Square Root Of Variance Research Articles

Inflammation and autonomic balance in cirrhosis: Association between sympathetic nervous system and osteopontin, interleukin‐22, interleukin‐6 and interleukin‐1Ra concentrations according to portal hypertension and disease severity

AbstractBackgroundThe autonomic nervous system is linked to hyperdynamic circulation in cirrhosis and several studies have highlighted the crucial role that systemic inflammation elicits in altering sympathovagal equilibrium with the consequent reduction in heart rate variability (HRV).To investigate the correlation between time‐domain HRV parameters, serum cytokines concentrations and portal hypertension, we studied a cohort of patients with cirrhosis, accounting for etiology and treatments.MethodsIn this cross‐sectional, observational cohort study, 107 outpatients with non‐alcoholic cirrhosis were assessed consecutively by abdominal ultrasound and by upper gastrointestinal endoscopy to search for esophagogastric varices. 24‐h electrocardiogram Holter monitoring with time‐domain HRV measurement (square root of the mean of successive differences of Normal‐to‐Normal [NN] [RMSSD], standard deviation or the square root of variance [SDNN] and standard deviation of the means of the NN intervals calculated over a 5‐min period [SDANN]) was performed and serum concentrations of osteopontin (OPN), interleukin (IL)‐22, IL‐6, IL‐1Ra and IL‐17 were obtained in all patients.ResultsIL‐6, OPN, IL‐22 and IL‐1Ra concentrations in cirrhotic patients were associated with disease severity expressed by Child‐Pugh and MELD score, to some portal hypertension's indirect signs and some of its complications. A significant increase in systemic concentrations of OPN in patients with hepatocellular carcinoma was encountered. SDANN and SDNN values were indirectly related to serum levels of IL‐6, OPN, IL‐1Ra and IL‐22.ConclusionsThis study underlines the interaction between the alteration of the ANS and the activation of inflammatory pathways that characterize cirrhosis taking into account clinical characteristics and treatments.

Probability density functions of quantum mechanical observable uncertainties

We study the uncertainties of quantum mechanical observables, quantified by the standard deviation (square root of variance) in Haar-distributed random pure states. We derive analytically the probability density functions (PDFs) of the uncertainties of arbitrary qubit observables. Based on these PDFs, the uncertainty regions of the observables are characterized by the support of the PDFs. The state-independent uncertainty relations are then transformed into the optimization problems over uncertainty regions, which opens a new vista for studying state-independent uncertainty relations. Our results may be generalized to multiple observable cases in higher dimensional spaces.

Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation

NASA's Global Ecosystem Dynamics Investigation (GEDI) mission offers data for temperate and pan-tropical estimates of aboveground forest biomass (AGB). The spaceborne, full-waveform LiDAR from GEDI provides sample footprints of canopy structure, expected to cover about 4% of the land area following two years of operation. Several options are available for estimating AGB at different geographical scales. Using GEDI sample data alone, gridded biomass predictions are based on hybrid inference which correctly propagates errors due to the modeling and accounts for sampling variability, but this method requires at least two GEDI tracks in the area of interest. However, there are significant gaps in GEDI coverage and in some areas of interest GEDI data may need to be combined with other wall-to-wall remotely sensed (RS) data, such as those from multispectral or SAR sensors. In these cases, we may employ hierarchical model-based (HMB) inference that correctly considers the additional model errors that result from relating GEDI data to the wall-to-wall data. Where predictions are possible from both hybrid and HMB inference the question arises which framework to choose, and under what circumstances? In this paper, we make progress towards answering these questions by comparing the performance of the two prediction frameworks under conditions relevant for the GEDI mission. Conventional model-based (MB) inference with wall-to-wall TanDEM-X data was applied as a baseline prediction framework, which does not involve GEDI data at all.An important feature of the study was the comparison of AGB predictors in terms of both standard deviation (SD: the square root of variance) and root mean square error (RMSE: the square root of mean square error – MSE). Since, in model-based inference, the true AGB in an area of interest is a random variable, comparisons of the performance of prediction frameworks should preferably be made in terms of their RMSEs. However, in practice only the SD can be estimated based on empirical survey data, and thus it is important also to study whether or not the difference between the two uncertainty measures is small or large under conditions relevant for the GEDI mission.Our main findings were that: (i) hybrid and HMB prediction typically resulted in smaller RMSEs than conventional MB prediction although the difference between the three frameworks in terms of SD often was small; (ii) in most cases the difference between hybrid and HMB inference was small in terms of both RMSE and SD; (iii) the RMSEs for all frameworks was substantially larger than the SDs in small study areas whereas the two uncertainty measures were similar in large study areas, and; (iv) spatial autocorrelation of model residual errors had a large effect on the RMSEs of AGB predictors, especially in small study areas. We conclude that hybrid inference is suitable in most GEDI applications for AGB assessment, due to its simplicity compared to HMB inference. However, where GEDI data are sparse HMB inference should be preferred.

