Standard Deviation Of The Difference Research Articles

Arctic Sea Ice Albedo Estimation from Fengyun-3C/Visible and Infra-Red Radiometer

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases.

Assessing reproductive performance and predictive models for litter size in Landrace sows under tropical conditions.

Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns. A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2nd and 3rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4th parity and then declined. In contrast, NPL and PPL decreased until the 2nd parity and then steadily increased until the 8th parity. The 2nd and 3rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC. The 3rd degree polynomial model offers the most suitable description of NBA, NPL, and PPL patterns. It holds promise for applications in genetic evaluations to enhance litter size and reduce piglet loss at birth in sows. These findings highlight the importance of accounting for sow parity effects in swine breeding programs, particularly in tropical conditions, to optimize piglet production and sow performance.

Racial effects on masimo pulse oximetry: impact of low perfusion index

Purpose: Evaluate the SpO2-SaO2 difference between Black and White volunteer subjects having a low perfusion index (Pi) compared to those having a normal Pi. Methods: The Pi data were abstracted from electronic files collected on 7183 paired SpO2-SaO2 samples (3201 Black and 3982 White) from a recently reported desaturation study of 75 subjects (39 Black and 36 White) where SaO2 values were sequentially decreased from 100 to 70%. The Pi values from that dataset were divided into two groups (Pi ≤ 1 or Pi > 1) for analysis. A Pi value ≤ 1 was considered “low perfusion” and a Pi value > 1 was considered “normal perfusion”. Statistical calculations included values of bias (mean difference of SpO2-SaO2), precision (standard deviation of the difference), and accuracy (root-mean-square error [ARMS]). During conditions of low perfusion (Pi ≤ 1, range [0.1 to 1]), overall bias and precision were + 0.48% ± 1.59%, while bias and precision were + 0.19 ± 1.53%, and + 0.91 ± 1.57%, for Black and White subjects, respectively. Results: During normal perfusion (Pi > 1, range [1 to 12]), overall bias and precision were + 0.18% ± 1.34%, while bias and precision were -0.26 ± 1.37%, and − 0.12 ± 1.31%, for Black and White subjects, respectively. ARMS was 1.37% in all subjects with normal perfusion and 1.64% in all subjects with low perfusion. Conclusion: Masimo SET® pulse oximeters with RD SET® sensors are accurate for individuals of both Black and White races when Pi is normal, as well as during conditions when Pi is low. The ARMS for all conditions studied is well within FDA standards. This study was conducted in healthy volunteers during well-controlled laboratory desaturations, and results could vary under certain challenging clinical conditions.

Fostering Nationalism among University Students in Indonesia: A Communal Perspective

This study’s primary aim is to investigate globalization’s impact on nationalism in Indonesia, specifically focusing on the youth population. The research seeks to understand how globalization influences nationalist sentiments, particularly in the context of the Indonesian educational system. The chosen methodology centers around implementing a Civic Education learning model, aiming to activate and enhance nationalism values among students. The research employs a structured approach, utilizing a test on nationalism knowledge administered before and after implementing the Civic Education learning model. This method allows for a comprehensive assessment of the potential impact of the learning model on students’ understanding of nationalism. The analysis involves measuring the mean score difference between pre-test and post-tests, employing statistical calculations such as mean difference, the standard deviation of the difference, the standard error of the mean difference, and calculated t-values. Additionally, behavioral-scale tests are conducted to evaluate the mean score difference in students’ nationalism behavior. Quantitative calculations and analyses are employed to substantiate the research hypothesis. The statistical findings indicate a significant influence of the Civic Education learning model on students’ knowledge of nationalism and behavior. The mean score differences before and after the model’s implementation and the calculated t-values provide robust evidence of the positive impact on students’ nationalist sentiments. The study extends its contribution to pedagogy by demonstrating the efficacy of alternative teaching methods, specifically in Civic Education. The findings suggest that implementing the Civic Education learning model enhances practical application and holds promise in strengthening Indonesia’s global influence. The research aligns with established concepts of nationalism, emphasizing the actualization of patriotism through the collective development of clear national goals and objectives. The study aims to contribute meaningful insights to the ongoing discourse on nationalism in Indonesia, particularly among the youth.

