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At least 127 records · Page 7

Evaluation of a visual interpretation method for tau-PET with 18 F-flortaucipir

Introduction: Positron emission tomography targeting tau (tau-PET) is a promising diagnostic tool for the identification of Alzheimer's disease (AD). Currently available data rely on quantitative measures, and a visual interpretation method, critical for clinical translation, is needed. Methods: In this work, we developed a visual interpretation method for 18 F-flortaucipir tau-PET and tested it on 274 individuals (cognitively normal controls, patients with mild cognitive impairment [MCI], AD dementia, and non-AD diagnoses). Two readers interpreted 18 F-flortaucipir PET using two complementary indices: a global visual score and a visual distribution pattern. Results: Global visual scores were reliable, correlated with global cortical 18 F-flortaucipir standardized uptake value ratio (SUVR) and were associated with clinical diagnosis and amyloid status. The AD-like 18 F-flortaucipir pattern had good sensitivity and specificity to identify amyloid-positive patients with AD dementia or MCI. Discussion: This 18 F-flortaucipir visual rating scheme is associated with SUVR quantification, clinical diagnosis, and amyloid status, and constitutes a promising approach to tau measurement in clinical settings.

59 BASIC BIOLOGICAL SCIENCES↗

A survey of radiographers' confidence and self-perceived accuracy in frontline image interpretation and their continuing educational preferences

The provision of a written comment on traumatic abnormalities of the musculoskeletal system detected by radiographers can assist referrers and may improve patient management, but the practice has not been widely adopted outside the United Kingdom. The purpose of this study was to investigate Australian radiographers' perceptions of their readiness for practice in a radiographer commenting system and their educational preferences in relation to two different delivery formats of image interpretation education, intensive and non-intensive. A cross-sectional web-based questionnaire was implemented between August and September 2012. Participants included radiographers with experience working in emergency settings at four Australian metropolitan hospitals. Conventional descriptive statistics, frequency histograms, and thematic analysis were undertaken. A Wilcoxon signed-rank test examined whether a difference in preference ratings between intensive and non-intensive education delivery was evident. The questionnaire was completed by 73 radiographers (68% response rate). Radiographers reported higher confidence and self-perceived accuracy to detect traumatic abnormalities than to describe traumatic abnormalities of the musculoskeletal system. Radiographers frequently reported high desirability ratings for both the intensive and the non-intensive education delivery, no difference in desirability ratings for these two formats was evident (z = 1.66, P = 0.11). Some Australian radiographers perceive they are not ready to practise in a frontline radiographer commenting system. Overall, radiographers indicated mixed preferences for image interpretation education delivered via intensive and non-intensive formats. Further research, preferably randomised trials, investigating the effectiveness of intensive and non-intensive education formats of image interpretation education for radiographers is warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Implications of the XENON1T excess on the dark matter interpretation

The dark matter interpretation for a recent observation of excessive electron recoil events at the XENON1T detector seems challenging because its velocity is not large enough to give rise to recoiling electrons of O(keV). Fast-moving or boosted dark matter scenarios are receiving attention as a remedy for this issue, rendering the dark matter interpretation a possibility to explain the anomaly. We investigate various scenarios where such dark matter of spin 0 and 1/2 interacts with electrons via an exchange of vector, axial-vector, pseudo-scalar, or scalar mediators. We find parameter values not only to reproduce the excess but to be consistent with existing bounds. Our study suggests that the scales of mass and coupling parameters preferred by the excess can be mostly affected by the type of mediator, and that significantly boosted dark matter can explain the excess depending on the mediator type and its mass choice. The method proposed in this work is general, and hence readily applicable to the interpretation of observed data in the dark matter direct detection experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Interpreting the Lipidome: Bioinformatic Approaches to Embrace the Complexity

Background Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites. Aim of review To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome. Key scientific concepts of review Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Kyle, Jennifer E.↗

On the self-interference in electron scattering: Copenhagen, Bohmian and geometrical interpretations of quantum mechanics

