Position Uncertainty Research Articles

PDFF-CNN: An attention-guided dynamic multi-orientation feature fusion method for gestational age prediction on imbalanced fetal brain MRI dataset.

Fetal brain magnetic resonance imaging (MRI)-based gestational age prediction has been widely used to characterize normal fetal brain development and diagnose congenital brainmalformations. The uncertainty of fetal position and external interference leads to variable localization and direction of the fetal brain. In addition, pregnant women typically concentrate on receiving MRI scans during the fetal anomaly scanning week, leading to an imbalanced distribution of fetal brain MRI data. The above-mentioned problems pose great challenges for deep learning-based fetal brain MRI gestational ageprediction. In this study, a pyramid squeeze attention (PSA)-guided dynamic feature fusion CNN (PDFF-CNN) is proposed to robustly predict gestational ages from fetal brain MRI images on an imbalanced dataset. PDFF-CNN contains four components: transformation module, feature extraction module, dynamic feature fusion module, and balanced mean square error (MSE) loss. The transformation and feature extraction modules are employed by using the PSA to learn multiscale and multi-orientation feature representations in a parallel weight-sharing Siamese network. The dynamic feature fusion module automatically learns the weights of feature vectors generated in the feature extraction module to dynamically fuse multiscale and multi-orientation brain sulci and gyri features. Considering the fact of the imbalanced dataset, the balanced MSE loss is used to mitigate the negative impact of imbalanced data distribution on gestational age predictionperformance. Evaluated on an imbalanced fetal brain MRI dataset of 1327 routine clinical T2-weighted MRI images from 157 subjects, PDFF-CNN achieved promising gestational age prediction performance with an overall mean absolute error of 0.848 weeks and an of 0.904. Furthermore, the attention activation maps of PDFF-CNN were derived, which revealed regional features that contributed to gestational age prediction at each gestationalstage. These results suggest that the proposed PDFF-CNN might have broad clinical applicability in guiding treatment interventions and delivery planning, which has the potential to be helpful with prenatal diagnosis.

Joint Direction-of-Arrival and Time-of-Arrival Estimation With Ultra-Wideband Elliptical Arrays

This paper presents a general technique for the joint Direction-of-Arrival (DoA) and Time-of-Arrival (ToA) estimation in multipath environments. The proposed ultra-wideband technique is based on phase-mode expansions and the use of nearly frequency-invariant elliptical arrays. New possibilities open with the present approach, as not only elliptical, but also circular and linear (highly flattened) arrays can be considered with the same implementation. Systematic selection/rejection of signals-of-interest/signals-not-of-interest in smart wireless environments is possible, unlike with previous approaches based on circular arrays. Concentric elliptical arrays of many sizes and eccentricities can be jointly considered, with the subsequent improvement that entails in DoA and ToA detection. This leads to the realization of pseudo-random array patterns; namely, quasi-arbitrary geometries created from the superposition of multiple elliptical arrays. Some simulation and experimental tests (measurements in an anechoic chamber) are carried out for several frequency bands to check the correct performance of the method. The method is proven to give accurate estimations in all tested scenarios, and to be robust against noise and position uncertainty in sensor placement.

A global view on star formation: The GLOSTAR Galactic plane survey

As part of the GLObal view of STAR formation in the Milky Way (GLOSTAR) survey, we present the high-resolution continuum source catalog for the regions (ℓ = 2° −28°, 36° −40°, 56° −60°, and |b| < 1.0°), observed with the Karl G. Jansky Very Large Array (VLA) in its B-configuration. The continuum images were optimized to detect compact sources on angular scales up to 4″, and have a typical noise level of 1σ ~ 0.08 mJy beam−1 for an angular resolution of 1″, which makes GLOSTAR currently the highest resolution as well as the most sensitive radio survey of the northern Galactic plane at 4–8 GHz. We extracted 13354 sources above a threshold of 5σ and 5437 sources above 7σ that represent the high-reliability catalog. We determined the in-band spectral index (α) for the sources in the 7σ-threshold catalog. The mean value is α = −0.6, which indicates that the catalog is dominated by sources emitting nonthermal radio emission. We identified the most common source types detected in radio surveys: 251 H II region candidates (113 new), 282 planetary nebulae (PNe) candidates (127 new), 784 radio star candidates (581 new), and 4080 extragalactic radio source candidates (2175 new). A significant fraction of H II regions and PNe candidates have α < −0.1 indicating that these candidates could contain radio jets, winds or outflows from high-mass and low-mass stellar objects. We identified 245 variable radio sources by comparing the flux densities of compact sources from the GLOSTAR survey and the Co-Ordinated Radio “N” Infrared Survey for High-mass star formation (CORNISH), and find that most of them are infrared quiet. The catalog is typically 95% complete for point sources at a flux density of 0.6 mJy (i.e., a typical 7σ level) and the systematic positional uncertainty is ≲ 0″.1.