Abstract 15130: Sweat Lactate Sensor for Detecting Anaerobic Threshold in Paitents With Heart Failure: Prospective Clinical Trial (LacS-001)

Background: Exercise is essential for good health and prevention of exacerbations in patients with heart failure (HF). To determine ventilatory threshold (VT); a key to detect appropriate exercise intensity, our team developed a small, easy-to-use device for non-invasive, simple, and real-time visualization of sweat lactate dynamics during exercise. Clinical Question: Could our sweat lactate sensor (GI-1) provide a safe and accurate means of detecting VT in patients with HF in a clinical setting? Aim: This prospective clinical trial (clinical trial; jRCT2032220057) was designed to investigate the safety of a sweat lactate sensor (GI-1) and the correlation between the lactate threshold in sweat (sLT), as assessed using our sweat lactate sensor, and the VT. Methods: We recruited 50 patients with HF and New York Heart Association functional classification I-II, with a median age of 63.5 years (interquartile range: 58.0-72.0 years). Incremental exercise tests were conducted and changes in sweat lactate levels were monitored simultaneously. The sLT was defined as the first steep increase in lactate levels from baseline as seen on graphical plots and was evaluated by three independent investigators. The primary outcome measures were a correlation coefficient of 0.6 or greater between sLT and VT, the similarities as assessed by the Bland-Altman analysis, and the standard deviation of the difference between the two within 15 W. Results: Among the 50 patients, a correlation coefficient of 0.651 (95% confidence interval, 0.391-0.815) was achieved in 32 cases. The difference between the sLT and VT was -4.9±15.0 W, and no comparative error was noted in the Bland-Altman plot. No device-related adverse events were reported among the registered patients. Conclusions: Our sweat lactate sensor, GL-1, provides a safe and accurate means of detecting VT in patients with HF in a clinical setting, thereby offering valuable additional information for treatment.

Abstract 15380: Diagnostic Performance of Ultrasonic Flow Ratio versus Quantitative Flow Ratio for Assessment of Coronary Artery Stenosis

Introduction: Ultrasonic flow ratio (UFR) is a novel intravascular ultrasound (IVUS)-derived method for fast computation of fractional flow reserve (FFR) without pressure wires and adenosine. Aims: The aim of this study was to evaluate the diagnostic performance of UFR and compare it with angiography-based quantitative flow ratio (QFR), using FFR as the reference standard. Methods: Patients who underwent coronary angiography, IVUS and FFR were analyzed. UFR and QFR was computed offline in a central core-lab by independent analysts blinded to FFR. Results: A total of 111 paired comparisons between UFR, QFR and FFR from 56 patients were analyzed. UFR showed a numerically better correlation (r=0.83 vs. 0.79; p=0.27) and significant better agreement (standard deviation of the difference=0.07 vs. 0.08; p=0.02) with FFR than QFR. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio for UFR to predict FFR was 92% (95% CI: 85%-96%), 85% (95% CI: 71%-94%), 97% (95% CI: 89%-99%), 95% (95% CI: 83%-99%), 90% (95% CI: 82%-95%), 27.6 (95% CI: 7.0-108.4), and 0.16 (95% CI: 0.08-0.31), respectively. The area under curve for UFR to predict an FFR ≤ 0.80 was 0.94, is equivalent to QFR (difference=0.04; p=0.23), and higher than minimal lumen area (difference=0.09, p=0.006). Diagnostic accuracy was not significantly different in bifurcation lesions, nor in non-bifurcation lesions. Conclusions: The UFR showed good diagnostic concordance with FFR, equivalent to QFR. The good diagnostic performance of UFR provides a potentiality for the integration of physiological assessment and intravascular imaging in real-world clinical practice.

