Systematic Effects Research Articles

Improving MRI turbulence quantification by addressing the measurement errors caused by the derivatives of the turbulent velocity field - Sequence development and in-vitro validation.

To improve the current method for MRI turbulence quantification which is the intravoxel phase dispersion (IVPD) method. Turbulence is commonly characterized by the Reynolds stress tensor (RST) which describes the velocity covariance matrix. A major source for systematic errors in MRI is the sequence's sensitivity to the variance of the derivatives of velocity, such as the acceleration variance, which can lead to a substantial measurement bias. We developed a Cartesian phase contrast sequence with fast velocity encoding and two separately measured partial echoes with opposite readout directions. This design aims to reduce the high-order gradient moments that are responsible for the described measurement error. Velocity encoding directions follow the ICOSA6 scheme to capture the full RST. Turbulence data is reconstructed using the intra-voxel phase dispersion (IVPD) technique. We validated this sequence in vitro using a periodic hill flow benchmark with highly anisotropic turbulence. MRI data underwent extensive averaging, with multiple velocity encoding values employed to reduce noise and isolate systematic effects. The RST data obtained from the new sequence agree well with the ground truth. Compared to a state-of-the-art sequence, the maximum errors were reduced by factor five. Simple adjustments to current MRI protocols can greatly enhance turbulence measurement accuracy through the reduction of high-order gradient moments. The proposed measures include applying fast velocity encoding, high readout bandwidth, and a highly asymmetric readout. Ringing artifacts due to the asymmetric readout can be removed via a second, inverted readout.

Errors-in-variables model fitting for partially unpaired data utilizing mixture models

We introduce a general framework for regression in the errors-in-variables regime, allowing for full flexibility about the dimensionality of the data, observational error probability density types, the (nonlinear) model type and the avoidance of ad-hoc definitions of loss functions. In this framework, we introduce model fitting for partially unpaired data, i.e., for given data groups the pairing information of input and output is lost (semi-supervised). This is achieved by constructing mixture model densities, which directly model the loss of pairing information allowing inference. In a numerical simulation study linear and nonlinear model fits are illustrated as well as a real data study is presented based on life expectancy data from the world bank utilizing a multiple linear regression model. These results show that high quality model fitting is possible with partially unpaired data, which opens the possibility for new applications with unfortunate or deliberate loss of pairing information in data.

Extracellular Matrix-Inspired Dendrimer Nanogels Encapsulating Cyclophosphamide for Systemic Sclerosis Treatment.

Cyclophosphamide has a certain therapeutic effect on treating systemic sclerosis (SSc), while difficulties exist in controlling severe systematic side effects and enhancing targeting capacity. Here, inspired from the natural extracellular matrix composition, we propose a cyclophosphamide-encapsulated nanogel based on dendritic polymers polyamidoamine (PAMAM) for SSc treatment. We combine bovine serum albumin and generation 5 (G5) PAMAM dendrimers with polyphenol modification to obtain nanogels featured with antioxidant and anti-inflammatory effects. The nanogels can possess excellent biocompatibility and prevent fibroblasts from oxidative stress damage and TGF-β-mediated activation. Furthermore, in the bleomycin-induced SSc mouse model, dendrimer nanogels encapsulating cyclophosphamide also exhibit the ability to attenuate fibrosis by modulating immunity, suppressing inflammation, and reducing collagen synthesis. These findings underscore the value of this dendritic polymer nanogel in the treatment of chronic SSc, indicating its broader potential for clinical applications.

In cyber we trust? Understanding election legitimacy in the age of electronic election systems

ABSTRACT This study asks the question “to what extent do electronic election systems affect perceptions of election legitimacy in the U.S.?” The use of these systems is growing in the U.S. and abroad. Frequently, the justification for using electronic technology in election administration is that it reduces human-induced error – accidental error or intentional fraud – making elections cleaner and more credible. This study examines the effects on perceived election legitimacy of two electronic election technologies: electronic poll books and biometric voter identity verification. Poll books are record-keeping devices that allow election officials to determine which individuals are eligible to vote and where. Voters match their identity in the poll book to confirm they are eligible to vote. Electronic technology exists and is used for both poll books and voter identity verification. This pre-registered study tests these ideas in a pair of survey experiments conducted with samples of voting-age adults in the U.S.

