Systematic Bias Research Articles

The SRG/eROSITA All-Sky Survey: SRG/eROSITA cross-calibration with Chandra and XMM-Newton using galaxy cluster gas temperatures

Galaxy cluster gas temperatures ($T$) play a crucial role in many cosmological and astrophysical studies. However, it has been shown that $T$ measurements can significantly vary between different X-ray telescopes. These $T$ biases can propagate to several cluster applications in which $T$ can be used, such as measuring hydrostatic cluster masses and constraining the angular variation of cosmological parameters. Thus, it is important to accurately cross-calibrate X-ray instruments to account for systematic biases. In this work, we present the cross-calibration between Spectrum Roentgen Gamma/eROSITA (SRG/eROSITA) and Chandra /ACIS and between SRG/eROSITA and XMM-Newton /EPIC using for the first time a large sample of galaxy cluster $T$. To do so, we used the first eROSITA All-Sky Survey data and the preliminary extremely expanded HIgh FLUx Galaxy Cluster Sample, a large X-ray flux-limited cluster catalog. We spectroscopically measured X-ray $T$ for 186 independent cluster regions with both SRG/eROSITA and Chandra /ACIS in a self-consistent way for three energy bands: 0.7-7 keV (full), 0.5-4 keV (soft), and 1.5-7 keV (hard). We did the same with SRG/eROSITA and XMM-Newton /EPIC for 71 different cluster regions and all three bands. We find that SRG/eROSITA measures systematically lower $T$ than the other two instruments, with hotter clusters deviating more than cooler ones. For the full band, SRG/eROSITA returns 20$<!PCT!>$ and 14$<!PCT!>$ lower $T$ than Chandra /ACIS and XMM-Newton /EPIC, respectively, when the two other instruments each measure $k_ B T 3$ keV. The discrepancy respectively increases to 38<!PCT!> and 32<!PCT!> when Chandra /ACIS and XMM-Newton /EPIC each measure $k_ B T 10$ keV. On the other hand, the discrepancy becomes milder for low-$T$ galaxy groups. Moreover, a broken power law fit demonstrated that there is a break at the SRG/eROSITA- Chandra /ACIS scaling relation at $k_ B T 1.7-2.7$ keV, depending on the energy band. The soft band shows a marginally lower discrepancy compared to the full band. In the hard band, the cross-calibration of SRG/eROSITA and the other instruments show very strong differences. We tested several possible systematic biases (such as multiphase cluster gas, Galactic absorption, non-Gaussian scatter, and selection effects) to identify the reason behind the cross-calibration discrepancies, but none could significantly alleviate the tension. For now, it is most likely that the systematically lower SRG/eROSITA $T$ can be attributed to systematic effective area calibration uncertainties; however, the exact role of multiphase cluster gas in the observed $T$ discrepancies needs to be further investigated. Furthermore, we provide conversion factors between SRG/eROSITA Chandra /ACIS, and XMM-Newton /EPIC $T$ that will be beneficial for future cluster studies that combine SRG/eROSITA $T$ with data from other X-ray instruments. Finally, we also provide conversion functions between the official eRASS1 cluster catalog $T$ and the equivalent core and core-excised Chandra /ACIS and XMM-Newton /EPIC $T$.

Systematic bias from waveform modeling for binary black hole populations in next-generation gravitational wave detectors

Systematic bias from waveform modeling for binary black hole populations in next-generation gravitational wave detectors