A precise method to calibrate a vessel's dynamic draft based on a single GNSS antenna

Calculating a vessel's dynamic draft is critical for surveying seabed topographies and ensuring safe navigation on the sea. To obtain an accurate dynamic draft, a precise method based on a single GNSS antenna is proposed. First, the geodetic height of the transducer recorded when the vessel is sailing and drifting is processed by wavelet analysis to eliminate the influence of waves. Then, the processed geodetic height data with only the impacts from tides serve as the true tide, and the other data with impacts from tides and dynamic draft serve as the mixed tide. The mixed tide is fitted by the Fourier function and calibrated by the true tide to obtain the water level during sailing. Finally, by subtracting the true tide at the sailing from the mixed tide, the real-time dynamic draft during the surveying time is accurately acquired. Results show that the mean, maximum, and minimum of the obtained dynamic draft are 0.183 m, 0.238 m, and 0.136 m, respectively. The standard deviation of the difference between the water level from the tide station and the derived water level is approximately 1.0 cm, which indirectly proves the high accuracy of the proposed method in calculating the dynamic draft.

Development and validation of aquestionnaire to assess physiotherapists' postural-structural-biomechanical-oriented beliefs about pain

Therapists frequently use the postural-structural-biomechanical (PSB) model in clinical practice to explain the symptom of pain using biomechanical deficits. Adequate knowledge about pain encompasses not only the neurophysiology of pain but also knowledge that existing PSB-oriented explanations of the development and enhancement of pain are outdated. There is no assessment to evaluate physiotherapists' PSB-oriented beliefs about pain. The aim of the present study was to develop aquestionnaire to assess physiotherapists' PSB-oriented beliefs about pain and to evaluate its reliability (internal consistency), validity, and agreement. The Essential Knowledge of Pain Questionnaire (EKPQ) was constructed on the basis of aliterature search and discussions between experts. In apilot study, 32pupils of aphysiotherapy school were then asked to complete the German version of the revised Neurophysiology of Pain Questionnaire (rNPQ-D) and the EKPQ using the SoSci Survey in order to assess their knowledge and beliefs about pain. The internal consistency of the EKPQ was acceptable with aCronbach's α = 0.784. There was astrong positive significant correlation between the questionnaires (r = 0.518; p = 0.002). The Bland-Altman analysis revealed amean difference of 28.9% (± standard deviation of the difference 15.3%) with an upper limit of 95% agreement of 58.8% and alower limit of 95% agreement of -1.0% between the questionnaires. Participants achieved amean score of 60.7% in the rNPQ‑D and amean score of 31.8% in the EKPQ. The newly developed EKPQ questionnaire seems to be areliable and valid assessment to determine physiotherapists' PSB-oriented beliefs about pain. The results also confirm that ahigh level of knowledge about the neurophysiology of pain does not exclude aPSB orientation. Whether the EKPQ can be used alongside the rNPQ as an additional assessment to evaluate beliefs about pain should be investigated in the future with suitable study designs, e.g. Delphi study.

Moisture content estimation of green softwood logs of three species based on measurements of flexural vibration

The moisture contents of sugi (Cryptomeria japonica), todomatsu (Abies sachalinensis) and hinoki (Chamaecyparis obtusa) logs were estimated using a method of moisture content estimation proposed in our previous study. In the course of estimation, it was revealed that the regression line of the correlation between specific dynamic Young’s modulus (E/ρ) and tangent loss (tan δ) of green wood was different from that of moisture-conditioned wood and showed species dependency, both of which are not previously reported. Regression lines at the fiber saturation point (FSP) were constructed for each species by measuring E/ρ and tan δ from the flexural vibration of green small specimens and correcting the E/ρ values at their own moisture contents into E/ρ values at the FSP. The correlation of green wood in this study was different from that reported in previous studies of moisture-conditioned wood near the FSP. The correlations of sugi and hinoki were similar, whereas those of sugi and todomatsu were different despite no previous report of species dependency in air-dried wood. The moisture contents 86 logs (not those used to prepare small specimens) were estimated using regression lines of each species. The standard deviation of the difference between the estimated moisture content and the measured moisture content was 15.7%. A systematic error of 25.9% in moisture content was attributed to the different methods of specimen support used for small specimens and logs.

