Uncertainty In Reconstruction Research Articles

Spectral function for He4 using the Chebyshev expansion in coupled-cluster theory

We compute spectral function for $^{4}\mathrm{He}$ by combining coupled-cluster theory with an expansion of integral transforms into Chebyshev polynomials. Our method allows us to estimate the uncertainty of spectral reconstruction. The properties of the Chebyshev polynomials make the procedure numerically stable and considerably lower in memory usage than the typically employed Lanczos algorithm. We benchmark our predictions with other calculations in the literature and with electron-scattering data in the quasi-elastic peak. The spectral function formalism allows one to extend ab initio lepton-nucleus cross sections into the relativistic regime. This makes it a promising tool for modeling this process at higher-energy transfers. The results we present open the door for studies of heavier nuclei, important for the neutrino oscillation programs.

Trends in reconstructed monthly, seasonal and annual flows for Irish catchments (1900–2016)

Trends in reconstructed monthly, seasonal and annual flows for Irish catchments (1900–2016)

Methods for robust estimates of tree biomass from pollen accumulation rates: Quantifying paleoecological reconstruction uncertainty

Pollen accumulation rates (PAR, grains cm–2 year–1) have been shown to be a reliable but methodologically complex bioproxy for quantitative reconstruction of past tree abundance. In a prior study, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and the pollen group TC (Taxaceae and Cupressaceae families) – were robust and precise estimators of contemporary tree biomass. This paper expands our earlier work. Here, we more fully evaluate the errors associated with biomass reconstructions to identify weaknesses and recommend improvements in PAR-based reconstructions of forest biomass. We account for uncertainty in our biomass proxy in a formal, coherent fashion. The greatest error was introduced by the age models, underscoring the need for improved statistical approaches to age-depth modeling. Documenting the uncertainty in pollen vegetation models should be standard practice in paleoecology. We also share insights gained from the delineation of the relevant source area of pollen, advances in Bayesian 210Pb modeling, the importance of site selection, and the use of independent data to corroborate biomass estimates. Lastly, we demonstrate our workflow with a new dataset of reconstructed tree biomass between 1850 and 2018 AD from lakes in the Klamath Mountains, California. Our biomass records followed a broad trend of low mean biomass in the ∼1850s followed by large contemporary increases, consistent with expectations of forest densification due to twentieth century fire suppression policies in the American West. More recent reconstructed tree biomass estimates also corresponded with silviculture treatments occurring within the relevant source area of pollen of our lake sites.

Optimization of Tunable Diode Laser Arrays for Inlet Mass Capture Measurement

Multibeam tunable diode laser absorption spectroscopy (TDLAS) sensors are used to measure mass flow in a complex, inhomogeneous flowfield with limited optical access. The cost and complexity of a TDLAS array increases with the number of beams, but adding beams does not necessarily improve accuracy. A technique to optimize the location and orientation of multiple laser beams for mass flow sensing in a 3D flow path geometry is developed and presented. We devised a statistical objective function that minimizes the uncertainty of estimates using a novel, linear formulation of absorption tomography with velocimetry (LATV). Beam arrangements that minimize the uncertainty of LATV reconstructions consequently maximize confidence in mass flow rate estimates; such arrangements are identified, subject to physical constraints on the pitch and catch optics. Our metric provides general guidance for the arrangement of a multibeam TDLAS mass flow sensor and does not require the use of tomographic reconstruction.

Reconstructing Stieltjes Functions from Their Approximate Values: A Search for a Needle in a Haystack

Material response of passive media to external influences is described by complex analytic functions of frequency that can always be written in terms of Stieltjes functions -- a special class of analytic functions mapping complex upper half-plane into itself. Reconstructing such functions from their experimentally measured values at specific frequencies is one of the central problems that we address in this paper. A definitive reconstruction algorithm that produces a certificate of optimality as well as a graphical representation of the uncertainty of reconstruction is proposed. Its effectiveness is demonstrated in the context of the electrochemical impedance spectroscopy.

A flexible method for estimating tip diversification rates across a range of speciation and extinction scenarios.

