unlikely in the real world to distribute the injected fluid uniformly among all the clusters, we need diagnostic techniques to generate the flow profile along a lateral. Fiber-optic measurements, such as distributed acoustic sensing (DAS) and distributed temperature sensing (DTS), are currently used to diagnose downhole flow conditions. This technology allows us to qualitatively confirm the fluid flow profile and other issues occurring downhole during fracturing such as leakage through plugs. For optimizing a fracturing design, we also need to understand how the design parameters are correlated with the stimulation efficiency. In this study, we combine two sets of models of DAS and DTS data interpretation for injected fluid volume distribution. The DAS is interpreted based on an empirical correlation between fluid flow rates and frequency band energy from the acoustic signals. The DTS is interpreted by performing temperature history match-based thermal energy conservation. Because of the completely different physics behind the interpretations, the confirmation of two interpretations provides confidence in fluid distribution.

Geochemistry & Geophysics↗

Methodological Aspects of Shielding and Activation Analyses for ITER Diagnostics Systems - Paper 125

It is expected that the diagnostics systems of the ITER tokamak will provide valuable measurement data about the first in its kind D-T fusion plasma with emission of 14 MeV neutrons. These systems must withstand the neutron and secondary photon radiation along the ITER operation. Under the neutron irradiation the ITER materials are getting radioactive and therefore an adequate shielding must be provided along all the time of ITER operation and shut-down for the reliable machine operation and for the safe personnel access to its components, such as the diagnostics ports. These are the prerequisites for the shielding and activation analysis of the ITER diagnostics systems discussed in this paper. This paper provides insight into the current tasks of neutronics support for the development of ITER diagnostics systems. The tasks themselves range from relatively straightforward ones such as Monte Carlo radiation transport calculations for shielding analyses of the diagnostics systems, to more advanced tasks of Shut-Down Dose Rate (SDDR) analyses for which the dedicated Rigorous 2-Step mesh-based (R2Smesh) and Direct 1-Step (D1S) methodologies were applied. The accuracy and precision of the ITER neutronics analysis is dependent on the methodological approaches and the implying modeling assumptions. In addition to the SDDR challenges, another distinguishing feature of fusion neutronics is a wide use of CAD-based neutronics modeling to design components of fusion devices such as ITER and DEMO. Basically, there are two possibilities of CAD geometry settings in Monte Carlo (MC) radiation transport models, either by the geometry format conversion of CAD models into the format of MC models by means of the interface programs such as McCad and MCAM or by the direct use of CAD geometry engine in MC calculations such as it was realized in the DAGMC code approach. Several conversion interfaces and the DAGMC software library have been tested on the 3D ITER model developed for the CAD-MCNP benchmark. It was concluded that the considered approaches have reached the maturity level to allow their application to real ITER design analyses.

61 RADIATION PROTECTION AND DOSIMETRY↗

A data-driven approach to sampling matrix selection for compressive sensing

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware constraints and is not responsive to domain-specific context. We propose a method for defining an order for a sampling basis that is optimal with respect to capturing variance in data, thus allowing for meaningful sensing at any desired level of compression. We focus on the Walsh-Hadamard sampling basis for its relevance to hardware constraints, but our approach applies to any sampling basis of interest. We illustrate the effectiveness of our method on the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset, the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset, and a Colorado State University Swiss Ranger depth image dataset. The spectral datasets consist of simulant experiments, including releases of chemicals such as GAA and SF6. We combine our sampling and reconstruction with the adaptive coherence estimator (ACE) and bulk coherence for chemical detection and we incorporate an algorithmic threshold for ACE values to determine the presence or absence of a chemical. We compare results across sampling methods in this context. We have successful chemical detection at a compression rate of 90%. For all three datasets, we compare our sampling approach to standard orderings of sampling basis such as random, sequency, and an analog of sequency that we term `frequency.' In one instance, the peak signal to noise ratio was improved by over 30% across a test set of depth images.

compressive sensing, hyperspectral imaging, Walsh-↗

Aerial Lidar and Geomorphic Change Detection Software- Tools for Monitoring Canyon Sediments at LANL - 18668

