Known Sources Of Error Research Articles

All-optical method to directly measure the pressure–volume–temperature equation of state of fluids in the diamond anvil cell

We have developed a new all-optical method to directly measure the pressure–volume–temperature (PVT) equation of state (EOS) of fluids and transparent solids in the diamond anvil high pressure cell by measuring the volume of the sample chamber. Our method combines confocal microscopy and white light interference with a new analysis method, which exploits the mutual dependence of sample density and refractive index: Experimentally, the refractive index determines the measured sample chamber thickness (and therefore the measured sample volume/density), yet the sample density is by far the dominant factor in determining the variation in the refractive index with pressure. Our analysis method allows us to obtain a set of values for the density and refractive index, which are mutually consistent and agree with the experimental data within error. We have conducted proof-of-concept experiments on a variety of samples (H2O, CH4, C2H6, C3H8, KCl, and NaCl) at ambient temperature and at high temperatures up to just above 500 K. Our proof-of-concept data demonstrate that our method is able to reproduce known fluid and solid EOS within error. Furthermore, we demonstrate that our method allows us to directly and routinely measure the PVT EOS of simple fluids at GPa pressures up to, at least, 514 K (the highest temperature reached in our study). A reasonable estimation of the known sources of error in our volume determinations indicates that the error is currently ±2.7% at high temperature and that it is feasible to reduce it to ca. ±1% in future work.

4 Standardization of Devices, Methods and Units of Measurement of Infectious and Non-Infectious Bioaerosols in the Workplace: Literature Review

Abstract There is currently a disconnect between the occupational hygienist and the epidemiologist in establishing quantitative relationships between exposure and resulting acute and chronic diseases. This disconnect is the result of a lack of standardization for assessing worker exposure to pathogenic biological agents. Specifically, there are numerous combinations of devices, analytical methods and units of measurement used in hygiene and epidemiological studies that prevent study to study comparisons and development of a uniform body of knowledge. Several recent reviews have concluded that occupational exposure limits for biological agents cannot be established due to this lack of standardization. The problem is exacerbated by the fact that most studies use area monitoring rather than breathing zone monitoring, a known source of error in defining worker dose. This review will use specific agents such as Legionella, Coccidioides, Endotoxin, Metalworking Fluid Mist, Flour Dust and Compost Dust to define the problem and suggest possible solutions.

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography reading are unknown. Purpose To determine how automation bias can affect inexperienced, moderately experienced, and very experienced radiologists when reading mammograms with the aid of an artificial intelligence (AI) system. Materials and Methods In this prospective experiment, 27 radiologists read 50 mammograms and provided their Breast Imaging Reporting and Data System (BI-RADS) assessment assisted by a purported AI system. Mammograms were obtained between January 2017 and December 2019 and were presented in two randomized sets. The first was a training set of 10 mammograms, with the correct BI-RADS category suggested by the AI system. The second was a set of 40 mammograms in which an incorrect BI-RADS category was suggested for 12 mammograms. Reader performance, degree of bias in BI-RADS scoring, perceived accuracy of the AI system, and reader confidence in their own BI-RADS ratings were assessed using analysis of variance (ANOVA) and repeated-measures ANOVA followed by post hoc tests and Kruskal-Wallis tests followed by the Dunn post hoc test. Results The percentage of correctly rated mammograms by inexperienced (mean, 79.7% ± 11.7 [SD] vs 19.8% ± 14.0; P < .001; r = 0.93), moderately experienced (mean, 81.3% ± 10.1 vs 24.8% ± 11.6; P < .001; r = 0.96), and very experienced (mean, 82.3% ± 4.2 vs 45.5% ± 9.1; P = .003; r = 0.97) radiologists was significantly impacted by the correctness of the AI prediction of BI-RADS category. Inexperienced radiologists were significantly more likely to follow the suggestions of the purported AI when it incorrectly suggested a higher BI-RADS category than the actual ground truth compared with both moderately (mean degree of bias, 4.0 ± 1.8 vs 2.4 ± 1.5; P = .044; r = 0.46) and very (mean degree of bias, 4.0 ± 1.8 vs 1.2 ± 0.8; P = .009; r = 0.65) experienced readers. Conclusion The results show that inexperienced, moderately experienced, and very experienced radiologists reading mammograms are prone to automation bias when being supported by an AI-based system. This and other effects of human and machine interaction must be considered to ensure safe deployment and accurate diagnostic performance when combining human readers and AI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Baltzer in this issue.