Using graphlet degree vectors to predict atomic displacement parameters in protein structures.

In structural biology, atomic displacement parameters, commonly used in the form of B values, describe uncertainties in atomic positions. Their distribution over the structure can provide hints on local structural reliability and mobility. A spatial macromolecular model can be represented by a graph whose nodes are atoms and whose edges correspond to all interatomic contacts within a certain distance. Small connected subgraphs, called graphlets, provide information about the wiring of a particular atom. The multiple linear regression approach based on this information aims to predict a distribution of values of isotropic atomic displacement parameters (B values) within a protein structure, given the atomic coordinates and molecular packing. By modeling the dynamic component of atomic uncertainties, this method allows the B values obtained from experimental crystallographic or cryo-electron microscopy studies to be reproduced relatively well.

Setup Uncertainty of Pediatric Brain Tumor Patients Receiving Proton Therapy: A Prospective Study.

This study quantifies setup uncertainty in brain tumor patients who received image-guided proton therapy. Patients analyzed include 165 children, adolescents, and young adults (median age at radiotherapy: 9 years (range: 10 months to 24 years); 80 anesthetized and 85 awake) enrolled in a single-institution prospective study from 2020 to 2023. Cone-beam computed tomography (CBCT) was performed daily to calculate and correct manual setup errors, once per course after setup correction to measure residual errors, and weekly after treatments to assess intrafractional motion. Orthogonal radiographs were acquired consecutively with CBCT for paired comparisons of 40 patients. Translational and rotational errors were converted from 6 degrees of freedom to a scalar by a statistical approach that considers the distance from the target to the isocenter. The 95th percentile of setup uncertainty was reduced by daily CBCT from 10 mm (manual positioning) to 1-1.5 mm (after correction) and increased to 2 mm by the end of fractional treatment. A larger variation existed between the roll corrections reported by radiographs vs. CBCT than for pitch and yaw, while there was no statistically significant difference in translational variation. A quantile mixed regression model showed that the 95th percentile of intrafractional motion was 0.40 mm lower for anesthetized patients (p=0.0016). Considering additional uncertainty in radiation-imaging isocentricity, the commonly used total plan robustness of 3 mm against positional uncertainty would be appropriate for our study cohort.

Merging multiple sensing platforms and deep learning empowers individual tree mapping and species detection at the city scale

The precise estimation of the number of trees, their individual tree locations, along with species information, is crucial for enhancing ecosystem services in urban areas. Previous studies largely used satellite or airborne images for mapping trees, but they were insufficient to generate a large number of species distributions. Ground-level data also led to inaccurate positional information of individual trees, although they provided reliable species detection results. In this study, we propose a novel framework that fully explores the complementary strengths of air- and ground-level sensing platforms by leveraging various deep neural networks to generate a detailed tree maps at a city-wide scale. Our strategy includes individual tree mapping and tree species detection using three-color channel images acquired from multiple sensing platforms. Through publicly available airborne imagery, we estimate the presence of over 1.2 million trees in Suwon city of South Korea spanning 121.04 km2 (R2 of 0.95 and relative bias of −1.9 %), achieving more accurate individual tree positions (positional uncertainty around 2.0 m) than conventional methods. Our comprehensive experiments also demonstrate the effectiveness of utilizing tree bark photos and street-level imagery taken by citizens and vehicles to identify urban tree species, with accuracy rates of over 80 % for citizen-sensed tree species maps and 66 % for vehicle-sensed tree species map. Along with the proliferation of web-based airborne images, the widespread use of smartphones, and the advancements in vehicle-mounted sensors, this study can facilitate efficient and accurate management of urban trees across scales. For reproducibility of the study, we share the source code and datasets at https://github.com/landkwon94/ryoungseob-master.