The Los Alamos National Laboratory Environmental Remediation program has conducted extensive geomorphic surveys of sediment deposits in the canyon bottoms within and surrounding the facility. The goal of the geomorphic surveys was to provide basic information needed to characterize chemical inventories of the sediments downstream of historical release sites. Sediment units were mapped based on depositional setting and age. Representative characterization samples were collected for each unit and submitted for chemical analysis. Chemical inventories were estimated by calculating the total volume of each depositional unit and multiplying by average chemical concentration. This method of characterization provides a spatial distribution of chemical data based on fluvial processes. In general, for the canyon bottom sediments, the higher concentrations of industrial chemicals were associated with fine-grained floodplain deposits closest to the source. Since initial characterization, many of the reaches have undergone changes in response to post-wildfire floods and severe rain events. These events impacted the channel and floodplain deposits. Much of the elevated concentrations are confined to the over-bank deposits distal from the primary channel. In order to ensure that the sediment units containing elevated chemical concentrations are stable, repeat aerial light detection and ranging (LiDAR) surveys are conducted and changes are assessed using the Geomorphic Change Detection (GCD) plug-in for ArcGIS. These tools provide high confidence uncertainty estimates and extensive areal coverage. This is a valuable method for long-term monitoring of surface sediments with low-level but widespread contaminant distributions. All of the monitored canyon bottom reaches pass risk assessment and present technically infeasible sediment removal options. Following the 2014 monsoon season, aerial LiDAR data has been collected annually and the resulting digital elevation models (DEMs) processed using the GCD method. Changes are identified using GCD and are verified by field walk downs. If erosion is identified in areas which are vulnerable to mobilizing contaminated sediment, enhanced controls can be installed to stabilize banks or other areas with high erosion potential. Annual sediment monitoring samples are collected where there is evidence for flow and deposition within the past year. Since 2014, no severe floods have been catalogued using the LiDAR surveys and GCD software. The recent rainfall/runoff events have not caused major changes to the canyon bottom channels and floodplains. Geomorphic processes identified in the monitoring results include channel aggradation and incision that over the course of a monsoon season results in minor changes to the system. Other active processes contributing to observed changes are minor slides, flows, slumps, and falls of unconsolidated sediment on steep bedrock or soil surfaces. A comprehensive baseline has been established by geomorphic mapping and characterization sampling. Periodic monitoring consists of LiDAR surveys and GCD analysis which offers an effective and defensible methodology for documenting stability of surface sediments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Delineating transcriptional networks of prognostic gene signatures refines treatment recommendations for lymph node-negative breast cancer patients

The majority of women diagnosed with lymph node-negative breast cancer are unnecessarily treated with damaging chemotherapeutics after surgical resection. This highlights the importance of understanding and more accurately predicting patient prognosis. We define the transcriptional networks regulating well-established prognostic gene expression signatures. We find that the same set of transcriptional regulators consistently lie upstream of both ‘prognosis’ and ‘proliferation’ gene signatures, suggesting that a central transcriptional network underpins a shared phenotype within these signatures. Strikingly, the master transcriptional regulators within this network predict recurrence risk for lymph node-negative breast cancer better than currently used multigene prognostic assays, particularly in estrogen receptor-positive patients. Simultaneous examination of p16 INK4A expression, which predicts tumours that have bypassed cellular senescence, revealed that intermediate levels of p16 INK4A correlate with an intact pRB pathway and improved survival. A combination of these master transcriptional regulators and p16 INK4A , termed the OncoMasTR score, stratifies tumours based on their proliferative and senescence capacity, facilitating a clearer delineation of lymph node-negative breast cancer patients at high risk of recurrence, and thus requiring chemotherapy. Furthermore, OncoMasTR accurately classifies over 60% of patients as ‘low risk’, an improvement on existing prognostic assays, which has the potential to reduce overtreatment in early-stage patients. Taken together, the present study provides new insights into the transcriptional regulation of cellular proliferation in breast cancer and provides an opportunity to enhance and streamline methods of predicting breast cancer prognosis.