A High-precision Survey of the D/H Ratio in the Nearby Interstellar Medium

We present high signal-to-noise ratio measurements of the H i Lyα absorption line toward 16 Galactic targets that are at distances between approximately 190 and 2200 pc, all beyond the wall of the Local Bubble. We describe the models used to remove stellar emission and absorption features and the methods used to account for all known sources of error in order to compute high-precision values of the H i column density with robust determinations of the uncertainties. When combined with H2 column densities from other sources, we find total H column densities ranging from 1020.01 to 1021.25 cm−2. Using deuterium column densities from Far Ultraviolet Spectroscopic Explorer observations we determine the D/H ratio along the sight lines. We confirm and strengthen the conclusion that D/H is spatially variable over these H i column density and target distance regimes, which predominantly probe the interstellar medium outside the Local Bubble. We discuss how these results affect models of Galactic chemical evolution. We also present an analysis of metal lines along the five sight lines for which we have high-resolution spectra and, along with results reported in the literature, discuss the corresponding column densities in the context of a generalized depletion analysis. We find that D/H is only weakly correlated with metal depletion and conclude that the spatial D/H variability is not solely due to dust depletion. A bifurcation of D/Htot as a function of depletion at high depletion levels provides modest support that deuterium-rich gas is infalling onto the Galactic plane.

Evidence of an Absence of Inbreeding Depression in a Wild Population of Weddell Seals (Leptonychotes weddellii).

Inbreeding depression can reduce the viability of wild populations. Detecting inbreeding depression in the wild is difficult; developing accurate estimates of inbreeding can be time and labor intensive. In this study, we used a two-step modeling procedure to incorporate uncertainty inherent in estimating individual inbreeding coefficients from multilocus genotypes into estimates of inbreeding depression in a population of Weddell seals (Leptonychotes weddellii). The two-step modeling procedure presented in this paper provides a method for estimating the magnitude of a known source of error, which is assumed absent in classic regression models, and incorporating this error into inferences about inbreeding depression. The method is essentially an errors-in-variables regression with non-normal errors in both the dependent and independent variables. These models, therefore, allow for a better evaluation of the uncertainty surrounding the biological importance of inbreeding depression in non-pedigreed wild populations. For this study we genotyped 154 adult female seals from the population in Erebus Bay, Antarctica, at 29 microsatellite loci, 12 of which are novel. We used a statistical evidence approach to inference rather than hypothesis testing because the discovery of both low and high levels of inbreeding are of scientific interest. We found evidence for an absence of inbreeding depression in lifetime reproductive success, adult survival, age at maturity, and the reproductive interval of female seals in this population.

A statistical evaluation of ballistic backmapping for the slow solar wind: The interplay of solar wind acceleration and corotation

Abstract Mapping solar wind plasma back to its source is often achieved using the ‘two-step ballistic backmapping’ method. Solar wind observations are mapped through the heliosphere to the edge of a PFSS model, by assuming a constant speed, radial, plasma flow. Tracing field lines through the model gives the source location at 1 R⊙ The heliospheric mapping component hinges upon the argument that two known sources of error, stemming from solar wind acceleration and non-radial flow, effectively cancel. This assumption has not been tested statistically. In this study, we evaluate the heliospheric portion of two-step backmapping, in addition to mapping using models with explicit radial acceleration, and azimuthal velocity, vφ, derived from angular momentum conservation. We estimate longitudinal mapping offsets, Δφ, between 326 Earth-observed crossings of the heliospheric current sheet (HCS), and corresponding crossings at 2.5 R⊙ from PFSS models. While the detailed solar wind models can be optimised to produce Δφ in good average agreement with HCS crossing data, the ballistic mapping performs almost as well, although all residuals have a sizeable standard deviation σ ∼ 16○. We conclude that the proposed error cancellation likely contributes to the good performance of ballistic mapping. However, interplanetary acceleration and the height of effective solar wind corotation are both smaller than previously assumed. Our results further suggest that early Parker Solar Probe observations of large vφ around 36 R⊙ do not represent the overall solar wind, due to the requirement for it to be balanced by increased acceleration.