Forecasts of effects of beam systematics and deprojection on the third-generation ground-based cosmic microwave background experiment

Forecasts of effects of beam systematics and deprojection on the third-generation ground-based cosmic microwave background experiment

The Effect of Cooperation with Conspecifics on a Pigeon’s Behavior under the Random Ratio Schedule

Abstract Social behavior involves interactions among individuals of the same species, and the presence or behavior of other individuals plays important roles. An individual’s performance in any particular task is improved or facilitated when others are present. The phenomenon of social facilitation has been studied for over a century, and it has implications for important behaviors like substance use, gambling, or choice behavior. The present study aimed to explore how the presence of conspecifics affects the behaviors of pigeons under a random ratio schedule. Four homing pigeons were used in various conditions to analyze response rates and bout-pause patterns. Experimental conditions were set up to examine the effects of conspecifics based on the following factors: the mere presence of conspecifics, simultaneous engagement in the same task, and sharing gains. Pigeon performance in each condition was compared based on the response rate and bout-and-pause patterns of key pecking behavior. The results suggest that sharing gain would work as an abolishing operation, although it does not produce a systematic effect on bout-pause patterns.

SWOT Data Assimilation with Correlated Error Reduction: Fitting Model and Error Together

Abstract The Surface Water Ocean Topography (SWOT) satellite mission provides high-resolution two-dimensional sea surface height (SSH) data with swath coverage. However, spatially correlated errors affect these SSH measurements, particularly in the cross-track direction. The scales of errors can be similar to the scales of ocean features. Conventionally, instrumental errors and ocean signals have been solved for independently in two stages. Here, we have developed a one-stage procedure that solves for the correlated error at the same time that data are assimilated into a dynamical ocean model. This uses the ocean dynamics to distinguish ocean signals from observation errors. We test its performance relative to the two-stage method using simplified dynamics and a data set consisting of westward propagating Rossby waves, along with correlated instrumental errors of varying magnitudes. In a series of tests, we found that the one-stage approach consistently outperforms the two-stage approach when estimating SSH signal and correlated errors. The one-stage approach can recover over 95% of the SSH signal, while skill for the two-stage approach drops significantly as error increases. Our findings suggest that solving for the correlated errors within the assimilation framework can provide an effective analysis approach, reducing the risks of confounding signal and instrument noise.

Do we feel colours? A systematic review of 128years of psychological research linking colours and emotions.

Colour is an integral part of natural and constructed environments. For many, it also has an aesthetic appeal, with some colours being more pleasant than others. Moreover, humans seem to systematically and reliably associate colours with emotions, such as yellow with joy, black with sadness, light colours with positive and dark colours with negative emotions. To systematise such colour-emotion correspondences, we identified 132 relevant peer-reviewed articles published in English between 1895 and 2022. These articles covered a total of 42,266 participants from 64 different countries. We found that all basic colour categories had systematic correspondences with affective dimensions (valence, arousal, power) as well as with discrete affective terms (e.g., love, happy, sad, bored). Most correspondences were many-to-many, with systematic effects driven by lightness, saturation, and hue ('colour temperature'). More specifically, (i) LIGHT and DARK colours were associated with positive and negative emotions, respectively; (ii) RED with empowering, high arousal positive and negative emotions; (iii) YELLOW and ORANGE with positive, high arousal emotions; (iv) BLUE, GREEN, GREEN-BLUE, and WHITE with positive, low arousal emotions; (v) PINK with positive emotions; (vi) PURPLE with empowering emotions; (vii) GREY with negative, low arousal emotions; and (viii) BLACK with negative, high arousal emotions. Shared communication needs might explain these consistencies across studies, making colour an excellent medium for communication of emotion. As most colour-emotion correspondences were tested on an abstract level (i.e., associations), it remains to be seen whether such correspondences translate to the impact of colour on experienced emotions and specific contexts.