Estimates of diversification rates at the tips of a phylogeny provide a flexible approach for correlation analyses with multiple traits and to map diversification rates in space while also avoiding the uncertainty of deep time rate reconstructions. Available methods for tip rate estimation make different assumptions, and thus their accuracy usually depends on the characteristics of the underlying model generating the tree. Here, we introduce MiSSE, a trait-free, state-dependent speciation and extinction approach that can be used to estimate varying speciation, extinction, net diversification, turnover, and extinction fractions at the tips of the tree. We compare the accuracy of tip rates inferred by MiSSE against similar methods and demonstrate that, due to certain characteristics of the model, the error is generally low across a broad range of speciation and extinction scenarios. MiSSE can be used alongside regular phylogenetic comparative methods in trait-related diversification hypotheses, and we also describe a simple correction to avoid pseudoreplication from sister tips in analyses of independent contrasts. Finally, we demonstrate the capabilities of MiSSE, with a renewed focus on classic comparative methods, to examine the correlation between plant height and turnover rates in eucalypts, a species-rich lineage of flowering plants.

Progress and uncertainties in global and hemispheric temperature reconstructions of the Common Era

Global and hemispheric temperature reconstructions provide an important means of placing recent anthropogenic temperature trends in the context of preindustrial climate variations and evaluating their causes. As new reconstructions have been developed and estimates of past climate have been refined, results continue to show that by the late 20th century temperatures very likely exceeded those of any time in at least the last millennium. Despite progress over the last two decades, however, there remain persistent uncertainties with regard to, inter alia, first millennium temperatures at global and annual scales, the magnitude of multidecadal to millennial-scale changes and their causes, and the surface temperature response to volcanic eruptions. We review the strengths and limitations of existing global and hemispheric paleoclimate temperature reconstructions and highlight likely sources of extant uncertainties, all in the context of the recent Sixth Assessment Report from Working Group I of the Intergovernmental Panel on Climate Change. Based on our review of these factors, we provide recommendations for using, interpreting, and improving large-scale temperature reconstructions.

Assessing the intercolony δ18O proxy calibration in a coral microatoll and its implication for ENSO reconstruction in the northern South China Sea

Massive Porites corals are widely used for paleoclimate reconstruction, however the potential of Porites coral microatoll δ18O as high-resolution archive of paleoclimate has only been recognized recently, and the systematic chemistry-climate relationship has yet to be well characterized in the western Pacific. In this study, we examined the reproducibility of microatoll δ18O records against two adjacent Porites corals from the Xisha Islands in the northern South China Sea (SCS) and evaluated the reliability of microatoll δ18O as a proxy for reconstructing regional climate and El Niño-Southern Oscillation (ENSO) variability. The seasonal to interannual variability in microatoll δ18O was primarily controlled by local sea surface temperature (SST), while the δ18O signal might be suppressed by sea surface salinity (SSS) variations on interannual timescale. Despite the overlapping coral δ18O records exhibited similar patterns of variability, the mean values were consistently offset by ~0.2‰ and the sensitivity of δ18O proxy to climate also varied across different coral colonies. The microatoll δ18O exhibited relatively high proxy-SST sensitivities and amplitude of the seasonal variabilities. These results suggested that intercolony δ18O variability was a significant source of uncertainty in coral-based paleoclimate reconstructions. Microatoll δ18O anomaly appeared to serve as a sensitive and relatively reliable proxy for ENSO variability, although the imprints of weak-to-moderate ENSO events could not be fully captured due to the complex relationship between the East Asian Monsoon and ENSO, as well as the local seawater salinity changes. This study further strengthened the evidence for microatoll as an alternate climate archive in the SCS and highlighted its potential in helping resolve poorly understood paleoclimate before instrumental observations.

Ancient DNA reveals a southern presence of the Northeast Arctic cod during the Holocene.

Climate change has been implicated in an increased number of distributional shifts of marine species during the last century. Nonetheless, it is unclear whether earlier climatic fluctuations had similar impacts. We use ancient DNA to investigate the long-term spawning distribution of the Northeast Arctic cod (skrei) which performs yearly migrations from the Barents Sea towards spawning grounds along the Norwegian coast. The distribution of these spawning grounds has shifted northwards during the last century, which is thought to be associated with food availability and warming temperatures. We genetically identify skrei specimens from Ruskeneset in west Norway, an archaeological site located south of their current spawning range. Remarkably, 14C analyses date these specimens to the late Holocene, when temperatures were warmer than present-day conditions. Our results either suggest that temperature is not the only driver influencing the spawning distribution of Atlantic cod, or could be indicative of uncertainty in palaeoclimate reconstructions in this region. Regardless, our findings highlight the utility of aDNA to reconstruct the historical distribution of economically important fish populations and reveal the complexity of long-term ecological interactions in the marine environment.