Effects of sodium-glucose co-transporter 2 inhibitors on liver fibrosis in non-alcoholic fatty liver disease patients with type 2 diabetes mellitus: An updated meta-analysis of randomized controlled trials

Background and aimSodium-glucose co-transporter 2 inhibitors (SGLT2i) has been verified to improve Non-alcoholic fatty liver disease (NAFLD) in previous clinical practice. We mainly aim to investigate the effects of SGLT2i on liver fibrosis in NAFLD patients with type 2 diabetes mellitus (T2DM). MethodsWe conducted a comprehensive literature search utilizing the databases PubMed, Embase, Web of Science, and Cochrane Library, and extracted continuous data in the form of mean and standard deviation of the difference before and after treatment. RevMan 5.3 software was used to chart the pooled forest plot and perform heterogeneity, sensitivity and subgroup analysis. This study is conducted under the protocol registered with the Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY protocol 4946, INPLASY202360058). ResultsA total of 16 articles involving 699 patients were included. Indicators of liver fibrosis, containing Liver Stiffness Measurement (LSM), Controlled Attenuation Parameter (CAP), Serum ferritin, Serum type 4 collagen 7s, and FIB-4 index, were found to be considerably reduced by SGLT2i medication and subgroup analysis manifested pronounced dose-dependence. Additionally, SGLT2i therapy decreased BMI, lipid buildup and insulin resistance. ConclusionsSGLT2 inhibitors significantly ameliorated liver fibrosis and liver fat content, improved body conditions and insulin resistance, demonstrating that SGLT2i might reduce the risk of the progression of liver fibrosis and have a positive effect on NAFLD patients with T2DM.

Accuracy of VO2 estimation according to the widely used Krakau formula for the prediction of cardiac output.

Invasive cardiac output (CO) is measured with the thermodilution (TD) or the indirect Fick method (iFM) in right heart catheterization (RHC). The iFM estimates CO using approximation formulas for oxygen consumption ([Formula: see text]O2), but there are significant discrepancies (> 20%) between both methods. Although regularly applied, the formula proposed by Krakau has not been validated. We compared the CO discrepancies between the Krakau formula with the reference (TD) and three established formulas and investigated whether alterations assessed in cardiac magnetic resonance imaging (CMR) determined the extent of the deviations. This retrospective study included 188patients aged 63 ± 14years (30% women) receiving both CMR and RHC. The CO was measured with TD or with the iFM using the formulas by Krakau, LaFarge, Dehmer, and Bergstra for [Formula: see text]O2 estimation (iFM-K/-L/-D/-B). Percentage errors were calculated as twice the standard deviation of the difference between two CO methods divided by their means; acut-off of < 30% was regarded as acceptable. The iFM and TD-derived CO ratio was built, and deviations > 20% were counted. Logistic regression analyses were performed to identify determinants of adeviation of > 20%. The TD-derived CO (5.5 ± 1.7 L/min) was significantly different from all iFM (K: 4.8 ± 1.6, L: 4.3 ± 1.6; D: 4.8 ± 1.5 L/min; B: 5.4 ± 1.8 L/min all p < 0.05). The iFM-K-CO differed from all methods (p < 0.001) except iFM‑D (p = 0.19). Percentage errors between TD-CO and iFM-K/-L/-D/-B were all beyond the acceptance limit (44/45/44/43%), while percentage errors between iFM‑K and other iFM were all < 16%. None of the parameters measured in CMR was predictive of adiscrepancy of > 20% between both methods. The Krakau formula was comparable to other iFM in estimating CO levels, but none showed satisfactory agreement with the TD method. Improved derivation cohorts for [Formula: see text]O2 estimation are needed that better reflect today's patients undergoing RHC.