Deglaciation of the north American ice sheet complex in calendar years based on a comprehensive database of chronological data: NADI-1

The most recent deglaciation of the North American Ice Sheet Complex (NAISC: comprising the Innuitian, Cordilleran, and Laurentide ice sheets) offers a broad perspective from which to analyze the timing and rate of ice retreat, deglacial sea-level rise, and abrupt climate change events. Previous efforts to portray the retreat of the NAISC have been focused largely on minimum-limiting radiocarbon ages and ice margin location(s) tied to deglacial landforms that were not, for the most part, chronologically constrained. Here, we present the first version of North American Deglaciation Isochrones (NADI-1) spanning 25 to 1 ka in calendar years before present. Key new features of this work are (i) the incorporation of cosmogenic nuclide data, which offer a direct constraint on the timing of ice recession; (ii) presentation of all data and time-steps in calendar years; (iii) optimal, minimum, and maximum ice extents for each time-step that are designed to capture uncertainties in the ice margin position, and; (iv) extensive documentation and justification for the placement of each ice margin. Our data compilation includes 2229 measurements of 10Be, 459 measurements of 26Al and 35 measurements of 36Cl from a variety of settings, including boulders, bedrock surfaces, cobbles, pebbles, and sediments. We also updated a previous radiocarbon dataset (n = 4947), assembled luminescence ages (n = 397) and gathered uranium-series data (n = 2). After scrutiny of the geochronological dataset, we consider >90% of data to be reliable or likely reliable. Key findings include (i) a highly asynchronous maximum glacial extent in North America, occurring as early as 27 ka to as late as 17 ka, within and between ice sheets. In most marine realms, extension of the ice margin to the continental shelf break at 25 ka is somewhat speculative because it is based on undated and spatially scattered ice stream and geomorphic evidence; (ii) detachment of the Laurentide and Cordilleran ice sheets took place gradually via southerly and northerly ‘unzipping’ of the ice masses, starting at 17.5 ka and ending around 14 ka; (iii) the final deglaciation of Hudson Bay began at 8.5 ka, with the collapse completed by 8 ka. The maximum extent of ice during the last glaciation occurred at 22 ka and covered 15,470,000 km2. All North American ice sheets merged at 22 ka for the first time in the Quaternary. The highly asynchronous Last Glacial Maximum in North America means that our isochrones (starting at 25 ka) capture ice advance across some areas, which is based on limited evidence and is therefore somewhat speculative. In the Supplementary Data, the complete NADI-1 chronology is available in PDF, GIF and shapefile format, together with additional visualizations and spreadsheets of geochronological data. The NADI-1 shapefiles are also available at https://doi.org/10.5281/zenodo.8161764.

Feasibility of forecasting convective rain by diagnosing intracloud lightning jumps

This study conducted a comparison of the data quality of Earth Networks (EN) and Taiwan Power Company’s Total Lightning Detection System (TLDS) and evaluated the feasibility of using intracloud (IC) lightning to issue convective rain warnings. The results indicate uncertainties in the TLDS positioning of IC lightning. When forecasting convective rain on the basis of IC lightning jumps using EN data, the mean prefigurance and postagreement scores were 0.8 and 0.67, respectively, which were more favourable than the respective TLDS scores of 0.65 and 0.47. In regions with high TLDS positioning uncertainties, the use of EN data increased the number of prefigurance and postagreement hits in each analysis zone and raised the prefigurance and postagreement scores to 0.3 and 0.5, respectively. This indicates that analyses using EN data can reduce the risk of missed convective rain warnings when diagnosing IC jumps and can reduce the false alarm rate. In this study, IC jumps preceded convective rains by a maximum of 27.5–39.3 min on average in all analysis zones across Taiwan. The results suggest that diagnosing IC jumps to forecast convective rain is feasible, but until the uncertainties in the positioning of IC lightning using TLDSs have been remedied, EN data are the more suitable diagnostic choice.