59 BASIC BIOLOGICAL SCIENCES↗

MO-DE-BRA-04: The CREATE Medical Physics Research Training Network: Training of New Generation Innovators

Purpose: Over the past century, physicists have played a major role in transforming scientific discovery into everyday clinical applications. However, with the increasingly stringent requirements to regulate medical physics as a health profession, the role of physicists as scientists and innovators has become at serious risk of erosion. These challenges trigger the need for a new, revolutionized training program at the graduate level that respects scientific rigor, attention for medical physics-relevant developments in basic sciences, innovation and entrepreneurship. Methods: A grant proposal was funded by the Collaborative REsearch and Training Experience program (CREATE) of the Natural Sciences and Engineering Research Council (NSERC) of Canada. This enabled the creation of the Medical Physics Research Training Network (MPRTN) around two CAMPEP-accredited medical physics programs. Members of the network consist of medical device companies, government (research and regulatory) and academia. The MPRTN/CREATE program proposes a curriculum with three main themes: (1) radiation physics, (2) imaging & image processing and (3) radiation response, outcomes and modeling. Results: The MPRTN was created mid 2013 (mprtn.com) and features (1) four new basic Ph.D. courses; (2) industry participation in research projects; (3) formal job-readiness training with involvement of guest faculty from academia, government and industry. MPRTN activities since 2013 include 22 conferences; 7 workshops and 4 exchange travels. Three patents were filed or issued, nine awards/best papers were won. Fifteen journal publications were accepted/published, 102 conference abstracts. There are now 13 industry partners. Conclusion: A medical physics research training network has been set up with the goal to harness graduate student’s job-readiness for industry, government and academia in addition to the conventional clinical role. Two years after inception, significant successes have been booked, but the true challenge will be to demonstrate that with this training philosophy CREATE scholars gain access to a much broader job market. Supported by the Natural Sciences and Engineering Research Council (NSERC) Canada.

60 APPLIED LIFE SCIENCES↗

Maximum likelihood positioning algorithm for high-resolution PET scanners

Purpose: In high-resolution positron emission tomography (PET), lightsharing elements are incorporated into typical detector stacks to read out scintillator arrays in which one scintillator element (crystal) is smaller than the size of the readout channel. In order to identify the hit crystal by means of the measured light distribution, a positioning algorithm is required. One commonly applied positioning algorithm uses the center of gravity (COG) of the measured light distribution. The COG algorithm is limited in spatial resolution by noise and intercrystal Compton scatter. The purpose of this work is to develop a positioning algorithm which overcomes this limitation. Methods: The authors present a maximum likelihood (ML) algorithm which compares a set of expected light distributions given by probability density functions (PDFs) with the measured light distribution. Instead of modeling the PDFs by using an analytical model, the PDFs of the proposed ML algorithm are generated assuming a single-gamma-interaction model from measured data. The algorithm was evaluated with a hot-rod phantom measurement acquired with the preclinical HYPERION II {sup D} PET scanner. In order to assess the performance with respect to sensitivity, energy resolution, and image quality, the ML algorithm was compared to a COG algorithm which calculates the COG from a restricted set of channels. The authors studied the energy resolution of the ML and the COG algorithm regarding incomplete light distributions (missing channel information caused by detector dead time). Furthermore, the authors investigated the effects of using a filter based on the likelihood values on sensitivity, energy resolution, and image quality. Results: A sensitivity gain of up to 19% was demonstrated in comparison to the COG algorithm for the selected operation parameters. Energy resolution and image quality were on a similar level for both algorithms. Additionally, the authors demonstrated that the performance of the ML algorithm is less prone to missing channel information. A likelihood filter visually improved the image quality, i.e., the peak-to-valley increased up to a factor of 3 for 2-mm-diameter phantom rods by rejecting 87% of the coincidences. A relative improvement of the energy resolution of up to 12.8% was also measured rejecting 91% of the coincidences. Conclusions: The developed ML algorithm increases the sensitivity by correctly handling missing channel information without influencing energy resolution or image quality. Furthermore, the authors showed that energy resolution and image quality can be improved substantially by rejecting events that do not comply well with the single-gamma-interaction model, such as Compton-scattered events.

60 APPLIED LIFE SCIENCES↗