SEAFLOOR POSITIONING MODEL FOR SIMULTANEOUS ESTIMATION OF SOUND VELOCITY

Abstract. The spatial and temporal change of sound speed has a significant impact on the accuracy of GNSS-A underwater positioning. However, it is hard to collect enough data to cover all the spatial and temporal changes of sound velocity. We built an acoustic ranging model that included the sound velocity component, and then we looked at how the model could be used for three-dimensional seabed location and undersea crust monitoring. Meanwhile, B-spline curves are used to construct a sound velocity model that encompasses temporal variation as well as two-dimensional spatial gradients. The method was utilized to assess the simulated data and the in-situ data collected in July 2019, respectively. Simulation results show that the root mean square of the horizontal coordinates solved by the ranging model is less than 10 cm, and the model may meet the demands of subsea crust monitoring under certain situations. In the real data experiment, the square root of variance of the coordinate was better than 10 cm. The sound velocity model findings indicated that the variance of sound velocity in the experimental marine region was less than 1m/s, with clear daily patterns and short-period variations. The algorithm does not need the sound velocity profile information and can save the measurement time of the sound velocity profile.

Cost-Distortion Optimization and Resource Control in Pseudo-Analog Visual Communications

The rate-distortion in conventional digital systems is replaced by cost distortion in pseudo-analog systems where the cost consists of power and bandwidth. In this paper, we formulate the cost-distortion optimization problem in terms of a power-bandwidth pair versus distortion to bring an insight to pseudo-analog transmission. Using a divide-and-conquer strategy, the 3-D optimization problem of a power-bandwidth pair versus distortion is decomposed into two subproblems: power distortion and bandwidth distortion optimization. To solve the integer nonlinear optimization problem, we propose two prediction models that transform the partial summation of variances and the square roots of variances into continuous functions. The proposed models are used to derive the closed-form solutions for both optimization subproblems, and a tradeoff between power and bandwidth is discussed. Accordingly, the resource control algorithm is designed to allocate the fewest resources required to obtain specific video quality; power can be traded for bandwidth and vice versa. Our experimental results show that the proposed optimization models achieve stable perceptual video quality comparable to that of Groups of Pictures and use resources more efficiently than do SoftCast.

Distinguishing fibrosis/necrosis from teratoma or viable disease in the retroperitoneum in post-chemotherapy, nonseminomatous testicular germ cell tumor using quantitative CT texture analysis.

563 Background: In metastatic nonseminomatous testicular germ cell tumor (NSGCT), post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) is indicated for residual masses > 1 cm because of these 45% will be fibrosis/necrosis, 45% will be teratoma and 15% will be viable malignancy. There is no imaging test that reliably distinguishes lymph nodes (LNs) with tumor (teratoma or malignancy) from LNs with fibrosis/necrosis. We evaluated whether quantitative CT texture analysis (TA) could make this differentiation. Methods: Pre- and post-chemotherapy CTs (all same phase and slice thickness) were reviewed in 22 NSGCT patients with RP LNs > 1 cm post chemotherapy. After manual segmentation of RP LNs on a 3D workstation, 187 TA metrics were derived, using 2D/3D gray-level co-occurrence matrix (GLCM), 2D/3D gray-level difference matrix (GLDM), and spectral analysis. Metrics were derived 2 ways: from post-chemotherapy CTs alone, and also as a difference between pre- and post-chemotherapy CTs, resulting in 374 metrics. PC-RPLND pathology was correlated with CT data at 88 LN stations in these 22 patients. Results: 15 imaging metrics showed a significant difference (p ≤ 0.05) between LN stations with only fibrosis/necrosis and those with teratoma or viable tumor. Seven were derived from the difference between pre- and post-chemotherapy CTs: 4 using a 2D GLCM (coronal standard deviation, coronal square root of variance, coronal mean, and coronal sum of average), and 3 using a 2D GLDM (axial variance, axial square root of variance, and coronal variance). The other 8 were derived from post-chemotherapy CTs alone: 7 using a 2D GLCM (sagittal square root of variance, sagittal standard deviation, coronal square root of variance, coronal mean, coronal standard deviation, coronal sum of average, and coronal entropy) and 1 using a 2D GLDM (sagittal sum entropy). Conclusions: CT TA shows promise in differentiating necrosis from teratoma or viable tumor in RP LNs in post-chemotherapy NSGCT. A larger study is needed to further test this method, towards a long-term goal of potentially allowing some patients to avoid PC-RPLND.