Adapting a practical EPR dosimetry protocol to measure output factors in small fields with alanine.

Modern radiotherapy techniques often deliver small radiation fields. In this work, a practical Electron Paramagnetic Resonance (EPR) dosimetry protocol is adapted and applied to measure output factors (OF) in small fields of a 6 MV radiotherapy system. Correction factors and uncertainties are presented and OFs are compared to the values obtained by following TRS-483 using an ionization chamber (IC). Irradiations were performed at 10cm depth inside a water phantom positioned at 90cm source to surface distance with a 6 MV flattening filter free photon beam of a Halcyon radiotherapy system. OFs for different nominal field sizes (1×1, 2×2, 3×3, 4×4, normalized to 10×10 cm2 ) were determined with a PinPoint 3D (PTW 31022) IC following TRS-483 as well as with alanine pellets with a diameter of 4mm and a height of 2.4mm. EPR readout was performed with a benchtop X-band spectrometer. Correction factors due to volume averaging and due to positional uncertainties were derived from 2D film measurements. OFs obtained from both dosimeter types agreed within 0.7% after applying corrections for the volume averaging effect. For the used alanine pellets, volume averaging correction factors of 1.030(2) for the 1×1 cm2 field and <1.002 for the larger field sizes were determined. The correction factor for positional uncertainties of 1mm was in the order of 1.018 for the 1×1 cm2 field. Combined relative standard uncertainties uc for the OFs resulting from alanine measurements were estimated to be below 1.5% for all field sizes. For IC measurements, uc was estimated to be below 1.0%. A practical EPR dosimetry protocol is adaptable for precisely measuring OFs in small fields down to 1×1cm2 . It is recommended to consider the effect of positional uncertainties for field sizes <2×2cm2 .

Star tracking for pointing determination of Imaging Atmospheric Cherenkov Telescopes

We present a novel approach to the determination of the pointing of Imaging Atmospheric Cherenkov Telescopes (IACTs) using the trajectories of the stars in their camera’s field of view. The method starts with the reconstruction of the star positions from the Cherenkov camera data, taking into account the point spread function of the telescope, to achieve a satisfying reconstruction accuracy of the pointing position. A simultaneous fit of all reconstructed star trajectories is then performed with the orthogonal distance regression (ODR) method. ODR allows us to correctly include the star position uncertainties and use the time as an independent variable. Having the time as an independent variable in the fit makes it better suitable for various star trajectories. This method can be applied to any IACT and requires neither specific hardware nor interface or special data-taking mode. In this paper, we use the Large-Sized Telescope (LST) data to validate it as a useful tool to improve the determination of the pointing direction during regular data taking. The simulation studies show that the accuracy and precision of the method are comparable with the design requirements on the pointing accuracy of the LST (≤14″). With the typical LST event acquisition rate of 10 kHz, the method can achieve up to 50 Hz pointing monitoring rate, compared to 𝒪(1) Hz achievable with standard techniques. The application of the method to the LST prototype (LST-1) commissioning data shows the stable pointing performance of the telescope.

Observation and assignment of a high-resolution FTIR-spectrum of T[formula omitted]O, DT16O and HT16O in the range of 4300 to [formula omitted

In the range of 4300 to 4700cm−1, we present analysis of the 2ν1, 2ν2+ν3 and ν1+ν3 bands of T216O, the 2ν1 and ν1+2ν2 of DT16O and the 2ν1 of HT16O. The analysed high-resolution spectrum has been obtained from a Bruker IFS 125HR Fourier-transform spectrometer with a resolution of 0.025cm−1 using an optical cell with an activity of 10GBq. For the in total 2436 lines an individual positional uncertainty of up to 3.4×10-5cm−1 and a systematic uncertainty of 7.5×10-4cm−1 could be achieved. Four of the six bands have been analysed for the first time, the ν1+ν3 band of T216O and the 2ν1 of HT16O have been analysed in previous works of our group. These datasets are extended by 527 new lines and a cross check is confirming the consistency between both works. A comparison of the assigned line positions to the variationally calculated predictions from the Tomsk database agrees with previous findings indicating that band-specific shifts and shifts depending on the rotational quantum numbers are observed leading to an overall difference of up to 0.3cm−1.