Becoming as Open-Minded and Organized as My Classmates? Peer Effects on Self-Reported Personality Trait Development in the Classroom.

How does a student's personality development relate to the personality of their classmates? The school class builds a pertinent comparison group during adolescence that has been identified as a critical factor in students' development of abilities and self-perceptions. This study empirically tests the impact of classroom personality composition on changes in adolescents' Big Five personality traits. We hypothesized positive associations between class-level openness and conscientiousness and the individual development of these traits given their role in academic performance. To test these hypotheses and explore additional composition effects, we employed three approaches of multilevel structural equation modeling on two large longitudinal samples of German adolescents (N1 = 5470; N2 = 788). Our analyses yielded two principal findings: First, individual personality levels remained highly stable across different time periods. Second, contrary to our hypotheses, baseline class-level openness and conscientiousness were not positively linked to individual personality development. Instead, there were some indications that higher class-level openness was negatively linked to individual openness to experiences at the second measurement point. We discuss the absence of systematic composition effects at the classroom level and consider methodological challenges in investigating these effects.

The influence of body orientation on length judgements.

Perceiving the size of a visual object requires the combination of various sources of visual information. A recent paper by Kim et al. (Body Orientation Affects the Perceived Size of Objects. Perception 2022, 51: 25-36) concluded that body orientation played a substantial role. The present paper aims to answer the question of whether the reported effect of body orientation on visuo-haptic size matching was due to effects on the visual or the haptic judgements of size. To do so, we used a within-participant design combining an experiment using visuo-haptic size matching with two experiments that assessed the visual and haptic size-percept using free magnitude estimation. Our experiments produced a systematic visuo-haptic mismatch, but the sign of the mismatch was opposite to that of the original study. Moreover, our study did not reveal a systematic effect of body orientation on this mismatch. Thirdly, we found that the mismatch we determined from participants matching a visual and haptic percept was considerably smaller than the mismatch we derived from their visual and haptic size estimates. In summary, our results emphasise that conclusions about the perceived size of objects are very sensitive to details of the experimental approach.

The Impact of Preoperative Risk Factors on Delayed Discharge in Day Surgery: A Meta-Analysis.

This study aims to evaluate and identify the main preoperative risk factors affecting the timely discharge of day surgery patients, offering evidence to enhance preoperative assessments and minimize delayed discharge. With the widespread adoption of day surgery in global healthcare systems, ensuring timely discharge of patients post-surgery has become a critical challenge. Numerous studies have explored various preoperative risk factors influencing delayed discharge. This meta-analysis integrates existing evidence to clarify the primary preoperative risk factors. A systematic search was conducted across the PubMed, CINAHL, Scopus, Web of Science, Embase, Cochrane Library, and CNKI databases, including all clinical studies on preoperative risk factors for day surgery published until 15 October 2024. A systematic review and random effects model were employed to aggregate data and estimate the main preoperative risk factors for day surgery. A total of nine studies involving 41,458 patients were included. The analysis revealed statistically significant differences in the following preoperative risk factors: age (MD = 1.33, 95% CI: 0.73-1.93, p < 0.0001), body mass index (BMI) (MD = 0.69, 95% CI: 0.18-1.20, p = 0.008), the presence of chronic comorbidities (OR = 3.62, 95% CI: 2.93-4.46, p < 0.00001), the type of anesthesia (OR = 15.89, 95% CI: 7.07-35.69, p < 0.00001), a history of cardiac disease (OR = 2.46, 95% CI: 1.71-3.53, p < 0.00001), gender (OR = 3.18, 95% CI: 2.03-4.99, p < 0.00001), the expected duration of surgery (MD = 0.18, 95% CI: 0.15-0.20, p < 0.00001), complex procedures (OR = 1.78, 95% CI: 1.47-2.16, p < 0.00001), a lack of social family support (OR = 2.42, 95% CI: 1.60-3.67, p < 0.0001), and inadequate preoperative assessment (OR = 3.64, 95% CI: 2.06-6.41, p < 0.00001). There were no statistically significant differences between the delayed discharge group and the non-delayed discharge group in terms of the American Society of Anesthesiologists (ASA) classification (p = 1.00) and preoperative anxiety (p = 0.08). This study identifies the primary preoperative risk factors for delayed discharge in day surgery, including age, high BMI, the presence of chronic comorbidities, the type of anesthesia, a history of cardiac disease, gender, the duration of surgery, the complexity of the procedure, a lack of social family support, and inadequate preoperative assessment. These findings provide a reference for preoperative assessment, highlighting the need for clinical attention to these high-risk groups during preoperative screening and management to reduce the likelihood of delayed discharge and enhance surgical safety and success rates.