Probabilistic model for the gravitational wave signal from merging black holes

Parametrized models that predict the gravitational-wave (GW) signal from merging black holes are used to extract source properties from GW observations. The majority of research in this area has focused on developing methods capable of producing highly accurate, point estimate, predictions for the GW signal. A key element missing from every model used in the analysis of GW data is an estimate for how confident the model is in its prediction. This omission increases the risk of biased parameter estimation of source properties. Current strategies include running analyses with multiple models to measure systematic bias however, this fails to accurately reflect the true uncertainty in the models. In this work we develop a probabilistic extension to the phenomenological modeling workflow for nonspinning black holes and demonstrate that the model not only produces accurate point estimates for the GW signal but can be used to provide well-calibrated local estimates for its uncertainty. Our analysis highlights that there is a lack of numerical relativity (NR) simulations available at multiple resolutions which can be used to estimate their numerical error and implore the NR community to continue to improve their estimates for the error in NR solutions published. Waveform models that are not only accurate in their point-estimate predictions but also in their error estimates are a potential way to mitigate bias in GW parameter estimation of compact binaries due to unconfident waveform model extrapolations. Published by the American Physical Society 2024

CURLING – I. The influence of point-like image approximation on the outcomes of cluster strong lens modeling

Abstract Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modeling in galaxy clusters is computationally expensive, leading to the point-source approximation of strongly lensed extended images, potentially introducing systematic biases. Herein, as the first paper of the ClUsteR strong Lens modelIng for the Next-Generation observations (CURLING) program, we use lensing ray-tracing simulations to quantify the biases and uncertainties arising from the point-like image approximation for JWST-like observations. Our results indicate that the approximation works well for reconstructing the total cluster mass distribution, but can bias the magnification measurements near critical curves and the constraints on the cosmological parameters, the total matter density of the Universe Ωm, and dark energy equation of state parameter w. To mitigate the biases, we propose incorporating the extended surface brightness distribution of lensed sources into the modeling. This approach reduces the bias in magnification from 46.2 per cent to 0.09 per cent for μ ∼ 1000. Furthermore, the median values of cosmological parameters align more closely with the fiducial model. In addition to the improved accuracy, we also demonstrate that the constraining power can be substantially enhanced. In conclusion, it is necessary to model cluster-scale strong lenses with pixelized multiple images, especially for estimating the intrinsic luminosity of highly magnified sources and accurate cosmography in the era of high-precision observations.

Performance of the non-invasive point-of-care device, EzeCheck, for haemoglobin assessment in adults and children in community and institutional care settings.

Anaemia is a major public health problem, especially in resource constrained settings. Dependency on assessment of blood hemoglobin (Hgb) concentration impedes anemia detection, risk stratification and intervention. Thus, valid, frugal and scalable technologies are needed. EzeCheck is a noninvasive portable device developed in India for predicting hemoglobin levels in human beings aged 4 years and above using a finger-tip biosensor. In this assessment, we aimed to: (i) evaluate EzeCheck's performance with an automated whole blood hemato-analyzer (Sysmex XN 1000) as the gold standard, and (ii) estimate EzeCheck's agreement with Sahli's method and HemoCue (Hb-301) in real-world primary and higher care facilities. Paired assessments were done at five sites across India i.e., Bhubaneshwar, Shimla, Solan and Mashobra and Ulhasnagar. Participants across all age groups (4 years and above) were assessed. We used a range of statistical tests to evaluate the performance of EzeCheck. It was found that EzeCheck performed well across age and gender categories with convincing validity, concordance, precision and accuracy, and acceptable bias. While comparing EzeCheck with Hemato-analyzer, no statistically significant systematic bias was found. However, EzeCheck showed significant systematic bias when compared to Sahli's method and HemoCue. We concluded that EzeCheck could detect anemia (as per WHO Hgb cut-offs) in 'real-world settings' and 'across age and gender categories', with high sensitivity, specificity and accuracy, and can serve as a replacement to traditional methods of hemoglobin assessment. Further, for countries with higher prevalence of anemia where universal screening may be mandated, the positive predictive value of EzeCheck will be higher. The likelihood ratios also indicated that the device had moderate-to-good utility. EzeCheck is suitable for embedment into program and out-patient health care settings in resource constrained contexts as a spot-check hemoglobinometer.