Self-interference embodies the essence of the particle-wave formulation of quantum mechanics (QM). According to the Copenhagen interpretation of QM, self-interference by a double-slit requires a large transverse coherence of the incident wavepacket such that it covers the separation between the slits. Bohmian dynamics provides a first step in the separation of the particle-wave character of matter by introducing deterministic trajectories guided by a pilot wave that follows the time-dependent Schrödinger equation. In this work, I present a new description of the phenomenon of self-interference using the geometrical formulation of QM introduced in Tavernelli (2016). In particular, this formalism removes the need for the concept of wavefunction collapse in the interpretation of the act of measurement i.e., the emergence of the classical world. The three QM formulations (Schrödinger, Bohmian, and geometrical) are applied to the description of the scattering of a free electron by a hydrogen atom and a double-slit. The corresponding interpretations of self-interference are compared and discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

How reliable is distribution of relaxation times (DRT) analysis? A dual regression-classification perspective on DRT estimation, interpretation, and accuracy

The distribution of relaxation times (DRT) has gained increasing attention and adoption in recent years as a versatile method for analyzing electrochemical impedance spectroscopy (EIS) data obtained from complex devices like fuel cells, electrolyzers, and batteries. The DRT deconvolutes the impedance without a priori specification of a generative model, which is especially useful for interpretation and model selection when the governing principles of the system under study are not fully understood. However, DRT estimation is an ill-posed inversion problem that must be addressed with a subjective choice of regularization and tuning, which leaves substantial risk of misleading interpretations of EIS data. In this work, we suggest a new classification view of the DRT inversion to clarify DRT estimation and interpretation. We introduce a dual regression-classification framework that unifies the classification and regression views of the DRT inversion with wide-reaching implications for DRT analysis. The dual framework is employed to demonstrate a new kind of DRT inversion algorithm and develop novel evaluation metrics that capture previously ignored aspects of DRT accuracy. These approaches are applied to both synthetic data and experimental spectra collected from a protonic ceramic fuel cell and a lithium-ion battery to illustrate their broad utility. The dual inversion algorithm shows promising performance for accurate DRT estimation and autonomous model identification, while the dual evaluation approach produces metrics that meaningfully assess the strengths and risks of DRT algorithms. Here this work provides valuable insight for both practical application of the DRT to experimental data and further development of EIS analysis methods.

36 MATERIALS SCIENCE↗

Interpreting biomarker data from the COPHES/DEMOCOPHES twin projects: Using external exposure data to understand biomarker differences among countries

In 2011 and 2012, the COPHES/DEMOCOPHES twin projects performed the first ever harmonized human biomonitoring survey in 17 European countries. In more than 1800 mother–child pairs, individual lifestyle data were collected and cadmium, cotinine and certain phthalate metabolites were measured in urine. Total mercury was determined in hair samples. While the main goal of the COPHES/DEMOCOPHES twin projects was to develop and test harmonized protocols and procedures, the goal of the current paper is to investigate whether the observed differences in biomarker values among the countries implementing DEMOCOPHES can be interpreted using information from external databases on environmental quality and lifestyle. In general, 13 countries having implemented DEMOCOPHES provided high-quality data from external sources that were relevant for interpretation purposes. However, some data were not available for reporting or were not in line with predefined specifications. Therefore, only part of the external information could be included in the statistical analyses. Nonetheless, there was a highly significant correlation between national levels of fish consumption and mercury in hair, the strength of antismoking legislation was significantly related to urinary cotinine levels, and we were able to show indications that also urinary cadmium levels were associated with environmental quality and food quality. These results again show the potential of biomonitoring data to provide added value for (the evaluation of) evidence-informed policy making. - Highlights: • External data was collected to interpret HBM data from DEMOCOPHES. • Hg in hair could be related to fish consumption across different countries. • Urinary cotinine was related to strictness of anti-smoking legislation. • Urinary Cd was borderline significantly related to air and food quality. • Lack of comparable data among countries hampered the analysis.