Improving Localization of Cardiac Geometry Using ECGI.

Electrocardiographic imaging (ECGI) requires a model of the torso, and inaccuracy in the position of the heart is a known source of error. We previously presented a method to localize the heart when body and heart surface potentials are known. The goal of this study is to extend this approach to only use body surface potentials. We used an iterative coordinate descent optimization to estimate the positions of the heart for several consecutive heartbeats relying on the assumption that the epicardial potential sequence is the same in each beat. The method was tested with data synthesized using measurements from a isolated-heart, torso-tank preparation. Improvement was evaluated in terms of both heart localization and ECGI accuracy. The geometric correction resulted in cardiac geometries closely matching ground truth geometry. ECGI accuracy increased dramatically by all metrics using the corrected geometry. Future studies will employ more realistic animal models and then human subjects. Success could impact clinical ECGI by reducing errors from respiratory movement and perhaps decrease imaging requirements, reducing both cost and logistical difficulty of ECGI, widening clinical applicability.

Benchmarking a High-Fidelity Mixed-Species Entangling Gate.

We implement a two-qubit logic gate between a ^{43}Ca^{+} hyperfine qubit and a ^{88}Sr^{+} Zeeman qubit. For this pair of ion species, the S-P optical transitions are close enough that a single laser of wavelength 402nm can be used to drive the gate but sufficiently well separated to give good spectral isolation and low photon scattering errors. We characterize the gate by full randomized benchmarking, gate set tomography, and Bell state analysis. The latter method gives a fidelity of 99.8(1)%, comparable to that of the best same-species gates and consistent with known sources of error.

Practical trapped-ion protocols for universal qudit-based quantum computing

The notion of universal quantum computation can be generalized to multi-level qudits, which offer advantages in resource usage and algorithmic efficiencies. Trapped ions, which are pristine and well-controlled quantum systems, offer an ideal platform to develop qudit-based quantum information processing. Previous work has not fully explored the practicality of implementing trapped-ion qudits accounting for known experimental error sources. Here, we describe a universal set of protocols for state preparation, single-qudit gates, a new generalization of the M\o{}lmer-S\o{}rensen gate for two-qudit gates, and a measurement scheme which utilizes shelving to a meta-stable state. We numerically simulate known sources of error from previous trapped ion experiments, and show that there are no fundamental limitations to achieving fidelities above \(99\%\) for three-level qudits encoded in \(^{137}\mathrm{Ba}^+\) ions. Our methods are extensible to higher-dimensional qudits, and our measurement and single-qudit gate protocols can achieve \(99\%\) fidelities for five-level qudits. We identify avenues to further decrease errors in future work. Our results suggest that three-level trapped ion qudits will be a useful technology for quantum information processing.

Development of a total hip replacement phantom for the assessment of CT-image quality.

The quality of computed tomography (CT) imaging is important when used to judge the success of joint replacement surgery. Metal artefacts are a known source of error, typically compensated by noise reduction software. To develop a transportable and stable system for the assessment of image quality of bone lesions around orthopedic implants. The design and manufacture of a bone-implant-phantom is described, which is based on a calf acetabulum with surrounding pelvic bone structures. Bone lesions of several sizes were created in the acetabulum before implanting the cup of an uncemented hip prosthesis, which was fixed with a stainless-steel bone screw. Plastic strips were placed on a cobalt-chromium stemmed femoral component, simulating typical bone lesions around loosening or infected prostheses, before embedding the stem in material similar to bone and shaped like a femur. The head of the femoral component was then placed in the acetabular cup and CT scans were produced. It was possible to construct a durable CT hip phantom for quality assurance work. The usability of different materials and the choices made for the phantom are discussed. It is possible to construct a durable joint implant phantom for quality assurance and scanner hardware and software assessment with limited resources. The phantom was successfully used in the assessment of the hardware and software performance of different CT scanners.