Standardized transect walks outperform pan traps in assessing wild bee community in a Mediterranean protected area (Asinara National Park, Italy)

AbstractThe decline of pollinator insects in various parts of the world has increased the interest in studies on bee sampling. Because pollinator management and conservation policies depend on data representing their communities, knowledge of the systematic bias of sampling methods in relation to surrounding habitat is fundamental. This study examined the performance of standardized transect walks and colored pan traps considering differences in bee species richness, diversity, and composition, and the potential bias due to a different availability of floral sources throughout seasons. The study was conducted in a minor outlying island (Asinara, Italy), a natural park characterized by the prevalence of natural or semi-natural habitats and an Oceanic Pluviseasonal Mediterranean bioclimate. We found that transect and pan trap methods reflected different bee communities based on taxonomic families, genera, and species. In general, the transect method captured more varied samples than pan traps, despite the significantly lower number of individuals captured on transects. Moreover, pan traps captured more bees as floral abundance decreased, whereas transects showed greater bee abundance, richness, and diversity with increasing floral resource availability. In addition, 18 species out of the 68 observed in total were caught exclusively with pan traps, especially in July–October, when transect catches decreased due to substantial bloom reduction. Therefore, alternating the two methods according to season (i.e., transect in late winter-spring and pan trap in summer-autumn) might be the most suitable trade-off to obtain a better representation of the bee community by limiting sampling efforts and the negative impact on bee fauna.

Why do seismic hazard models worldwide appear to overpredict historical intensity observations?

Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models-which forecast shaking as peak ground acceleration or velocity-and observations-parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes.

TOLNet validation of satellite ozone profiles in the troposphere: impact of retrieval wavelengths

Abstract. The Tropospheric Ozone Lidar Network (TOLNet) was used to validate retrievals of ozone (O3) profiles in the troposphere from the TROPOspheric Monitoring Instrument (TROPOMI) ultraviolet (UV), Cross-track Infrared Sounder (CrIS) infrared (IR), and a combined UV + IR wavelength retrieval from TROPOMI/CrIS. Observations from six separate ground-based lidar systems and various locations of ozonesondes distributed throughout North America and in the Netherlands were used to quantify systematic bias and random errors for each satellite retrieval. Furthermore, TOLNet data were used to intercompare idealized UV, IR, and UV + IR convolved lidar profiles of O3 in the troposphere during case studies representative of high-O3 events. This study shows that the improved sensitivity and vertical resolution in UV + IR retrievals in the middle- and upper-troposphere resulted in tropospheric degree of freedom (DOF) values ∼ 33 % higher compared to UV- and IR-only retrievals. The increased DOFs in the UV + IR retrievals allowed for improved reproduction of mid- and upper-tropospheric O3 enhancements and, to a lesser degree, near-surface pollution enhancements compared to single-wavelength satellite products. The validation of O3 profiles in the troposphere retrieved with the UV-only, IR-only, and UV + IR Tikhonov regularised Ozone Profile retrievAl with SCIATRAN (TOPAS) algorithm developed at the Institute for Environmental Physics, University of Bremen, demonstrated the utility of using TOLNet as a satellite evaluation data set. TOPAS UV-only, IR-only, and UV + IR wavelength retrievals had systematic biases, quantified with normalized mean bias, throughout the troposphere of 11.2 ppb (22.1 %), −1.7 ppb (−0.3 %), and 3.5 ppb (7.8 %), respectively, which meet the tropospheric systematic bias requirements defined by the science teams for the TROPOMI and CrIS sensors. The primary drivers of systematic bias were determined to be solar zenith angle, surface albedo, and cloud fraction. Random errors, representative of uncertainty in the retrievals and quantified by root mean squared errors (RMSEs), were large for all three retrievals, with UV-only, IR-only, and UV + IR wavelength retrievals having RMSEs throughout the troposphere of 17.4 ppb (19.8 % of mean tropospheric column values), 10.5 ppb (12.6 % of mean tropospheric column values), and 14.0 ppb (14.6 % of mean tropospheric column values), respectively. TOPAS UV-only profiles did not meet the uncertainty requirements defined for TROPOMI for the troposphere; however, CrIS IR-only retrievals did meet the uncertainty requirements defined by this mission. The larger random errors reflect the challenge of retrieving daily O3 profiles due to the limited sensitivity and vertical resolution of these retrievals in the troposphere. Tropospheric systematic biases and random error were lower in IR-only and combined UV + IR retrievals compared to UV-only products due to the increased sensitivity in the troposphere allowing the retrievals to deviate further from the a priori profiles. Observations from TOLNet demonstrated that the performance of the three satellite products varied by season and altitude in the troposphere. TOLNet was shown to result in similar validation statistics compared to ozonesonde data, which are a commonly used satellite evaluation data source, demonstrating that TOLNet is a sufficient source of satellite O3 profile validation data in the troposphere, which is critical as this data source is the primary product identified for the tropospheric O3 validation of the recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission.