Effect on null spaces of list-mode imaging systems due to increasing the number of attributes.

There are two types of uncertainty in image reconstructions from list-mode data: statistical and deterministic. One source of statistical uncertainty is the finite number of attributes of the detected particles, which are sampled from a probability distribution on the attribute space. A deterministic source of uncertainty is the effect that null functions of the imaging operator have on reconstructed pixel or voxel values. Quantifying the reduction in this deterministic source of uncertainty when more attributes are measured for each detected particle is the subject of this work. Specifically, upper bounds on an error metric are derived to quantify the error introduced in the reconstruction by the presence of null functions, and these upper bounds are shown to be reduced when the number of attributes is increased. These bounds are illustrated with an example of a two-dimensional single photon emission computed tomography (SPECT) system where the depth of interaction in the scintillation crystal is added to the attribute vector.

Time-resolved Rayleigh scattering tomography

Tomographic Rayleigh scattering (RS) imaging at a repetition rate of 10 kHz was demonstrated in non-reacting flows employing the second harmonic of a high-energy Nd: YAG burst-mode laser. Sequences of 100 images of the flow mixture fraction were directly derived from high-speed four-dimensional (4D) RS images. The tomographic reconstruction algorithm, measurement resolution, uncertainties, and jet flow mixing characteristics are discussed. Successful tomographic RS imaging using a high-energy burst-mode laser source lays the foundation for spatiotemporal, multidimensional analyses of density, mixture fraction, and temperature measurements in reacting and non-reacting flows of practical interest.

Verification of Satellite Railway Track Position Measurements Making Use of Standard Coordinate Determination Techniques

The article presents the results of satellite railway track position measurements performed by a multidisciplinary research team, the members of which represented Gdansk University of Technology and Gdynia Maritime University. Measuring methods are described which were used for reconstructing the railway track axis position and diagnosing railway track geometry deformations. As well as that, the description of the novel method developed by the authors to perform mobile GNSS measurements is included. The reported research aimed at assessing the uncertainty of railway track axis reconstruction making use of the dynamic GNSS method. To assess the applicability of this method, the obtained results were compared with those from the stationary measurement method used in railway business. The data used for comparison was recorded on the same railway track section during several measurement campaigns. In these campaigns, different types of GNSSs with different position recording frequencies (1–100 Hz) were used at different measurement speeds (5–70 km/h). The performed analysis has shown that the accuracy of railway track axis reconstruction making use of mobile GNSS measurements is sufficient for using this methodology in railway business.

Active Visuo-Haptic Object Shape Completion

Recent advancements in object shape completion have enabled impressive object reconstructions using only visual input. However, due to self-occlusion, the reconstructions have high uncertainty in the occluded object parts, which negatively impacts the performance of downstream robotic tasks such as grasping. In this work, we propose an active visuo-haptic shape completion method called Act-VH that actively computes where to touch the objects based on the reconstruction uncertainty. Act-VH reconstructs objects from point clouds and calculates the reconstruction uncertainty using IGR, a recent state-of-the-art implicit surface deep neural network. We experimentally evaluate the reconstruction accuracy of Act-VH against five baselines in simulation and in the real world. We also propose a new simulation environment for this purpose. The results show that Act-VH outperforms all baselines and that an uncertainty-driven haptic exploration policy leads to higher reconstruction accuracy than a random policy and a policy driven by Gaussian Process Implicit Surfaces. As a final experiment, we evaluate Act-VH and the best reconstruction baseline on grasping 10 novel objects. The results show that Act-VH reaches a significantly higher grasp success rate than the baseline on all objects. Together, this work opens up the door for using active visuo-haptic shape completion in more complex cluttered scenes.