Heart rate variability in infants with West syndrome

PurposeWest syndrome (WS) is a severe age-related acute epileptic encephalopathy of infancy characterized by infantile spasms, hypsarrhythmia and psychomotor delay. The aim of this study was to investigate if patients with WS had an altered autonomic output to the heart. MethodsIn 23 patients with WS the heart rate variability (HRV) was investigated by examining time- and frequency-domain parameters of HRV at the time of the diagnosis of hypsarrhythmia and compared to 22 age-matched controls. For the WS patients the same dataset was obtained and compared again at the end of the study period, when hypsarrhythmia was no longer present. ResultsCompared to controls, patients with WS during hypsarrhythmia had significantly lower SDNN (the standard deviation of the NN interval, i.e. the square root of variance) (19.2ms; p=0.007, Mann–Whitney's U-Test) and total power (242ms2; p=0.044, Mann–Whitney's U-Test) in the awake state, indicating an abnormal autonomic output to the heart. Comparing the initial to the final examination demonstrated a significant increase in the HRV parameters SDNN (31.3ms) and total power (757ms2; p=0.001 and p=0.013, Wilcoxon Signed Ranked Test). In addition, at the final examination the WS-patients no longer differed significantly from the controls. ConclusionOur data suggest that the initial reduction in HRV in patients at the time of onset of WS is transient and related to the presence of hypsarrhythmia.

Evaluation of mass measurements in accordance with the GUM

When the mass laboratory of DFM was created in 1989, harmonized principles for the evaluation of measurement uncertainty were being created based on a very simple principle endorsed by the CIPM: all uncertainties should be interpreted as the square root of variances (standard deviations) and should be combined and expressed as such. This paper describes how DFM has interpreted this principle for the calibration of mass standards and for the measurement of mass in general. The importance of reporting calibration results in a compact way that is easily propagated down the traceability chain is also discussed.

Estimating true standard deviations.

Estimating true standard deviations.

Relationship between Variability of Past Returns and Levels of Future Returns for Common Stocks, 1926–1960

Abstract The relationship of risk and expected returns of common stocks has been an integral part of the study of valuation theory even before Graham and Dodd authored their classic Security Analysis in 1934. In 1959, Harry Markowitz established a quantitative framework to the discussion. He adopted variance (or the square root of variance, the standard deviation) of annual returns as a usable measure of risk. The empirical study of the standard deviation of annual returns as a measure of total risk to ex post annual returns is the subject of this essay. This essay reports on one of the first empirical studies using the data bases of the center for Research in Security Prices at the Graduate School of Business of the University of Chicago.

Prediction of in situ degradation characteristics of neutral detergent fibre (aNDF) in temperate grasses and red clover using near-infrared reflectance spectroscopy (NIRS)