From ultrasound to microscopy: Actualities in thyroid investigation in cattle.

Thyroid ultrasonography examination is widely used in human and small animal medicine. However, it has rarely been applied in cattle. The aim of this study was to determine whether the measurements of the thyroid gland by ultrasound examination correlate to those taken during post-mortem examination. A sample of 22 cows and 23 calves was selected for thyroid gland evaluation. An ultrasound scan was performed ante-mortem, followed by euthanasia (for medical reasons) or slaughtered in the food chain and the dissection of the thyroid gland was therefore performed. Post-mortem, the gland was weighed and its dimensions and volume measured. The volume and weight measurements were compared with the predicted ones on US using the formulas available in the literature. Finally, histological examination was performed on thyroid glands. The dimensions of the thyroid gland measured by ultrasonography were significantly different (p<0.05) from those observed post-mortem, except for lobe lengths in calves (p>0.1). However, in calves, there was no systematic bias between the ultrasound and post-mortem examination of the thyroid gland, which were concordant (with an average error of 18%). Cystic lesions were observed on ultrasound in 9/22 cows and could be found on histological examination in 7 of these. Other lesions, such as follicular hypoplasia and hyperplasia, were seen on histological examination but not on ultrasound. Although the ultrasound measurements did not significantly correlate with those taken post-mortem, this examination may allow to differentiate non-standard thyroids in the case of hyperplastic goiter, as demonstrated in other species. This study also describes and illustrates interesting lesions of the thyroid gland in cattle. These findings are innovative in the description of the use of thyroid ultrasound in cattle, although further studies are needed to allow deeper conclusions.

Evaluating westward and eastward propagating mesoscale eddies using a 1/10° global ocean simulation of CAS-LICOM3

This research evaluates the performance of CAS-LICOM3 (Chinese Academy of Science, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics (LASG/IAP) Climate system Ocean Model, version 3) in simulating global coherent mesoscale eddies by comparison to satellite altimeter observations. The simulations of westward and eastward propagating eddies (WPEs and EPEs) and cyclonic and anticyclonic eddies (CEs and AEs) are separately analyzed. The results demonstrate that the simulated spatial-temporal variabilities in global mesoscale eddies agree roughly with the satellite observations. CAS-LICOM3 also reproduces the distinctive features between WPEs and EPEs or between CEs and AEs. However, some systematic biases are found. Globally, CAS-LICOM3 simulates a less frequent and weaker mesoscale eddy field than is observed. WPEs contribute more to these global biases than do EPEs. EPEs are relatively better reproduced than WPEs, exhibiting smaller underestimations and even overestimations in the energetic western boundary current and Antarctic circumpolar current regions. The simulation results for CEs resemble those of AEs, but AEs are comparatively less biased than CEs. These findings provide a basis for improving low-resolution and eddy-resolving ocean general circulation models (OGCMs) and developing submesoscale-resolving OGCMs.