54 ENVIRONMENTAL SCIENCES↗

Expert Radiation Oncologist Interpretations of Involved-Site Radiation Therapy Guidelines in the Management of Hodgkin Lymphoma

Purpose: Recently, involved-site radiation therapy (ISRT) guidelines have been developed and published to replace the previous concept of involved-field radiation therapy for patients with lymphoma. However, these ISRT guidelines may be interpreted in different ways, posing difficulties for prospective clinical trials. This study reports survey results regarding interpretation of the ISRT guidelines. Methods and Materials: Forty-four expert lymphoma radiation oncologists were asked to participate in a survey that included 7 different cases associated with 9 questions. The questions pertained to ISRT contouring and asked respondents to choose between 2 different answers (no “correct” answer) and a third write-in option allowed. Results: Fifty-two percent of those surveyed responded to the questionnaire. Among those who responded, 72% have practiced for >10 years, 46% have treated >20 Hodgkin lymphoma cases annually, and 100% were familiar with the ISRT concept. Among the 9 questions associated with the 7 cases, 3 had concordance among the expert radiation oncologists of greater than 70%. Six of the questions had less than 70% concordance (range, 56%-67%). Conclusions: Even among expert radiation oncologists, interpretation of ISRT guidelines is variable. Further guidance for ISRT field design will be needed to reduce variability among practicing physicians.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Interpretation of energy deposition data from historical operation of the transient test facility (TREAT)

The Transient Test Reactor (TREAT) at Idaho National Laboratory will resume operations in late 2017 after a 23 year hiatus while maintained in a cold standby state. Over that time period, computational power and simulation capabilities have increased substantially and now allow for new multiphysics modeling possibilities that were not practical or feasible for most of TREAT's operational history. Hence the return of TREAT to operational service provides a unique opportunity to apply state-of-the-art software and associated methods in the modeling and simulation of general three-dimensional steady state and kinetic behavior for reactor operation, and for coupling of the core power transient model to experiment simulations. However, measurements taken in previous operations were intended to predict power deposition in experimental samples, with little consideration of three-dimensional core power distributions. Hence, interpretation of data for the purpose of validation of modern methods can be challenging. For the research discussed herein, efforts are described for the process of proper interpretation of data from the most recent calibration experiments performed in the core, the M8 calibration series (M8-CAL). These measurements were taken between 1990 and 1993 using a set of fission wires and test fuel pins to estimate the power deposition that would be produced in fast reactor test fuel pins during the M8 experiment series. Because of the decision to place TREAT into a standby state in 1994, the M8 series of transients were never performed. However, potentially valuable information relevant for validation is available in the M8-CAL measurement data, if properly interpreted. This article describes the current state of the process of recovery of useful data from M8-CAL measurements and quantification of biases and uncertainties to potentially apply to the validation of multiphysics methods.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

PBPK and population modelling to interpret urine cadmium concentrations of the French population

As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure.

60 APPLIED LIFE SCIENCES↗

Kinetic Isotope Effects: Interpretation and Prediction Using Degrees of Rate Control