The Prevalence of Defensive Gun Use: Possible Sources of Error and the Results of 21 National Surveys

The merits of gun control as a policy for reducing violence depend on the costs and benefits of the controls. It has been argued that one significant cost of some controls could be reducing opportunities for crime victims to use guns for self-protection. The potential significance of these opportunity costs are dependent on just how often crime victims actually use guns for defense. This paper synthesizes the results of 21 professionally conducted national surveys of probability samples of the U.S. adult population, analyzes the likely sources of error in surveys, and compares prevalence of defensive gun use (DGU) indicated by the surveys with the highest available national estimates of the number of offensive/criminal uses of guns. Evidence on known sources of error indicates that almost all of them tend to make DGU prevalence estimates too low. Finally, national surveys consistently indicate that defensive uses of guns by crime victims are far more frequent than offensive uses by offenders to attack or threaten victims.

A general method for motion compensation in x-ray computed tomography

Motion during data acquisition is a known source of error in medical tomography, resulting in blur artefacts in the regions that move. It is critical to reduce these artefacts in applications such as image-guided radiation therapy as a clearer image translates into a more accurate treatment and the sparing of healthy tissue close to a tumour site. Most research in 4D x-ray tomography involving the thorax relies on respiratory phase binning of the acquired data and reconstructing each of a set of images using the limited subset of data per phase. In this work, we demonstrate a motion-compensation method to reconstruct images from the complete dataset taken during breathing without recourse to phase-binning or breath-hold techniques. As long as the motion is sufficiently well known, the new method can accurately reconstruct an image at any time during the acquisition time span. It can be applied to any iterative reconstruction algorithm.

Ice-Phase Precipitation

AbstractIce-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

Ontogeny of bite force in a validated biomechanical model of the American alligator.

Three-dimensional computational modeling offers tools with which to investigate forces experienced by the skull during feeding and other behaviors. American alligators (Alligator mississippiensis) generate some of the highest measured bite forces among extant tetrapods. A concomitant increase in bite force accompanies ontogenetic increases in body mass, which has been linked with dietary changes as animals increase in size. Because the flattened skull of crocodylians has substantial mediolaterally oriented muscles, crocodylians are an excellent model taxon in which to explore the role of mediolateral force components experienced by the feeding apparatus. Many previous modeling studies of archosaur cranial function focused on planar analysis, ignoring the mediolateral aspects of cranial forces. Here, we used three-dimensionally accurate anatomical data to resolve 3D muscle forces. Using dissection, imaging and computational techniques, we developed lever and finite element models of an ontogenetic series of alligators to test the effects of size and shape on cranial loading and compared estimated bite forces with those previously measured in vivo in A. mississippiensis We found that modeled forces matched in vivo data well for intermediately sized individuals, and somewhat overestimated force in smaller specimens and underestimated force in larger specimens, suggesting that ontogenetically static muscular parameters and bony attachment sites alone cannot account for all the variation in bite force. Adding aponeurotic muscle attachments would likely improve force predictions, but such data are challenging to model and integrate into analyses of extant taxa and are generally unpreserved in fossils. We conclude that anatomically accurate modeling of muscles can be coupled with finite element and lever analyses to produce reliable, reasonably accurate estimate bite forces and thus both skeletal and joint loading, with known sources of error, which can be applied to extinct taxa.