Robustness of hypofractionated breast radiotherapy after breast-conserving surgery with free breathing.

This study aimed to evaluate the robustness with respect to the positional variations of five planning strategies in free-breathing breast hypofractionated radiotherapy (HFRT) for patients after breast-conserving surgery. Twenty patients who received breast HFRT with 42.72 Gy in 16 fractions were retrospectively analyzed. Five treatment planning strategies were utilized for each patient, including 1) intensity-modulated radiation therapy (IMRT) planning (IMRTpure); 2) IMRT planning with skin flash tool extending and filling the fluence outside the skin by 2cm (IMRTflash); 3) IMRT planning with planning target volume (PTV) extended outside the skin by 2cm in the computed tomography dataset (IMRTePTV); 4) hybrid planning, i.e., 2 Gy/fraction three-dimensional conformal radiation therapy combined with 0.67 Gy/fraction IMRT (IMRThybrid); and 5) hybrid planning with skin flash (IMRThybrid-flash). All plans were normalized to 95% PTV receiving 100% of the prescription dose. Six additional plans were created with different isocenter shifts for each plan, which were 1mm, 2mm, 3mm, 5mm, 7mm, and 10mm distally in the X (left-right) and Y (anterior-posterior) directions, namely, (X,Y), to assess their robustness, and the corresponding doses were recalculated. Variation of dosimetric parameters with increasing isocenter shift was evaluated. All plans were clinically acceptable. In terms of robustness to isocenter shifts, the five planning strategies followed the pattern IMRTePTV, IMRThybrid-flash, IMRTflash, IMRThybrid, and IMRTpure in descending order. V 95% of IMRTePTV maintained at 99.6% ± 0.3% with a (5,5) shift, which further reduced to 98.2% ± 2.0% with a (10,10) shift. IMRThybrid-flash yielded the robustness second to IMRTePTV with less risk from dose hotspots, and the corresponding V 95% maintained >95% up until (5,5). Considering the dosimetric distribution and robustness in breast radiotherapy, IMRTePTV performed best at maintaining high target coverage with increasing isocenter shift, while IMRThybrid-flash would be adequate with positional uncertainty<5mm.

Historical and Cultural Prerequisites for the Formation of the Modern Image of an Educational Counselor

Introduction to the problem. The uncertainty of the professional position of the position of educational counselor is associated with insufficient theoretical and methodological substantiation of the content and functions of the activity. It becomes relevant to turn to the historical and pedagogical analysis of socio-cultural conditions mediating the practice of realization of the educational activity of a teacher. The aim of the article: to show the historical and cultural origins in the activity of the educational counselor, to determine the possible conditions for the formation of a positive image of the counselor in modern conditions. The methodological basis of the study is formed by the provisions of systemic (V. G. Afanasiev, M. S. Kagan, etc.) and sociocultural (A. G. Asmolov, A. S. Akhiezer, etc.) approaches, theoretical provisions of the concept of constructing social reality (P. Berger, T. Lukman, etc.). Berger, T. Lukman, A. Schütz, etc.), including in the form of images of pedagogical reality (T. A. Romm), the idea of polysubjectivity of education (D. V. Grigoriev, N. L. Selivanova, etc.). Research Findings. The position of an educational counselor can be interpreted in different senses, which set different images of his/her activity. For the formation of a positive image of the educational counselor it is important to comprehend the channels of influence on its perception by the public and professional consciousness, taking into account the existing historical experience. The formation of perceptions of the modern image of the educational adviser is connected with the existence in the national pedagogical tradition of the role of the counselor - an adult leader in children’s social organization (“vozhatsky image”) and the educational component of class leadership (“educational image”). Conclusion. Addressing the problem of forming the image of the educational counselor becomes an important task of education, because it expands ideas about the essence and functions of counselors (information function); promotes the inclusion of educational counselors in the everyday social and educational reality (integration function); promotes consolidation and identification of the bearers of this role among other social and pedagogical subjects (identification role).