Radiology resident competency in orthopedic trauma detection in simulated on-call scenarios.

To evaluate radiology residents' ability to accurately identify three specific types of orthopedic trauma using radiographic imaging within a simulated on-call environment. We utilized the Wisdom in Diagnostic Imaging Emergent/Critical Care Radiology Simulation (WIDI SIM) to assess residents' preparedness for independent radiology call. The simulation included 65 cases, with three focusing on orthopedic trauma: sacral ala, femoral neck, and pediatric tibial/Toddler's fractures. Faculty graded residents' responses using a standardized 10-point rubric and categorized errors as observational (failing to identify key findings) or interpretive (incorrect conclusions despite correct identification of findings). 321 residents evaluated sacral ala fracture radiographs and received an average score of 1.29/10, with 8.71 points lost to observational errors. Only 6% produced effective reports (scores ≥ 7), while 80% made critical errors (scores < 2). For femoral neck fracture CT images (n = 316 residents), the average score was 2.48/10, with 6.71 points lost to observational errors. 25% produced effective reports, and 66% made critical errors. Pediatric tibial/Toddler's fracture radiographs (n = 197 residents) yielded an average score of 2.94/10, with 6.60 points lost to observational errors. 29% generated effective reports, while 71% made critical errors. Radiology residents demonstrated significant difficulty in identifying these orthopedic trauma cases, with errors primarily attributed to observational deficiencies. These findings suggest a need for targeted educational interventions in radiology residency programs to improve the identification of these fractures.

Red Stellar Populations and Dust Extinction toward W3

We explore red stellar populations toward the W3 giant molecular cloud through the use of optical-to-infrared (IR) photometry and Gaia DR 3 data, simultaneously characterizing stellar content and properties of dust in the molecular medium. We use a Rayleigh–Jeans color excess method modified to de-redden stellar observations of both red giants (RGs) and OB stars, and construct an IR Hertzsprung–Russell diagram validated against the Besançon Galactic model. Taking advantage of the near-universal IR interstellar extinction law and precise Gaia measurements, we develop a method for obtaining the spectral classification, foreground extinction, and distance moduli of stars, validated by spectroscopically confirmed OB stars. We constrain the observed parallax and proper motion of OB stars in W3, demonstrating the importance of considering systematic effects in the parallax bias, and assign parallax- and proper-motion-based cloud membership to our stellar samples. While it has been assumed that all spectroscopic OB stars are inside the W3 cloud, we find evidence of seven background B stars and three potential runaway OB stars. The methods developed here, which are based on known stellar populations, enable us to identify 82 new OB candidates that are confidently within the cloud. We quantify several dust-to-dust empirical correlations, in particular the IR color excess E(H − [4.5]) and the optical depth τ 1 of submillimeter dust emission at 1 THz using RGs behind W3, measuring a best fit of E(H−[4.5])=(1.07±0.04)×103τ1,HOTT+(0.00±0.02)mag .