Spatio-temporal filtering techniques for the detection of disaster-related communication

Individuals predominantly exchange information with one another through informal, interpersonal channels. During disasters and other disrupted settings, information spread through informal channels regularly outpaces official information provided by public officials and the press. Social scientists have long examined this kind of informal communication in the rumoring literature, but studying rumoring in disrupted settings has posed numerous methodological challenges. Measuring features of informal communication–timing, content, location–with any degree of precision has historically been extremely challenging in small studies and infeasible at large scales. We address this challenge by using online, informal communication from a popular microblogging website and for which we have precise spatial and temporal metadata. While the online environment provides a new means for observing rumoring, the abundance of data poses challenges for parsing hazard-related rumoring from countless other topics in numerous streams of communication. Rumoring about disaster events is typically temporally and spatially constrained to places where that event is salient. Accordingly, we use spatio and temporal subsampling to increase the resolution of our detection techniques. By filtering out data from known sources of error (per rumor theories), we greatly enhance the signal of disaster-related rumoring activity. We use these spatio-temporal filtering techniques to detect rumoring during a variety of disaster events, from high-casualty events in major population centers to minimally destructive events in remote areas. We consistently find three phases of response: anticipatory excitation where warnings and alerts are issued ahead of an event, primary excitation in and around the impacted area, and secondary excitation which frequently brings a convergence of attention from distant locales onto locations impacted by the event. Our results demonstrate the promise of spatio-temporal filtering techniques for “tuning” measurement of hazard-related rumoring to enable observation of rumoring at scales that have long been infeasible.

Multiple-Target Visual Search Errors

Visual search—the ability to locate visual targets among distractors—is a fundamental part of professional performance for many careers, including radiology, airport security screening, cytology, lifeguarding, and more. Successful execution of visual search in these settings is critically important because the consequences of a missed target can be horrific. Unfortunately, many of these professions place high demands on the people performing the searches, and either the task or the environment (or both) could lead to significant errors. One known source of error that exists across many fields is “multiple-target visual search” errors—a target is less likely to be detected if another target was already found in the same search than if the target was the only one present. These errors have proven to be stubborn and not easily eliminated. This article offers a brief overview of the existing research on multiple-target visual search errors and discusses possible policy implications of the errors for airport security screening. The policy suggestions are based on empirical research, with the hope of providing food for thought on using scientific data and theory to improve performance. Specifically, three policy suggestions are raised: shift screening to a remote location away from the checkpoint, reduce the number of prohibited items to lessen the searchers’ cognitive burden, and emphasize search consistency in the training process. Note that the focus here is on airport security screening, as this is a domain most readers can relate to, but the suggestions can equally apply to many search environments.

Good practice statements on safe laboratory testing: A mixed methods study by the LINNEAUS collaboration on patient safety in primary care

ABSTRACTBackground: The systems-based management of laboratory test ordering and results handling is a known source of error in primary care settings worldwide. The consequences are wide-ranging for patients (e.g. avoidable harm or poor care experience), general practitioners (e.g. delayed clinical decision making and potential medico-legal implications) and the primary care organization (e.g. increased allocation of resources to problem-solve and dealing with complaints). Guidance is required to assist care teams to minimize associated risks and improve patient safety.Objective: To identify, develop and build expert consensus on ‘good practice’ guidance statements to inform the implementation of safe systems for ordering laboratory tests and managing results in European primary care settings.Methods: Mixed methods studies were undertaken in the UK and Ireland, and the findings were triangulated to develop ‘good practice’ statements. Expert consensus was then sought on the findings at the wider European level via a Delphi group meeting during 2013.Results: We based consensus on 10 safety domains and developed 77 related ‘good practice’ statements (≥ 80% agreement levels) judged to be essential to creating safety and minimizing risks in laboratory test ordering and subsequent results handling systems in international primary care.Conclusion: Guidance was developed for improving patient safety in this important area of primary care practice. We need to consider how this guidance can be made accessible to frontline care teams, utilized by clinical educators and improvement advisers, implemented by decision makers and evaluated to determine acceptability, feasibility and impacts on patient safety.