Kinetic isotope effects (KIEs) have been used for decades in catalysis research as a tool for clarifying reaction mechanisms. Significant primary kinetic isotope effects have usually been interpreted as being a result of isotope substitution at a site of bond breaking (or forming) in the rate-determining step in the reaction mechanism. However, quantitative analysis of the magnitude of the KIE in complex multistep reaction mechanisms is seldom reported. We prove here that the logarithm of the rate ratio for two isotopes is the weighted average over all species in the mechanism of their standard-state free energy difference between the two isotopes, divided by RT. The weighting factor is the degree of rate control (DRC) for that species (e.g., transition state, intermediate, reactant) when the rate is measured separately for each isotope. It is instead the degree of selectivity ratio control (DSRC) when the KIE is measured as the product selectivity in a parallel competition between two isotopes within the same reactant molecule. Since only a few species have non-zero DRCs (or DSRCs) for most reactions, only these few contribute to this weighted average and the KIE. We show that this provides a simple way to interpret and quantitatively predict kinetic isotope effects that is powerful in the insights it provides, allowing one to evaluate directly which species contribute most to the KIE. By applying it to H/D KIEs in several example mechanisms, we further show that the traditional way of interpreting KIEs that focuses only on the rate-determining step can easily lead to misunderstanding of KIE and the reaction mechanism. Finally, this highlights the importance to consider the effect of isotope substitution on the energies of all species with large DRCs (i.e, those whose energies are kinetically relevant). This method also offers opportunities for quantitative validation of mechanism-based microkinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid machine learning (ML) model, that explicitly represented the controls of fuel flammability, fuel availability, and human suppression effects on fires. The model demonstrated notable accuracy with a F 1 -score of 0.846 ± 0.012, surpassing process-driven fire danger indices and four commonly used ML models by up to 40% and 9%, respectively. More importantly, the ML model showed remarkably higher interpretability relative to other ML models. Specifically, by demystifying the “black box” of each ML model using the explainable AI techniques, we identified substantial structural differences across ML fire models, even among those with similar accuracy. The relationships between fires and their drivers, identified by our model, were aligned closer with established fire physical principles. The ML structural discrepancy led to diverse fire predictions and our model predictions exhibited greater consistency with actual fire occurrence. With the highly interpretable and accurate model, we revealed the strong compound effects from multiple climate variables related to evaporative demand, energy release component, temperature, and wind speed, on the dynamics of large fires and megafires in the western US. Our findings highlight the importance of assessing the structural integrity of models in addition to their accuracy. They also underscore the critical need to address the rise in compound climate extremes linked to large wildfires.

54 ENVIRONMENTAL SCIENCES↗

Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients' intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.

60 APPLIED LIFE SCIENCES↗

How machine learning can extend electroanalytical measurements beyond analytical interpretation

Electroanalytical measurements are routinely used to estimate material properties exhibiting current and voltage signatures. Analysis of such measurements relies on analytical expressions of material properties to describe the experiments. The need for analytical expressions limits the experiments that can be used to measure properties as well as the properties that can be estimated from a given experiment. Such analytical relations are essentially solutions of the physics-based differential equations (with properties as coefficients) describing the material behavior under certain specific conditions. In recent years, a new machine learning-based approach has been gaining popularity wherein the differential equations are numerically solved to interpret the electroanalytical experiments in terms of corresponding material properties. Since the physics-based differential equations are solved, one can additionally estimate underlying fields, e.g., concentration profile, using such an approach. To exemplify the characteristics of such a machine learning assisted interpretation of electroanalytical measurements, we use data from the Hebb–Wagner test on a magnesium spinel intercalation host. In conclusion, as compared to the traditional analytical expression-based interpretation, the emerging approach decreases experimental efforts to characterize relevant material properties as well as provides field information that was previously inaccessible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sensitivity of the interpretation of the experimental ion thermal diffusivity to the determination of the ion conductive heat flux

A moments equation formalism for the interpretation of the experimental ion thermal diffusivity from experimental data is used to determine the radial ion thermal conduction flux that must be used to interpret the measured data. It is shown that the total ion energy flux must be corrected for thermal and rotational energy convection, for the work done by the flowing plasma against the pressure and viscosity, and for ion orbit loss of particles and energy, and expressions are presented for these corrections. Each of these factors is shown to have a significant effect on the interpreted ion thermal diffusivity in a representative DIII-D [J. Luxon, Nucl. Fusion 42, 614 (2002)] discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Two-dimensional interpreter for field-reversed configurations