Effects of Altered Haptic Feedback Gain Upon Balance Are Explained by Sensory Conflict Estimation.

Lightly touching a solid object reduces postural sway. Here, we determine the effect of artificially modifying haptic feedback for balance. Participants stood with their eyes closed, lightly gripping a manipulandum that moved synchronously with body sway to systematically enhance or attenuate feedback gain between +2 and -2, corresponding to motion in the same or opposite direction to the body, respectively. This intervention had a systematic effect on postural sway, which exhibited an asymmetric u-shape function with respect to haptic feedback gain. Sway was minimal around zero gain, corresponding to a static object. Sway increased slightly at gains below -0.25 but increased greatly at gains above +0.25. At +2, it was approximately double that of a no-touch condition. Mean interaction force between the hand and manipulandum remained < 0.9 N throughout, although it increased slightly at extreme gains. Cross-correlations between hand force and trunk position were highest during conditions of least sway, suggesting that higher quality haptic feedback is associated with greater sway reduction. We successfully replicated the sway behaviour using a feedback control model that attenuated haptic feedback signals when the discrepancy between haptic and proprioceptive signals reached a threshold. Our findings suggests the CNS can utilise augmented haptic feedback for balance, but only with relatively small changes to natural feedback gain. In healthy volunteers, it offers minimal benefit over a static object. Haptic feedback is therefore optimal when motion is physiologically realistic and subtle enough to be misinterpreted as self-motion.

Fractional-order Sliding Mode Control of Manipulator Combined with Disturbance and State Observer

A fractional-order sliding mode control (FSMC) method for a manipulator based on disturbance and state observers is proposed. First, a state estimator is designed that can estimate the velocity and acceleration, and only joint position feedback and the mathematical model of the manipulator are needed. The state estimator converges in finite time. Then, the disturbance observer is designed. By designing the nominal system model of the manipulator, a disturbance observation error is introduced into the closed-loop control so that the performance of the manipulator can track the nominal system. Finally, a sliding mode controller (SMC) based on the fractional differential operator theory is also designed. The value of the sliding mode variable in the derivation of the controller is composed of the fractional derivative of the trajectory tracking error of the manipulator, whereas the fractional differentiation operation uses integration in its realization, and the integration is a low-pass filter, thus, high-frequency noise is suppressed. In the experimental section, the method designed is compared with the conventional sliding mode, which further reveals the rapidity and control accuracy of FSMC.

Testing the robustness of the BAO determination in the presence of massive neutrinos

We study the robustness of the Baryon Acoustic Oscillation (BAO) feature in the large-scale structure in the presence of massive neutrinos. In the standard BAO analysis pipeline a reference cosmological model is assumed to boost the BAO peak through the so-called reconstruction technique and in the modelling of the BAO feature to extract the cosmological information. State-of-the art spectroscopic BAO measurements, such as the Dark Energy Spectroscopic Instrument claim an aggregate precision of 0.52% on the BAO scale, with a systematic error of 0.1% associated to the assumption of a reference cosmology when measuring and analyzing the BAO feature. While the systematic effect induced by this arbitrary choice of fiducial cosmology has been studied for a wide range of ΛCDM-like models, it has not yet been tested for reference cosmologies with massive neutrinos with the precision afforded by next generation surveys. In this context, we employ the Quijote high-resolution dark-matter simulations with haloes above a mass of M ∼ 2×1013 h -1 M ⊙, with different values for the total sum of neutrinos masses, ∑mν [eV] = 0, 0.1, 0,2, 0.4 to study and quantify the impact of the pipeline's built-in assumption of massless neutrinos on the measurement of the BAO signal, with a special focus on the BAO reconstruction technique. We determine that any additional systematic bias introduced by the assumption of massless neutrinos is no greater than 0.1% (0.2%) for the isotropic (anisotropic) measurement. We expect these conclusions also hold for galaxies provided that neutrino properties do not alter the galaxy-halo connection.