Validating predictions of unobserved quantities

The ultimate purpose of most computational models is to make predictions, commonly in support of some decision-making process (e.g., for design or operation of some system). The quantities that need to be predicted (the quantities of interest or QoIs) are generally not experimentally observable before the prediction, since otherwise no prediction would be needed. Assessing the validity of such extrapolative predictions, which is critical to informed decision-making, is challenging. In classical approaches to validation, model outputs for observed quantities are compared to observations to determine if they are consistent. By itself, this consistency only ensures that the model can predict the observed quantities under the conditions of the observations. This limitation dramatically reduces the utility of the validation effort for decision making because it implies nothing about predictions of unobserved QoIs or for scenarios outside of the range of observations. However, there is no agreement in the scientific community today regarding best practices for validation of extrapolative predictions made using computational models. The purpose of this paper is to propose and explore a validation and predictive assessment process that supports extrapolative predictions for models with known sources of error. The process includes stochastic modeling, calibration, validation, and predictive assessment phases where representations of known sources of uncertainty and error are built, informed, and tested. The proposed methodology is applied to an illustrative extrapolation problem involving a misspecified nonlinear oscillator.

Mars Science Laboratory Entry Atmospheric Data System Trajectory and Atmosphere Reconstruction

On 5 August 2012, the Mars Science Laboratory entry vehicle successfully entered Mars’s atmosphere and landed the Curiosity rover on its surface. The entry vehicle carried a system of heat shield instrumentation that measured the aerodynamic and aerothermal environment during entry. Included in these sensors were seven pressure transducers linked to ports across the entry vehicle forebody that recorded the local surface pressures during entry. These measured surface pressures were used to generate estimates of atmospheric quantities based on computationally modeled surface pressure distributions. Angle of attack, angle of sideslip, dynamic pressure, Mach number, atmospheric conditions, and vehicle aerodynamics were reconstructed from the measured pressures. Three data reduction algorithms using subsets of the available data were used to assess data quality and interpret the entry performance. A Kalman filter algorithm was used to combine all available data for a final, complete reconstruction. The reconstruction results indicate that the data quality was good, and aerodynamic performance was within the uncertainties of preflight models. The three independent reconstructions are in overall good agreement, with several small anomalies that were reconciled using reasonable corrections within known sources of error. The combined Kalman filter reconstruction identified winds that are reasonable compared with preflight atmospheric models.

LAGEOS II pericenter general relativistic precession (1993–2005): Error budget and constraints in gravitational physics

The aim of this paper is to extend, clarify, and deepen the results of our previous work [D. M. Lucchesi and R. Peron, Phys. Rev. Lett. 105, 231103 (2010)], related to the precise measurement of LAGEOS (LAser GEOdynamics Satellite) II pericenter shift. A 13-year time span of LAGEOS satellites' laser tracking data has been considered, obtaining a very precise orbit and correspondingly residuals time series from which to extract the relevant signals. A thorough description is provided of the data analysis strategy and the dynamical models employed, along with a detailed discussion of the known sources of error in the experiment, both statistical and systematic. From this analysis, a confirmation of the predictions of Einstein's general relativity, as well as strong bounds on alternative theories of gravitation, clearly emerge. In particular, taking conservatively into account the stricter error bound due to systematic effects, general relativity has been confirmed in the Earth's field at the 98% level (meaning the measurement of a suitable combination of $\ensuremath{\beta}$ and $\ensuremath{\gamma}$ PPN parameters in weak-field conditions). This bound has been used to constrain possible deviations from the inverse-square law parameterized by a Yukawa-like new long range interaction with strength $|\ensuremath{\alpha}|\ensuremath{\lesssim}1\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}$ at a characteristic range $\ensuremath{\lambda}\ensuremath{\simeq}1$ Earth radius, a possible nonsymmetric gravitation theory with the interaction parameter ${\mathcal{C}}_{\ensuremath{\bigoplus}\text{LAGEOS II}}{\ensuremath{\lesssim}\text{(9 \ifmmode\times\else\texttimes\fi{} 10}}^{\ensuremath{-}2}\text{ }\text{ }\mathrm{km}{)}^{4}$, and a possible spacetime torsion with a characteristic parameter combination $|2{t}_{2}+{t}_{3}|\ensuremath{\lesssim}7\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}2}$. Conversely, if we consider the results obtained from our best fit of the LAGEOS II orbit, the constraints in fundamental physics improve by at least 2 orders of magnitude.