Object positional uncertainty modelling in 2D viewpoint planning

Viewpoint planning of terrestrial laser scanning surveys is often guided by the level of accuracy, which is a measure of radiated point precision that does not account for all factors affecting positional uncertainty. We propose the use of modelled object precision for viewpoint planning in a methodology that rigorously combines the three sources of positional uncertainty: the observations; registration; and the observation distribution. Our method is demonstrated on three 2D datasets by analyzing object precision in comparison to United States General Services Administration accuracy criterion. The results show the method's ability to 1) represent the precision for all objects in the environment; 2) identify problem areas where the level of accuracy specification is not met; and 3) inform densification measures needed to improve the design. Detailed explanations of the causes of design weaknesses accompany the results to illustrate the challenges of scanning complex built environments and to highlight solutions.

Point excess solute: A new metric for quantifying solute segregation in atom probe tomography datasets including application to naturally aged solute clusters in Al-Mg-Si-(Cu) alloys

Accurate, repeatable and quantitative analysis of nanoscale solute clustering in atom probe tomography (APT) datasets is a complex challenge which is made more difficult by the positional uncertainty and lack of absolute resolution inherent to the technique. In this work a new method, the point excess solute, is introduced for quantifying solute segregation in datasets with limited spatial resolution. This new method is based on measuring the matrix concentration using a dataset sampling method. We show the new method can accurately reproduce the values expected from synthetic datasets a priori and when the dataset spatial resolution and or phase contrast is too low for accurate quantification this is observable. The method is then applied to naturally aged solute clusters in the Al-Mg-Si-Cu system. Datasets were collected with a range of natural ageing times from 8 min to 76 weeks. The formation of the solute clusters is shown to be unaffected by the Cu content of the alloy.

Similarly slow diffusion of BAM and SecYEG complexes in live E. coli cells observed with 3D spt-PALM

The β-barrel assembly machinery (BAM) complex is responsible for inserting outer membrane proteins (OMPs) into the Escherichia coli outer membrane. The SecYEG translocon inserts inner membrane proteins into the inner membrane and translocates both soluble proteins and nascent OMPs into the periplasm. Recent reports describe Sec possibly playing a direct role in OMP biogenesis through interactions with the soluble polypeptide transport-associated (POTRA) domains of BamA (the central OMP component of BAM). Here we probe the diffusion behavior of these protein complexes using photoactivatable super-resolution localization microscopy and single-particle tracking in live E. coli cells of BAM and SecYEG components BamA and SecE and compare them to other outer and inner membrane proteins. To accurately measure trajectories on the highly curved cell surface, three-dimensional tracking was performed using double-helix point-spread function microscopy. All proteins tested exhibit two diffusive modes characterized by “slow” and “fast” diffusion coefficients. We implement a diffusion coefficient analysis as a function of the measurement lag time to separate positional uncertainty from true mobility. The resulting true diffusion coefficients of the slow and fast modes showed a complete immobility of full-length BamA constructs in the time frame of the experiment, whereas the OMP OmpLA displayed a slow diffusion consistent with the high viscosity of the outer membrane. The periplasmic POTRA domains of BamA were found to anchor BAM to other cellular structures and render it immobile. However, deletion of individual distal POTRA domains resulted in increased mobility, suggesting that these domains are required for the full set of cellular interactions. SecE diffusion was much slower than that of the inner membrane protein PgpB and was more like OMPs and BamA. Strikingly, SecE diffused faster upon POTRA domain deletion. These results are consistent with the existence of a BAM-SecYEG trans-periplasmic assembly in live E. coli cells.

Demonstration of sub-micron UCN position resolution using room-temperature CMOS sensor

High spatial resolution of ultracold neutron (UCN) measurement is of growing interest to UCN experiments such as UCN spectrometers, UCN polarimeters, quantum physics of UCNs, and quantum gravity. Here we utilize physics-informed deep learning to enhance the experimental position resolution and to demonstrate sub-micron spatial resolutions for UCN position measurements obtained using a room-temperature CMOS sensor, extending our previous work (Kuk et al., 2021; Yue et al., 2023) that demonstrated a position uncertainty of 1.5μm. We explore the use of the open-source software Allpix Squared to generate experiment-like synthetic hit images with ground-truth position labels. We use physics-informed deep learning by training a fully-connected neural network (FCNN) to learn a mapping from input hit images to output hit position. The automated analysis for sub-micron position resolution in UCN detection combined with the fast data rates of current and next generation UCN sources will enable improved precision for future UCN research and applications.