Assessing the impact of bias correction approaches on climate extremes and the climate change signal

AbstractWe assess the impact of three bias correction approaches on present day means and extremes, and climate change signal, for six climate variables (precipitation, minimum and maximum temperature, radiation, vapour pressure and mean sea level pressure) from dynamically downscaled climate simulations over Queensland, Australia. Results show that all bias‐correction methods are effective at removing systematic model biases, however the results are variable and season‐dependent. Importantly, our results are based on fully independent cross‐validation, an advantage over similar studies. Linear scaling preserves the climate change signals for temperature, while quantile mapping and the distribution‐based transfer function modify the climate change signal and patterns of change. The Perkins score for all the values above the 95th percentile and below the 5th percentile was used to evaluate how well the climate model matches the observational data. Bias correction improved Perkins score for extremes for some variables and seasons. We rank the bias‐correction methods based on the Kling–Gupta efficiency (KGE) score calculated during the validation period. We find that linear scaling and empirical quantile mapping are the best approaches for Queensland for mean climatology. On average, bias correction led to an improvement in the KGE score of 23% annually. However, in terms of extreme values, quantile mapping and statistical distribution‐based transfer function approaches perform best, and linear scaling tends to perform worst. Our results show that, except linear scaling, all approaches impact the climate change signal.

Assessing the impacts of ice penetration on monitoring water levels of high-latitude and -altitude lakes from CryoSat-2 altimetry

The CryoSat-2 satellite provides high-precision and long-term monitoring of global lake levels, offering advantages for water resource management, ecological protection, and disaster warning. However, the lake ice penetration by radar electromagnetic waves of CryoSat-2 altimetry tends to result in underestimation of water levels for lakes in high latitudes and altitudes. By contrast, the laser altimetry of ICESat-2 enables us to obtain the height measurements from lake ice surface and the ice penetration impacts on lake levels can be nearly ignored in the ICESat-2 elevation product. After converting the CryoSat-2 and ICESat-2 altimetry data to the same datum and height reference system, the water-level difference of (near-) synchronous observations between the two satellites could be mainly attributed to the influences by the lake ice penetration from CryoSat-2 data. In this study, totally 257 lakes in high-latitude (north of 50°N) and high-altitude (the Tibetan Plateau, TP) regions that are covered by both CryoSat-2 and ICESat-2 satellite tracks are examined to explore the characteristics of ice penetration impacts on water level measurements. The altimetry data during unfreezing seasons (June to October) are used to correct the systematic height biases of these two satellite measurements, thus their water level differences during freezing seasons (November to May of the following year) are deemed as the influences of ice penetration on lake level measurements by CryoSat-2 radar altimetry. The results show that the maximum underestimation depth of water level for each lake varies within the range of 0.01–3.47 m, with an average of 0.90 m. Particularly in North America with a dense distribution of lakes, the underestimation of lake levels by CryoSat-2 gradually ascends with increasing latitude. CryoSat-2 underestimates lake levels in Europe and the TP less than in North America. Among different months, the lake ice leads to the maximum underestimation on the water level by CryoSat-2 altimetry in March. The spatial and temporal characteristics of lake ice impacts on the water level measurements by CryoSat-2 altimetry would be an essential reference for quantifying and reducing the uncertainties of satellite radar altimetry for monitoring inland water dynamics.

Description and cross-sectional analyses of 25,880 adults and children in the UK National Registry of Rare Kidney Diseases cohort