Monitoring ice flow velocity of Petermann glacier combined with Sentinel-1 and −2 imagery

Synthetic Aperture Radar (SAR) images are commonly used to monitor glacier flow velocity at Greenland Ice Sheet (GrIS). However, offset-tracking with SAR imagery in summer usually show poor quality because the rapid ice surface freezing-melting cycles contaminating the surface backscattering characteristic, while optical images are less sensitive to this phenomenon. In this study, we combine Sentinel-1 and -2 images to create the glacier velocity time series for the Petermann glacier, located in the northern GrIS. Firstly, the offset-tracking technique is employed to acquire the initial deformation fields with SAR and optical sensors separately, each SAR and/or optical acquisition is tracked with its closest next three acquisitions. Next, after removing the bad matchings, the least squares method based on connected components is employed to calculate the time series of glacier velocity for Sentinel-1 and −2, separately. Finally, these two kinds of derived time series are integrated with a weighted least squares method, where weights are evaluated according to the estimated RMSEs in the last step. Error propagation analysis suggests RMSEs of the single pair of Sentinel-1 and −2 images offset-tracking are ∼ 0.22 m and ∼ 2.5 m for Petermann glaciers. Standard deviation of the difference between Sentinel-1 and Sentinel-2 measured velocity are ∼ 0.25 m/day. Compared with 6-day velocity fields product, NSIDC (National Snow and Ice Data Center) −0766, which is only derived with Sentinel-1observations, our results show good agreement and less defects in summer. The differences are ∼ 0.20 m/day in non-melting seasons and ∼ 0.34 m/day in summer. Longitudinal velocity differences growing in 2019 and 2020 at ∼ 20 Km up to the terminus are consistency with the crevasse expansion, indicating another calving event is approaching. This research finds that the fusion of Sentinel-1 and −2 offset-tracking results improves the completeness of the ice movement time series for polar glaciers.

Soil moisture estimates at 1 km resolution making a synergistic use of Sentinel data

Abstract. Very high-resolution (∼10–100 m) surface soil moisture (SM) observations are important for applications in agriculture, among other purposes. This is the original goal of the S2MP (Sentinel-1/Sentinel-2-Derived Soil Moisture Product) algorithm, which was designed to retrieve surface SM at the agricultural plot scale by simultaneously using Sentinel-1 (S1) backscatter coefficients and Sentinel-2 (S2) NDVI (Normalized Difference Vegetation Index) as inputs to a neural network trained with Water Cloud Model simulations. However, for many applications, including hydrology and climate impact assessment at regional level, large maps with a high resolution (HR) of around 1 km are already a significant improvement with respect to most of the publicly available SM datasets, which have resolutions of about 25 km. In this study, the S2MP algorithm was adapted to work at 1 km resolution and extended from croplands to herbaceous vegetation types. A target resolution of 1 km also allows the evaluation of the interest in using NDVI derived from Sentinel-3 (S3) instead of S2. Two sets of SM maps at 1 km resolution were produced with S2MP over six regions of ∼104 km2 in Spain, Tunisia, North America, Australia, and the southwest and southeast regions of France for the whole year of 2019. The first set was derived from the combination of S1 and S2 data (S1 + S2 maps), while the second one was derived from the combination of S1 and S3 (S1 + S3 maps). S1 + S2 and S1 + S3 SM maps were compared to each other, to those of the 1 km resolution Copernicus Global Land Service (CGLS) SM and Soil Water Index (SWI) datasets, and to those of the Soil Moisture Active Passive (SMAP) + S1 product. The S2MP S1 + S2 and S1 + S3 SM maps are in very good agreement in terms of correlation (R≥0.9), bias (≤0.04 m3 m−3), and standard deviation of the difference (SDD≤0.03 m3 m−3) over the six domains investigated in this study. In a second step, the S1 + S3 S2MP maps were compared to the other HR maps. S1 + S3 SM maps are well correlated to the CGLS SM maps (R∼0.7–0.8), but the correlations with respect to the other HR maps (CGLS SWI and SMAP + S1) drop significantly over many areas of the six domains investigated in this study. The highest correlations between the HR maps were found over croplands and when the 1 km pixels have a very homogeneous land cover. The bias among the different maps was found to be significant over some areas of the six domains, reaching values of ±0.1 m3 m−3. The S1 + S3 maps show a lower SDD with respect to CGLS maps (≤0.06 m3 m−3) than with respect to the SMAP + S1 maps (≤0.1 m3 m−3) for all the six domains. Finally, all the HR datasets (S1 + S2, S1 + S3, CGLS, and SMAP + S1) were also compared to in situ measurements from five networks across five countries, along with coarse-resolution (CR) SM products from SMAP, SMOS, and the European Space Agency Climate Change Initiative (CCI). While all the CR and HR products show different bias and SDD, the HR products show lower correlations than the CR ones with respect to in situ measurements. The discrepancies in between the different HR datasets, except for the more simple land cover conditions (homogeneous pixels with croplands) and the lower performances with respect to in situ measurement than coarse-resolution datasets, show the remaining challenges for large-scale HR SM mapping.