Near-infrared reflectance spectroscopy (NIRS) was used to estimate in situ neutral detergent fibre (aNDF) degradation characteristics. Dried or ensiled samples of perennial grasses and red clover ( n = 382) were used to develop calibration equations. In situ residues of aNDF after 144 h of ruminal incubation were assumed to represent the total indigestible aNDF fraction (aINDF). The fractional degradation rate of aNDF (kdNDF) was calculated assuming first order degradation kinetics with an initial lag time. The aNDF content ranged from 266 to 703 g/kg DM. The aINDF values ranged from 14 to 360 g/kg DM, and the kdNDF varied from 0.020 to 0.137/h. Spectral data was transformed to their second order derivates and a standard normal variate and detrending procedure was used. NIRS prediction were made by modified partial least square technique and prediction accuracy was tested after separating the samples into a validation (close to 70 samples) and calibration dataset. Establishment of new NIRS calibrations and successive predictions of new validation samples were repeated four times. Accuracy of NIRS predictions was evaluated by the standard error of prediction, corrected for bias (SEPC), and by the standard coefficient of determination in prediction ( R P 2 ). Dispersion in sample reference values (square root of variance) divided by SEPC (RPD) was also calculated and a value >2.5 was used as indicator of acceptable prediction. For aINDF, SEPC was 17.7 g/kg DM, R p 2 was 0.92 and RPD 3.4. For kdNDF, SEPC was 0.012/h, R p 2 was 0.51, and the RPD value was 1.7. For the initial lag time, SEPC was 1.27 h, R p 2 was 0.02 and RPD was 1.0. From this study it is concluded that the developed calibration equations had an acceptable prediction of aINDF, and can be used for predicting aINDF for use in practical feed evaluation. The NIRS prediction of kdNDF was less accurate because of weaknesses with the reference method. The initial lag time could not be predicted by NIRS.

11 A Simple Time Domain Estimate for Determining the Baroreceptor Reflex Mediated Heart Rate Response in Newborns

Top of pageAbstract Introduction: The baroreceptor reflex mediated heart rate response is generally estimated by complex cross-spectral analysis (transfer function gain) between R-R interval and systolic blood pressure (SBP) fluctuations in the low frequency (LF, 0.04–0.15 Hz) band: The baroreceptor reflex sensitivity (BRS, ms/mmHg) (Andriessen, P. et al. Pediatr Res 2003;53:89–97). Aim: To evaluate the BRS with a simple time domain (t-BRS) estimate rather than a complex frequency domain (f-BRS) estimate. Methods: Forty-two infants (postconceptional age, range: 28–42 wk) were studied in the first days after birth whose intensive care management required an arterial catheter. Data analysis was performed on 192-s-long stationary segments during the quiet sleep state. f-BRS was estimated using transfer function analysis (LF transfer gain) based on cross-spectral analysis of R-R interval and SBP density curves, using 5 half-overlapping fast Fourier transform 64-s segments, at coherence values > 0.5 indicating statistical reliability. t-BRS was estimated by the ratio of SD of (R-R)i intervals (square root of variance or root-mean-square for the mean) divided by the SD of SBP beat-to-beat values in the 192-s-long segments. Statistics: linear regression analysis and difference of mean as function of mean of both methods with its 95% limits of agreement (Bland-Altman). Results: Time domain assessment of BRS (t-BRS) correlated significantly with LF cross-spectral analysis (f-BRS): r2 = 0.85; t-BRS = f-BRS + 1; p<0.01. The mean difference of both methods (f-BRS - t-BRS) was -1 mmHg/ms. The 95% limits of agreement were between -5 and +3 mmHg/ms. Conclusions: The baroreceptor reflex mediated heart rate response can reliable estimated by this simple time domain estimate and may be useful to determine in critical ill patients with signs or symptoms of cardiovascular instability. Low BRS implicates poor short-term regulation of BP fluctuations. Intensive care management should aim at reducing interventions causing blood pressure changes in these patients.

Best Linear Unbiased Prediction of Sire Breeding Values from Part Lactations of Daughters

The objective was to compare the accuracy of sire evaluations based on 150-, 200-, 250-, and 305-day milk yields of daughters. Accuracy was defined as a ratio of the square root of variance of prediction errors to variance of breeding values.Utilizing additive genetic relationships among sires increased accuracy of sire evaluation, particularly of sires with few daughters. An evaluation with 18 daughters per sire by 150-day milk yields gave accuracy equivalent to evaluation by 305-day milk yields for about 14 daughters. About 11.8% more genetic progress was expected from 305-day records than from 150-day records on 25 daughters. Additive genetic relationships among sires were more advantageous for proofs of short records than for proofs of 305-day milk yields.