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. [58] developed models that could accurately infer the value of Ωm from catalogs that only contain the positions and radial velocities of galaxies that are robust to different astrophysics and subgrid models. However, observations are affected by many effects, including (1) masking, (2) uncertainties in peculiar velocities and radial distances, and (3) different galaxy population selections. Moreover, observations only allow us to measure redshift, which entangles the galaxy radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that while such effects degrade the precision and accuracy of the models, the fraction of galaxy catalogs for which the models retain high performance and robustness is over 90%, demonstrating the potential for applying them to real data.

Tele-correlation: calibrating shear-shear correlation with real data

Tele-correlation refers to the correlation of galaxy shapes with large angular separations (e.g., > 100 degrees). Since there are no astrophysical reasons causing such a correlation on cosmological scales, any detected tele-correlation could disclose systematic effects in shear-shear correlation measurement. If the shear estimators are measured on single exposures, we show that the field distortion (FD) signal associated with the galaxy position on the CCD can be retained and used in tele-correlation to help us directly calibrate the multiplicative and additive biases in shear-shear correlations.We use the DECaLS shear catalog produced by the Fourier_Quad pipeline to demonstrate this idea.To our surprise, we find that significant multiplicative biases can arise (up to more than 10%) due to redshift binning of the galaxies. Correction for this bias leads to about 1σ increase of the best-fit value of S 8 from 0.760+0.015 -0.017 to 0.777+0.016 -0.019 in our tomography study.

A spatial-statistical model to analyse historical rutting data

ABSTRACT Pavement rutting poses a significant challenge in flexible pavements, necessitating costly asphalt resurfacing. To address this issue comprehensively, we propose an advanced Bayesian hierarchical framework of latent Gaussian models with spatial components. Our model provides a thorough diagnostic analysis, pinpointing areas exhibiting unexpectedly high rutting rates. Incorporating spatial and random components, and important explanatory variables like annual average daily traffic (traffic intensity), asphalt type, rut depth and lane width, our proposed models account for and estimate the influence of these variables on rutting. This approach not only quantifies uncertainties and discerns locations at the highest risk of requiring maintenance, but also uncover spatial dependencies in rutting (millimetre/year). We apply our models to a data set spanning eleven years (2010–2020). Our findings emphasise the systematic unexplained spatial rutting effect, where some of the rutting variability is accounted for by spatial components, asphalt type, in conjunction with traffic intensity, is also found to be the primary driver of rutting. Furthermore, the spatial dependencies uncovered reveal road sections experiencing more than 1 millimeter of rutting beyond annual expectations. This leads to a halving of the expected pavement lifespan in these areas. Our study offers valuable insights, presenting maps indicating expected rutting, and identifying locations with accelerated rutting rates, resulting in a reduction in pavement life expectancy of at least 10 years.

Modeling the Center-to-limb Systematic in Normal-mode Coupling Measurements

Solar meridional circulation (MC), which manifests as poleward flow near the surface, is a relatively weak flow. While MC has been measured through various local helioseismic techniques, there is a lack of consensus about the nature of the depth profile and location of return flow, owing to its small amplitude and poor signal-to-noise ratio in observations. The measurements are strongly hampered by systematic effects whose amplitudes are comparable to the signal induced by the flow, and modeling them is therefore crucial. The removal of the center-to-limb (C2L) systematic, which is the largest known feature hampering the inference of meridional flow, has been heuristically performed in helioseismic analyses, but its effect on global modes is not fully understood or modeled. Here, we propose both a way to model the C2L systematic and a method for estimation of meridional flow using global helioseismic cross-spectral analysis. We demonstrate that the systematic cannot be ignored while modeling the mode-coupling cross-spectral measurement, and thus is critical for the inference of MC. We also show that inclusion of a model for the C2L systematic improves shallow MC estimates from cross-spectral analysis.