IntroductionThe National Registry of Rare Kidney Diseases (RaDaR) collects data from people living with rare kidney diseases across the UK, and is the world’s largest rare kidney disease registry. We present the clinical demographics and renal function of 25,880 prevalent patients and sought evidence of bias in recruitment to RaDaR. MethodsRaDaR is linked with the UK Renal Registry (UKRR, with which all UK patients receiving Kidney Replacement Therapy (KRT) are registered). We assessed ethnicity and socioeconomic status in: 1) prevalent RaDaR patients receiving KRT compared with patients with eligible rare disease diagnoses receiving KRT in the UKRR; 2) patients recruited to RaDaR compared with all eligible unrecruited patients at two renal centres; 3) the age-stratified ethnicity distribution of RaDaR patients with Autosomal Dominant Polycystic Kidney Disease was compared to that of the English Census. ResultsWe found evidence of disparities in ethnicity and social deprivation in recruitment to RaDaR, however these were not consistent across comparisons. Compared with either adults recruited to RaDaR or the English population, children recruited to RaDaR were more likely to be of Asian ethnicity (17.3% vs 7.5% , p-value < 0.0001) and live in more socially deprived areas (30.3% vs 17.3% in the most deprived IMD quintile, p-value < 0.0001). ConclusionWe observed no evidence of systematic biases in recruitment of patients into RaDaR but the data provide empirical evidence of negative economic and social consequences (across all ethnicities) experienced by families with children affected by rare kidney diseases.

Politics of education in the USA: Deconstructing gender dynamics

Gender equity in education remains a political issue in the USA. There is evidence to suggest that disparities persist across multiple dimensions of the educational landscape. This comprehensive research paper examines the complex interplay of historical, cultural, and institutional factors that shape gender dynamics in American education. The paper traces the arduous journey towards gender parity in education, highlighting landmark legal and policy developments while critiquing their uneven implementation. It delves into contemporary data, revealing persistent enrollment and achievement gaps, underrepresentation in specific fields like STEM, and the dearth of women in leadership roles. Interrogating the root causes, the research explores the intricate ways socioeconomic status, cultural stereotypes, institutional biases, and lack of role models converge to disadvantage girls and women. Moreover, the work investigates how gender socialization and stereotypes permeate educational settings, influencing teaching practices, curricula, and interpersonal interactions. It exposes manifestations of gender-based discrimination, harassment, and violence, analysing their prevalence, institutional responses, and long-term consequences on victims' personal and academic development. The paper culminates by proposing a multifaceted approach to promoting gender equity, encompassing institutional reforms, community-based initiatives, and strategies to address systemic inequalities. It calls for inclusive curricula, educator training, mentorship programs, family engagement, and collaborative efforts to dismantle deeply entrenched biases and create empowering educational environments for all genders.

Utilising LANDHYPERNET data products over a deciduous broadleaf forest to validate Sentinel-2 and Landsat surface reflectance products

This paper demonstrates the use of a novel, autonomous hyperspectral surface reflectance data collected at Wytham Woods, United Kingdom (WWUK) as part of the LANDHYPERNET network for the validation of multispectral data from Sentinel-2, Landsat 8 and Landsat 9. The deployment of the HYPSTAR instrument at the site and the corresponding quality control of the data products is described. In addition, a methodology based upon metrological principles is outlined showing the propagation of uncertainties from the LANDHYPERNET and satellite data products to enable conformity testing of the satellite products using the satellite mission requirements. A total of 9 matchups are found for satellite validation at the site, where there is a cloud-free satellite scene and a corresponding LANDHYPERNET sequence, which has passed all quality checks, within two hours of the overpass. An analysis of the impact of the spatial variability of the site is presented and can account for up to 40% of the uncertainty associated with the in-situ surface reflectance data. There is no systematic bias in the Bottom-Of-Atmosphere reflectance data obtained from the LANDHYPERNET data in comparison to the satellite data. In the best case, differences of less than 2% are found for certain spectral bands. However, in the worst cases, relatively large differences are found which exceed 100%, this is affected by the relatively low reflectance values found in the visible bands. These differences could be caused by the spatial and temporal mismatch between the in-situ and satellite measurement, or due to shadowing caused by the flux tower. Further data quality control and assurance is needed to best choose data sets suitable for satellite validation. Incorporating a Bidirectional Reflectance Distribution Function model into the processing chain for the forest canopy is recommended. Overall, although there are areas to further characterise, the site provides a useful benchmark for which to develop techniques for validation of satellite surface reflectance products over a challenging environment.