Aeromagnetic attitude compensation for uninhabited aircraft systems without high-altitude calibration patterns using hybrid recurrent neural networks

Since the 1950s, Tolles-Lawson-based aeromagnetic compensation methods have been used to separate an aircraft's magnetic signal from signal associated with ground geologic and cultural features. This is done by performing a high-altitude figure-of-merit (FOM) flight and fitting the band-pass-filtered magnetic data to determine compensation parameters. This paper describes a supervised hybrid recurrent neural network (HRNN) algorithm trained on low-altitude survey data to perform aeromagnetic compensation. The proposed HRNN attitude compensation method can be employed for aeromagnetic surveys where traditional FOM and compensation are not possible. It has particular relevance for surveying via uninhabited aircraft systems (UAS). Firstly, the HRNN was tested on data from a fixed-wing airplane survey, and the results were compared to hardware-based compensation results. The standard deviation of the difference between the two methods for magnetic attitude correction (MAC) was 0.1 nT for the training region and 0.4 nT for the application region, respectively. Secondly, a UAS FOM flight at the highest permitted altitude in Canada, 120 m above ground level, showed similar improvement ratios for software-based least squares (LS) and the proposed HRNN algorithm of 3.5 and 2.6, respectively. The percent change and deviation in differences in MACs from LS to HRNN was 0.0% and 0.9 nT across small-box loops and –2.7% and 0.4 nT across large-box loops. Finally, LS and the proposed HRNN algorithm were applied to a 50 m altitude UAS data set for which no FOM flight was possible. LS did not successfully model aircraft noise, whereas the HRNN demonstrated effective removal of the magnetic signal due to aircraft attitude variations. The modeled HRNN MAC had a standard deviation of 2.4 nT.

Retirement timing uncertainty: Empirical evidence and quantitative evaluation

People often retire at a different age than expected. We construct a measure of retirement timing uncertainty and find that the standard deviation of the difference between retirement expectations and actual retirement dates ranges from 3 to 6 years. To understand the potential implications of this uncertainty, we develop a simple model of exogenous but risky retirement. In this environment, individuals would give up 1.0%-4.5% of total lifetime consumption to fully insure this risk and 0.8%-3.2% of lifetime consumption simply to know their actual retirement date upon entering the labor force. This is crucial for retirement planning purposes because not saving to hedge this risk would leave individuals with even larger welfare costs.

Survey method for field measurement of rubber ball impact sound in reinforced concrete apartment houses in Korea – Based on the Korean measurement method