The 2021 mutual phenomena involving the Galilean satellites of Jupiter and the inner satellite Thebe

ABSTRACT Astrometric studies and orbital modelling of planetary moons have contributed significantly to advancing our understanding of their orbital dynamics. These studies require precise positions measured over extended periods. In this paper, we present the results of the 2021 Brazilian Jovian mutual phenomena campaign. The data correspond to eight events between Galilean satellites, in addition to a rare eclipse of Thebe, an inner satellite, totalling nine events. A geometric model along with the DE440/JUP365 ephemerides was used to reproduce the events and simulate the light curves. A Monte Carlo method and chi-squared statistics were used to fit the simulated light curves to the observations. The reflectance model adopted for our simulations was the complete version of the Oren–Nayer model. The average uncertainty of the relative positions of the Galilean satellites was 5 mas (15 km) and for the inner Thebe satellite 32 mas (96 km). The seven mutual events (nine independent observations) here analysed represent an addition of 17 per cent events (10 per cent light curves) with respect to the 2021 international mutual phenomena campaign. Furthermore, our result of Thebe eclipse is only the second measurement published to date. Our results contribute to the ephemeris data base, being fundamental to improving satellite orbits and thus minimizing their uncertainties.

Uncertainty quantification of the effect of cardiac position variability in the inverse problem of electrocardiographic imaging

Objective. Electrocardiographic imaging (ECGI) is a functional imaging modality that consists of two related problems, the forward problem of reconstructing body surface electrical signals given cardiac bioelectric activity, and the inverse problem of reconstructing cardiac bioelectric activity given measured body surface signals. ECGI relies on a model for how the heart generates bioelectric signals which is subject to variability in inputs. The study of how uncertainty in model inputs affects the model output is known as uncertainty quantification (UQ). This study establishes develops, and characterizes the application of UQ to ECGI. Approach. We establish two formulations for applying UQ to ECGI: a polynomial chaos expansion (PCE) based parametric UQ formulation (PCE-UQ formulation), and a novel UQ-aware inverse formulation which leverages our previously established ‘joint-inverse’ formulation (UQ joint-inverse formulation). We apply these to evaluate the effect of uncertainty in the heart position on the ECGI solutions across a range of ECGI datasets. Main results. We demonstrated the ability of our UQ-ECGI formulations to characterize the effect of parameter uncertainty on the ECGI inverse problem. We found that while the PCE-UQ inverse solution provided more complex outputs such as sensitivities and standard deviation, the UQ joint-inverse solution provided a more interpretable output in the form of a single ECGI solution. We find that between these two methods we are able to assess a wide range of effects that heart position variability has on the ECGI solution. Significance. This study, for the first time, characterizes in detail the application of UQ to the ECGI inverse problem. We demonstrated how UQ can provide insight into the behavior of ECGI using variability in cardiac position as a test case. This study lays the groundwork for future development of UQ-ECGI studies, as well as future development of ECGI formulations which are robust to input parameter variability.

Improvement of Digest2 NEO Classification Code—utilizing the Astrometry Data Exchange Standard

We describe enhancements to the digest2 software, a short-arc orbit classifier for heliocentric orbits. Digest2 is primarily used by the Near-Earth Object (NEO) community to flag newly discovered objects for a immediate follow-up and has been a part of NEO discovery process for more than 15 yr. We have updated the solar system population model used to weight the digest2 score according to the 2023 catalog of known solar system orbits and extended the list of mean uncertainties for 140 observatory codes. Moreover, we have added Astrometry Data Exchange Standard (ADES) input format support to digest2, which provides additional information for the astrometry, such as positional uncertainties for each detection. The digest2 code was also extended to read the roving observer astrometric format as well as the ability to compute a new parameter from the provided astrometric uncertainties () that can serve as an indicator of in-tracklet curvature when compared with tracklet’s great-circle fit rms. Comparison with the previous version of digest2 confirmed the improvement in accuracy of NEO identification and found that using ADES XML input significantly reduces the computation time of the digest2.