The role of the basic state in the climate response to future Arctic sea ice loss

Abstract There is great uncertainty in the atmospheric circulation response to future Arctic sea ice loss, with some models predicting a shift towards the negative phase of the North Atlantic Oscillation (NAO), while others predicting a more neutral NAO response. We investigate the potential role of systematic model biases in the spread of these responses by modifying the unperturbed (or ``control'') climate (hereafter referred to as the ``basic state'') of the Canadian Earth System Model version 5 (CanESM5) in sea ice loss experiments based on the protocol of the Polar Amplification Model Intercomparison Project (PAMIP). We show that the presence or absence of the stratospheric pathway in response to sea ice loss depends on the basic state, and that only the CanESM5 version that shows a weakening of the stratospheric polar vortex features a strong negative NAO response. We propose a mechanism that explains this dependency, with a key role played by the vertical structure of the winds in the region between the subtropical jet and the stratospheric polar vortex (``the neck region winds''), which determines the extent to which anomalous planetary wave activity in response to sea ice loss propagates away from the polar vortex. Our results suggest that differences in the models’ basic states could significantly contribute to model spread in the simulated atmospheric circulation response to sea ice loss, which may inform efforts to narrow the uncertainties regarding the impact of diminishing sea ice on mid-latitude climate.

Monitoring bar velocity to quantify fatigue in resistance training.

We analyzed the effects of load magnitude and bar velocity variables on sensitivity to fatigue. Seventeen resistance-trained men (age=25.7±4.9 years; height=177.0±7.2 cm; body mass=77.7±12.3 kg; back-squat 1RM=145.0±33.9 kg; 1RM/body mass=1.86) participated in the study. Pre- and post-exercise changes in the mean propulsive velocity (MPV) and peak velocity (PV) in the back-squat at different intensities were compared with variations in the countermovement jump (CMJ). CMJ height decreased significantly from pre- to post-exercise (∆%=-7.5 to -10.4; p<0.01; ES=0.37 to 0.60). Bar velocity (MPV and PV) decreased across all loads (∆%=-4.0 to -12.5; p<0.01; ES=0.32 to 0.66). The decrease in performance was similar between the CMJ, MPV (40% and 80% 1RM; p=1.00), and PV (80% 1RM; p=1.00). The magnitude of reduction in CMJ performance was greater than MPV (60% 1RM; p=0.05) and PV (40% and 60% 1RM; p<0.01) at the post-exercise moment. Low systematic bias and acceptable levels of agreement were only found between CMJ and MPV at 40% and 80% 1RM (bias=0.35 to 1.59; ICC=0.51 to 0.71; CV=5.1% to 8.5%). These findings suggest that the back-squat at 40% or 80% 1RM using MPV provides optimal sensitivity to monitor fatigue through changes in bar velocity.

Test–Retest Reliability of a Motorized Resistance Device for Measuring Throwing Performance in Volleyball Athletes

Throwing performance is a critical aspect of sports, particularly in overhead activities, necessitating reliable assessment methods. This study explores the test–retest reliability of throwing performance metrics measured by the 1080 Sprint, a robotic device integrating linear position technology and an electric motor. Specifically focusing on professional volleyball athletes with scapular dyskinesis, the study draws data from a previously published investigation on the impact of mirror cross exercise. Thirty-nine athletes were recruited, aged 21.9 ± 3.6 years, height 1.79 ± 0.3 m weight 68.5 ± 19.8 kg, and body mass index 21.3 ± 3.2 kg/m2, meeting stringent inclusion criteria. One-sample t-tests indicated no statistically significant differences between test–retest trials. The study revealed excellent reliability of the 1080 Sprint, with intraclass correlation coefficient (ICC) values exceeding 0.99 for all metrics, including speed, force, and power. The standard error of measurement (SEM) calculation revealed that the Sprint 1080 motorized resistance device demonstrates high precision in measuring throwing performance. Bland and Altman plots indicated minimal systematic bias across all metrics, encompassing speed, force, and power. The provision of the minimum detectable change (MDC) for each variable of the Sprint 1080 motorized resistance device offers coaches a valuable tool to identify performance improvements in volleyball athletes. In conclusion, the present study shows that the 1080 Sprint is valid and reliable for measuring throwing performance in volleyball athletes for monitoring purposes.

Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages

Background and Objectives: No comparative study has evaluated the inter-method agreement and reliability between Heuron AD and other clinically available brain volumetric software packages. Hence, we aimed to investigate the inter-method agreement and reliability of three clinically available brain volumetric software packages: FreeSurfer (FS), NeuroQuant® (NQ), and Heuron AD (HAD). Materials and Methods: In this study, we retrospectively included 78 patients who underwent conventional three-dimensional (3D) T1-weighed imaging (T1WI) to evaluate their memory impairment, including 21 with normal objective cognitive function, 24 with mild cognitive impairment, and 33 with Alzheimer’s disease (AD). All 3D T1WI scans were analyzed using three different volumetric software packages. Repeated-measures analysis of variance, intraclass correlation coefficient, effect size measurements, and Bland–Altman analysis were used to evaluate the inter-method agreement and reliability. Results: The measured volumes demonstrated substantial to almost perfect agreement for most brain regions bilaterally, except for the bilateral globi pallidi. However, the volumes measured using the three software packages showed significant mean differences for most brain regions, with consistent systematic biases and wide limits of agreement in the Bland–Altman analyses. The pallidum showed the largest effect size in the comparisons between NQ and FS (5.20–6.93) and between NQ and HAD (2.01–6.17), while the cortical gray matter showed the largest effect size in the comparisons between FS and HAD (0.79–1.91). These differences and variations between the software packages were also observed in the subset analyses of 45 patients without AD and 33 patients with AD. Conclusions: Despite their favorable reliability, the software-based brain volume measurements showed significant differences and systematic biases in most regions. Thus, these volumetric measurements should be interpreted based on the type of volumetric software used, particularly for smaller structures. Moreover, users should consider the replaceability-related limitations when using these packages in real-world practice.

Understanding Ionospheric and Geomagnetic Effects on Residual Biases in Radio Occultation Data for Stratospheric Climate Monitoring

AbstractHigher‐order residual ionospheric errors in Global Navigation Satellite System (GNSS) radio occultation (RO) data can induce a systematic residual ionospheric bias (RIB) in RO bending angles, which can impact stratospheric climate monitoring. The main RIB causes are the ray path splitting of dual‐frequency GNSS signals, the electron density distribution along the ray path and at the RO receiver location, and the geomagnetic field. In this study, we investigate the ionospheric and geomagnetic effects on RO‐retrieved stratospheric bending angle and temperature profiles by inspecting the kappa and bi‐local RIB correction methods, the current state‐of‐the‐art methods, using multiple RO satellite mission data in different ionospheric and geomagnetic conditions. We find that, globally, the layer mean/median RIBs of the kappa and bi‐local correction methods exhibit similar behaviors for different RO missions: the estimated bending angle RIBs reach about −0.025/−0.01 and −0.024/−0.008 μrad in the upper (40–45 km) and lower (30–35 km) stratosphere, respectively, while the temperature RIBs reach about −1.0/−0.3 and −0.2/−0.1 K in these layers. However, in the equatorial day time region, the RIB statistics of the mission results diverge. Both the kappa and bi‐local RIBs increase in magnitude with increasing ionization and geomagnetic field strength but show no increase with an increasing degree of ionospheric asymmetry. Overall, the more refined bi‐local method has higher capacity than the comparatively simple kappa method to represent the variability of the ionospheric and geomagnetic conditions that affect RO events. This is important for regional‐scale studies, where the geomagnetic term can be of key relevance.