The rubber ball impact sound has been standardized by ISO 10140 series and ISO 16283-2 for laboratory and field measurements, respectively. The ISO 10052 standard specifies a survey method for the impact sound measurement using a tapping machine and a rubber ball. This study proposed measurement position for the survey method which is highly correlated with result based on the Korean Standards (KS) and the building regulation of South Korea for engineering method. The rubber ball impact sounds were measured in 79 reinforced concrete apartment houses, which have a centre point and four perimeter points for both exciting and receiving sounds. The proposed survey method was validated for only a specific type of apartment building layout and construction in the South Korean environment. The excitation and receiving points in the perimeter having the most similar characteristics to the results obtained using the Korean engineering methods were first selected. By combining the selected perimeter point and centre point for both the excitation and receiving sounds, the characteristics of each combination were compared with the results obtained using the Korean engineering method. When one excitation point or receiving point in the perimeter was added to the centre point for the proposed survey method, the difference between the measurement result using the engineering and proposed survey method decreased. The standard deviation of the difference between the SNQs of the proposed survey method and the Korean engineering method for measuring the rubber ball impact sound was smaller than 2 dB.

Local Tide and Geoid Corrections Significantly Improve Coastal Retracked Jason Sea Surface Heights in the Philippines

Retracking algorithms increase the accuracy of coastal sea surface height (SSH) measurements. However, it is still important to validate these retracking estimates with tide gauge (SSHtg) observations. We downloaded the freely available Jason altimeter SSH processed using the XTRACK-ALES algorithm, then detided the SSH using different tide models. The first model is the default tidal correction based on Finite Element Solution 2014 (SSHfes), and the second model is the T_Tide harmonic analysis of the nearest tide gauge (SSHaltimeter). SSHfes showed a very poor correlation (&lt; 0.31) and very high root mean square error (RMSE, &gt; 29 cm). In contrast, SSHaltimeter generally showed a very high correlation (&gt; 0.91) and low RMSE (&lt; 17.4 cm). A further quality check based on the average and standard deviation of the difference between the SSH readings (SSHfes – SSHtg and SSHaltimeter – SSHtg) also showed the superior performance of SSHaltimeter, which scored &lt; 9.3 and &lt; 16.5 cm, respectively; compared to SSHfes, which scored &lt; 9.3 cm and &gt; 27 cm for the same parameters. The poor performance from the SSHfes likely comes from the complex bathymetry and coastal geomorphology of the country, which is not accounted for in the FES. The Philippines generally has a narrow shelf, and the FES tide corrections may be related to deep-water tides rather than the shallow-water tides observed from tide gauges. Despite the high correlation and agreement between the SSHaltimeter and SSHtg, the rate of sea level rise from the SSHaltimeter in some sites is more than twice the rate from SSHtg, which indicates the possible influence of the vertical land movement.

PHSOR11 Presentation Time: 1:20 PM: Verify the Transit Time Correction Accuracy of the Bravos Afterloader System Using a Novel Scintillation-Based Brachytherapy Quality Assurance Device

<h3>Purpose</h3> Compared to the older generations, the new Bravos high dose rate (HDR) afterloader offers the function to automatically correct dwell time to compensate the transit dose effect. To our best knowledge, there is no QA attempt to verify the accuracy of this correction. To address this issue, a new transit time measurement module has been developed and included in the OriQA HDR QA device, an autonomous phantom for HDR brachytherapy quality assurance. In this work, we employ the OriQA system to verify the transit time correction accuracy of the Bravos afterloader system. <h3>Method</h3> The OriQA device utilizes radioluminescence imaging technique to accurately measure HDR source strength, dwell time, and dwell position. It consists of a 20 cm needle applicator insert, a radioluminescence phosphor sheet placed directly atop the applicator, a digital camera, and software for signal processing and displaying results. Radiation-induced luminescence photons are emitted from the phosphor sheet and captured by the camera. The signal intensity and location are processed to yield relative source strength and dwell information. For the verification test, one of the Bravos channels was connected to the OriQA applicator using a one-meter transfer tube. After specific plan delivery, the raw data of OriQA measurement including source position and time was exported to Matlab for further analysis. The real dwell time at each dwell position and the transit time between dwells during cable extension and retraction were extracted. The transit time correction method provided by the vendor was applied to the measurement, yielding the delivered dwell time. The percentage difference between the delivered and planned dwell time was calculated and used as an indicator of the transit time correction accuracy. Several verification plans were created including seven with fixed dwell steps, one with variable dwell steps, and one with variable dwell time. Plans with fixed dwell steps were delivered three times. The rest were delivered once. Plan details are listed in table 1. For each plan, the mean and standard deviation of the difference between planned and delivered dwell time were calculated from all dwell positions and deliveries. <h3>Results</h3> The deviations between the planned and delivered dwell time are listed in table 1. For plans with less than 4 cm dwell step, the accuracy of transit time correction is, on average, less than 1.2% of the dwell time. For plans with 4 cm and 9 cm dwell step, the accuracy is 1.5% and 2.85%, on average, respectively. Dwell time variation does not affect the correction accuracy, as shown in plan 9. Standard deviations of plan 3, 4, and 9 are greater than 1% due to the relatively large difference at the proximal dwell. <h3>Conclusion</h3> This is the first study that successfully verifies the transit time correction accuracy of the Bravos system. Less than 2% accuracy is observed for clinically relevant dwell steps (0.3 cm to 4 cm). Variations in dwell step, dwell position, and dwell time do not worsen the accuracy.