Variation of surface soil δ13Corg in the upper and middle reaches of the Yarlung Zangbo river basin, southern Tibetan Plateau, and its climatic implications

Understanding the origin of the stable carbon isotope composition of the organic matter (δ13Corg) in surface soil is critical for using δ13Corg in geological archives to reconstruct environmental and climatic changes. However, the relationship between soil δ13Corg and climatic factors varies in different climatic regimes, resulting in uncertainties in climatic reconstructions. We measured the δ13Corg of 79 surface soil samples collected from the upper and middle reaches of the Yarlung Zangbo river basin (YZRB), southern Tibetan Plateau, in order to explore their spatial variations and environmental implications. The soil δ13Corg values range from −28.1‰ to −15.2‰, with an average of −22.8‰ and a modal value of around −25‰ to −23‰. Higher δ13Corg values occur in the central part of the YZRB (Lazi-Nedong) and lower δ13 Corg values occur in the western (Gar-Lazi) and eastern (Nedong-Bomi) parts. The variations in soil δ13Corg are significantly correlated with altitude (with a boundary at ~3500 m a.s.l.). The co-variation of temperature and precipitation is responsible for the effect of altitude on soil δ13Corg, with temperature (mainly warmest season temperature) being the main controlling factor above 3500 m a.s.l., and precipitation the main factor below 3500 m a.s.l.. Higher absolute values of the regression coefficients for the relationships between soil δ13Corg and altitude (−5.1‰/km) and with mean annual temperature (+0.56‰/°C) above 3500 m may be due to the higher proportion of C4 plants in the central part of the YZRB, making it necessary to avoid the influence of C4 plants when using soil δ13Corg to reconstruct altitude or temperature. However, soil δ13Corg may be useful for precipitation reconstruction below 3500 m a.s.l., where C3 plants dominate.

A probabilistic approach to tomography and adjoint state methods, with an application to full waveform inversion in medical ultrasound

Bayesian methods are a popular research direction for inverse problems. There are a variety of techniques available to solve Bayes’ equation, each with their own strengths and limitations. Here, we discuss stochastic variational inference (SVI), which solves Bayes’ equation using gradient-based methods. This is important for applications which are time-limited (e.g. medical tomography) or where solving the forward problem is expensive (e.g. adjoint methods). To evaluate the use of SVI in both these contexts, we apply it to ultrasound tomography of the brain using full-waveform inversion (FWI). FWI is a computationally expensive adjoint method for solving the ultrasound tomography inverse problem, and we demonstrate that SVI can be used to find a no-cost estimate of the pixel-wise variance of the sound-speed distribution using a mean-field Gaussian approximation. In other words, we show experimentally that it is possible to estimate the pixel-wise uncertainty of the sound-speed reconstruction using SVI and a common approximation which is already implicit in other types of iterative reconstruction. Uncertainty estimates have a variety of uses in adjoint methods and tomography. As an illustrative example, we focus on the use of uncertainty for image quality assessment. This application is not limiting; our variance estimator has effectively no computational cost and we expect that it will have applications in fields such as non-destructive testing or aircraft component design where uncertainties may not be routinely estimated.

Summer sea-ice variability on the Antarctic margin during the last glacial period reconstructed from snow petrel (<i>Pagodroma nivea</i>) stomach-oil deposits

Abstract. Antarctic sea ice is a critical component of the climate system affecting a range of physical and biogeochemical feedbacks and supporting unique ecosystems. During the last glacial stage, Antarctic sea ice was more extensive than today, but uncertainties in geological (marine sediments), glaciological (ice core), and climate model reconstructions of past sea-ice extent continue to limit our understanding of its role in the Earth system. Here, we present a novel archive of past sea-ice environments from regurgitated stomach oils of snow petrels (Pagodroma nivea) preserved at nesting sites in Dronning Maud Land, Antarctica. We show that by combining information from fatty acid distributions and their stable carbon isotope ratios with measurements of bulk carbon and nitrogen stable isotopes and trace metal data, it is possible to reconstruct changing snow petrel diet within Marine Isotope Stage 2 (ca. 24.3–30.3 cal kyr BP). We show that, as today, a mixed diet of krill and fish characterizes much of the record. However, between 27.4 and 28.7 cal kyr BP signals of krill almost disappear. By linking dietary signals in the stomach-oil deposits to modern feeding habits and foraging ranges, we infer the use by snow petrels of open-water habitats (“polynyas”) in the sea ice during our interval of study. The periods when consumption of krill was reduced are interpreted to correspond to the opening of polynyas over the continental shelf, which became the preferred foraging habitat. Our results show that extensive, thick, and multiyear sea ice was not always present close to the continent during the last glacial stage and highlight the potential of stomach-oil deposits as a palaeoenvironmental archive of Southern Ocean conditions.

Limited Lateral Transport Bias During Export of Sea Surface Temperature Proxy Carriers in the Mediterranean Sea.