An interpretive method is developed for extracting details of the fully two-dimensional (2D) “internal” structure of field-reversed configurations (FRC) from common diagnostics. The challenge is that only external and “gross” diagnostics are routinely available in FRC experiments. Inferring such critical quantities as the poloidal flux and the particle inventory has commonly relied on a theoretical construct based on a quasi-one-dimensional approximation. Such inferences sometimes differ markedly from the more accurate, fully 2D reconstructions of equilibria. An interpreter based on a fully 2D reconstruction is needed to enable realistic within-the-shot tracking of evolving equilibrium properties. Presented here is a flexible equilibrium reconstruction with which an extensive data base of equilibria was constructed. An automated interpreter then uses this data base as a look-up table to extract evolving properties. This tool is applied to data from the FRC facility at Tri Alpha Energy. It yields surprising results at several points, such as the inferences that the local β (plasma pressure/external magnetic pressure) of the plasma climbs well above unity and the poloidal flux loss time is somewhat longer than previously thought, both of which arise from full two-dimensionality of FRCs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Multi-frequency analysis of dark matter annihilation interpretations of recent anti-particle and γ-ray excesses in cosmic structures

The Fermi-LAT observation of a γ-ray excess from the galactic-centre, as well as the PAMELA, AMS, and AMS-2 anti-particle excesses, and the recent indications of a Fermi-LAT γ-ray excess in the Reticulum II dwarf galaxy have all been variously put forward as possible indirect signatures of supersymmetric neutralino dark matter. These are of particular interest as the neutralino annihilation models which fit these observations must have observable consequences across the frequency spectrum, from radio to γ-ray emission. Moreover, since dark matter is expected to be a major constituent of cosmic structure, these multi-frequency consequences should be common to such structures across the mass spectrum, from dwarf galaxies to galaxy clusters. Thus, in this work we make predictions for the multi-frequency spectra of three well-known sources dominated by dark matter on cluster, galaxy and dwarf galaxy scales, e.g. the Coma cluster, the galaxy M81, and the Draco dwarf galaxy, using models favoured by dark matter interpretations of the aforementioned observations. We pay special attention to the consequences for these models when their cross-sections are renormalised to reproduce the recent γ-ray excess observed in the Reticulum II dwarf galaxy, as well as using cross-sections from the Fermi-LAT dwarf galaxy limits, which throw a dark matter interpretation of this excess into doubt. We find that the multi-frequency data of Coma and Draco are in conflict with the dark matter interpretation of the AMS, PAMELA and Fermi positron excess. Additionally, models derived from Fermi-LAT galactic centre observations, and AMS-2 re-analysis, present similar but less extensive conflicts. Using the sensitivity projections for the Square Kilometre Array, the Cherenkov Telescope Array, as well as the ASTROGAM and ASTRO-H satellites, we determine the detection prospects for a subset of neutralino models that remain consistent with Planck cosmological constraints. Although the SKA has the greatest sensitivity to dark matter models, we demonstrate that ASTRO-H is well positioned to probe the inverse-Compton scattering emissions from neutralino annihilation and identify characteristics of the spectra which contain information about the neutralino mass and annihilation channel. This means that, given environments with favourable X-ray backgrounds, multi-frequency observation with the next generation of experiments will allow for unprecedented sensitivity to the neutralino parameter space as well as offsetting the individual weaknesses of each observation mode. Finally we show that all of the studied models can be better tested with the SKA phase 1.

79 ASTRONOMY AND ASTROPHYSICS↗

Highly deformed bands in Nd nuclei: New results and consistent interpretation within the cranked Nilsson-Strutinsky formalism

Three new highly-deformed (HD) bands are identified in 136 Nd and the highly deformed band of 137 Nd is extended at higher spin by four transitions, revealing a band crossing associated with the occupation of the second $νi_{13/2}$ intruder orbital. Extended cranked Nilsson-Strutinsky calculations are performed for all HD bands observed in 134 Nd, 136 Nd, and 137 Nd, achieving for the first time a consistent interpretation of all HD bands in the Nd nuclei. The new interpretation has significant consequences, like the change of parity of the yrast HD bands of 134 Nd and 136 Nd, and the involvement of two negative-parity neutron intruder orbitals in the configurations of most HD bands. The present experimental results and their theoretical interpretation represent an important step forward in the understanding of the second-minimum excitations in the Nd nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