How precisely European equity ETFs mirror their flagship benchmarks? Evidence from funds replicating performance of Euro Stoxx 50 Index

The main goal of the article is to examine the tracking efficiency of a homogenous sample of 14 ETFs listed on European exchanges, replicating the performance of Euro Stoxx 50 Index—a benchmark index for blue chips from the euro area. This study provides some insights into the tracking quality of European ETFs over the long time horizon (2012–2021 period) including data from entire business cycle: both economic prosperity and COVID-19 crisis. The study has been made applying different tracking error calculation techniques and return intervals—daily, weekly and monthly. Passive investing may be a highly desirable, cheap and accurate method for long or short term investments in the largest 50 cap companies in the euro zone. Hence, this unique research may help to succeed in ETF selection process. The study reveals that ETFs are very effectively managed by keeping the TEs below 0.3% (for ETFs with accumulating share classes) and below 1% (for ETFs with distributing share classes). This shows that the ETFs with accumulating share classes perform much better—the average TE for three different methods is 0.11% for accumulating share classes ETFs and 0.33% for distributing share classes ETFs. It proofs, that it is not important whether to use the standard deviation of the difference between the return of an ETF and that of its benchmark index, or the standard error of regression in TE assessment, both methods give very similar results. However, TE calculation method signifies, if the average of the absolute difference between the return of an ETF and that of the index is used. Additionally, it is found that time intervals used in TE calculations matter—the shift from monthly to daily intervals results in reduction of TE levels. Using shorter intervals brings lower TE values of European ETFs.

Myocardial flow reserve estimation with contemporary CZT-SPECT and 99mTc-tracers lacks precision for routine clinical application

BackgroundPET myocardial flow reserve (MFR) has established diagnostic and prognostic value. Technological advances have now enabled SPECT MFR quantification. We investigated whether SPECT MFR precision is sufficient for clinical categorization of patients. MethodsValidation studies vs invasive flow measurements and PET MFR were reviewed to determine global SPECT MFR thresholds. Studies vs PET and a SPECT MFR repeatability study were used to establish imprecision in SPECT MFR measurements as the standard deviation of the difference between SPECT and PET MFR, or test-retest SPECT MFR. Simulations were used to evaluate the impact of SPECT MFR imprecision on confidence of clinically relevant categorization. ResultsBased on validation studies, the typical PET MFR categories were used for SPECT MFR classification (< 1.5, 1.5-2.0, > 2.0). Imprecision vs PET MFR ranged from 0.556 to 0.829, and test-retest imprecision was 0.781-0.878. Simulations showed correct classification of up to only 34% of patients when 1.5 ≤ true MFR ≤ 2.0. Categorization with high confidence (> 80%) was only achieved for extreme MFR values (< 1.0 or > 2.5), with correct classification in only 15% of patients in a typical lab with MFR of 1.8 ± 0.5. ConclusionsCurrent SPECT-derived estimates of MFR lack precision and require further optimization for clinical risk stratification.