Some lipid‐biomarker‐based sea surface temperature (SST) proxies applied in the modern Mediterranean Sea exhibit large offsets from expected values, generating uncertainties in climate reconstructions. Lateral transport of proxy carriers along ocean currents prior to burial can contribute to this offset between reconstructed and expected SSTs. We perform virtual particle tracking experiments to simulate transport prior to and during sinking and derive a quantitative estimate of transport bias for alkenones and glycerol dibiphytanyl glycerol tetraethers (GDGTs), which form the basis of the UK’ 37 and TEX86 paleothermometers, respectively. We use a simple 30‐day surface advection scenario and sinking speeds appropriate for the export of various proxy carriers (6, 12, 25, 50, 100, 250, 500, and 1000 md−1). For the assessed scenarios, lateral transport bias is generally small (always <0.85°C) within the Mediterranean Sea and does not substantially contribute to uncertainties in UK’ 37‐ or TEX86‐based SSTs.

Grayscale uncertainty and errors of tomographic reconstructions based on projection geometries and projection sets

Grayscale uncertainty and errors of tomographic reconstructions based on projection geometries and projection sets

Operational daily evapotranspiration mapping at field scale based on SSEBop model and spatiotemporal fusion of multi-source remote sensing data.

Accurate understanding of daily evapotranspiration (ET) at field scale is of great significance for agricultural water resources management. The operational simplified surface energy balance (SSEBop) model has been applied to estimate field scale ET with Landsat satellite imagery. However, there is still uncertainty in the ET time reconstruction for cloudy days based on limited clear days’ Landsat ET fraction (ETf) computed by SSEBop. The Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data can provide daily surface observation over clear-sky areas. This paper presented an enhanced gap-filling scheme for the SSEBop ET model, which improved the temporal resolution of Landsat ETf through the spatio-temporal fusion with SSEBop MODIS ETf on clear days and increased the time reconstruction accuracy of field-scale ET. The results were validated with the eddy covariance (EC) measurements over cropland in northwestern China. It indicated that the improved scheme performed better than the original SSEBop Landsat approach in daily ET estimation, with higher Nash-Sutcliffe efficiency (NSE, 0.75 vs. 0.70), lower root mean square error (RMSE, 0.95 mm·d-1 vs. 1.05 mm·d-1), and percent bias (PBias, 16.5% vs. 25.0%). This fusion method reduced the proportion of deviation (13.3% vs. 25.5%) in the total errors and made the random error the main proportion, which can be reduced over time and space in regional ET estimation. It also evidently improved the underestimation of crop ET by the SSEBop Landsat scheme during irrigation before sowing and could more accurately describe the synergistic changes of soil moisture and cropland ET. The proposed MODIS and Landsat ETf fusion can significantly improve the accuracy of SSEBop in estimating field-scale ET.

Evaluation of intraoral optical scanning accuracy for fine structure reconstruction and occlusal records of inlay/onlay preparations.

The present study aimed to determine the impact of different degrees of salivary contamination and variations in occlusal force during intraoral scanning of inlay/onlay cavities on the accuracy of fine structure reconstruction and occlusal records. Digital data of inlay/onlay models, collected using an intraoral scanner, were divided into 40 groups according to the restoration type (onlay or inlay), salivary contamination level (none, completely dry; mild, moist but not visually completely apparent; moderate, half-filled cavity; severe, filled-up cavity), and simulated occlusal force (0, 2, 4, 6 or 8 kg). The acquired 120 datasets were used to measure the average interocclusal space and cavity buccolingual internal angle. Salivary contamination and occlusal force did affect the occlusal contact (P < 0.001), but restoration type did not (P > 0.05). An interaction was found between inlay type and salivary contamination (P < 0.001), but not between occlusal force and salivary contamination (P > 0.05). Salivary contamination also affected the accuracy of fine structure reconstruction (P < 0.001), but restoration type did not (P > 0.05), and no interaction was found between the two factors (P > 0.05). The difference in the measured internal angle increased with the increase in salivary contamination. Intraoral optical scanning of inlay/onlay preparations was reliable for recording occlusal contact but showed uncertainty in cavity fine structure reconstruction when moderate or severe salivary contamination was present in the cavity. Nevertheless, a moist cavity surface with no visually apparent salivary contamination is acceptable. (Int J Comput Dent 2022;25(3):257-265; doi: 10.3290/j.ijcd.b2599691).