Standard Analysis Software Research Articles

Inter- and intrarater reliability of short-term measurement of heart rate variability on rest in chronic obstructive pulmonary disease (COPD).

Individuals with COPD have an imbalance of cardiac autonomic control. In this context, HRV is considered an important tool for assessing cardiac sympathetic and parasympathetic balance, however it is a dependent evaluator measure and subject to methodological biases that may compromise the interpretation of results. This study examines the inter- and intrarater reliability of HRV parameters derived from short-term recordings in individuals with COPD. Fifty-one individuals of both genders with COPD clinical diagnosis confirmed by the pulmonary function test and aged ≥50 years were included. The RR interval (RRi) were recorded during a 10 min period on supine position using a portable heart rate monitor (Polar® H10 model). The data were transferred into Kubios® HRV Standard analysis software and analyzed within the stable sessions containing 256 sequential RRi. The intraclass correlation coefficient (ICC) ranged from 0.942 to 1.000 according to the intrarater analysis by Researcher 01 and 0.915 to 0.998 to the intrarater by Researcher 02. The interrater ICC ranged from 0.921 to 0.998. The coefficient of variation was up to 8.28 for Researcher 01 intrarater analysis, 9.06 for Researcher 02 intrarater analysis and 13.07 for interrater analysis. The measurement of HRV using a portable heart rate device in individuals with COPD present acceptable values of intra- and interrater reliability, supporting the use of HRV in the clinical and scientific scenario. Furthermore, it is important that the data analysis be performed by the same experienced evaluator.

Intra- and Interrater Reliability of Short-Term Measurement of Heart Rate Variability on Rest in Individuals Post-COVID-19.

Individuals affected by COVID-19 have an alteration in autonomic balance, associated with impaired cardiac parasympathetic modulation and, consequently, a decrease in heart rate variability (HRV). This study examines the inter- and intrarater reliability of HRV) parameters derived from short-term recordings in individuals post-COVID. Sixty-nine participants of both genders post-COVID were included. The RR interval, the time elapsed between two successive R-waves of the QRS signal on the electrocardiogram (RRi), were recorded during a 10 min period in a supine position using a portable heart rate monitor (Polar® V800 model). The data were transferred into Kubios® HRV standard analysis software and analyzed within the stable sessions containing 256 sequential RRi. The intraclass correlation coefficient (ICC) ranged from 0.920 to 1.000 according to the intrarater analysis by Researcher 01 and 0.959 to 0.999 according to the intrarater by Researcher 02. The interrater ICC ranged from 0.912 to 0.998. The coefficient of variation was up to 9.23 for Researcher 01 intrarater analysis, 6.96 for Researcher 02 intrarater analysis and 8.83 for interrater analysis. The measurement of HRV in post-COVID-19 individuals is reliable and presents a small amount of error inherent to the method, supporting its use in the clinical environment and in scientific research.

A Novel Echocardiographic-Based Classification for the Prediction of Peri-Device Leakage following Left Atrial Appendage Occluder Implantation.

(1) Background: The assessment of residual peri-device leakages (PDL) after left atrial appendage occlusion (LAAO) remains crucial for post-procedural management. Our study aimed to verify a novel echocardiographic classification for the prediction of PDL. (2) Methods: Echocardiographic data of 72 patients who underwent percutaneous LAAO were evaluated. All echo images were analyzed by two independent investigators using standard analysis software (Image-Arena IA-4.6.4.44 by TomTec®, Munich, Germany). A total number of 127 studies was evaluated. Forty-four patients had baseline studies, at 45 days and at 6 months post-implantation. We propose a morphological classification of LAA devices based on the amount of echodensity inside the devices into three types: type A showing complete homogenous thrombosis, type B incompletely thrombosed device with inhomogeneous echo-free space <50% of device, and type C with partially thrombosed device in which the echo free space was >50% of device in various planes, which we called the “ice-cream cone” sign. Each type was matched to the degree of PDL and clinical outcome parameters. (3) Results: Patients with type C had the highest percentage of PDL at 45 days follow-up (type A: 24%, type B: 31%, type C 100% PDL, p < 0.001) and at 6 months follow-up (type A: 7%, type B: 33%, type C 100% PDL, p < 0.001). Notably, device size in patients with PDL was larger than that in patients without PDL at 6 months follow-up (25.6 ± 3.5 mm vs. 28.7 ± 3.4 mm, p = 0.004). Device size in patients with type C appearance was the largest of the three types (type A: 25.9 ± 3.6 mm, type B: 25.8 ± 3.4 mm, type C 29.8 ± 3.0 mm, type A vs. C; p = 0.019; type B vs. C, p = 0.007). (4) Conclusions: In conclusion, PDL are common post-LAAO, and their frequency is underestimated and under-recognized. PDL are much more common in patients with larger LAA ostial sizes and likely lower longitudinal compression. Type C appearance of the LAAO devices (“ice-cream cone sign”) has a high positive predictive value for PDL. Further studies are needed for better delineation of the clinical importance of this proposed classification.

Fast GPU Algorithm for Analyzing Effective Connectivity in Functional Brain Imaging

Abstract Functional imaging, such as functional Magnetic Resonance Imaging (fMRI), allows the in-vivo study of the human neuronal circuitry. By applying specific environmental stimuli to human subjects, functional imaging detects signals that could indicate direct or indirect neuronal connectivity when they exhibit certain levels of association between brain regions. However, the directed connections cannot be identified using simple statistical approaches, such as pair-wise correlations. Structural Equation Modeling (SEM) is more appropriate for analyzing the causal relationship, called the effective connectivity. SEM is aimed to fit a path model subject to the anatomical constraints using the data collected from imaging study. Such data-driven path analysis involves the minimization of a maximum likelihood (ML) discrepancy function with respect to some constrained path coefficients. The minimization process is iterative. In each of iterations, a constrained coefficient will be switched to unconstrained and added to the pool of the unconstrained for the minimization. The iterations continue until the model attains an acceptable level of parsimonious fit index. The computing time is a big issue because it increases geometrically with the number of unconstrained path coefficients, in other words, the number of iterations. Using Quad-Core Central Processing Unit (CPU), it takes a month for the iterations from 0 to 30 path coefficients. High speed computing hardware and software can be applied to the optimization process so as to cope with the above-mentioned issue. Graphical Processing Unit (GPU) is a kind of high speed hardware solution that performs ultra-fast algorithmic computation on huge data matrices. This study demonstrates the utilization of GPU with the parallel Genetic Algorithm (GA) replacing the Powell minimization in the standard analysis software package. It is shown in an example of 30 path coefficients that the time taken for the path analysis can be reduced from 30 days to 3.6 hours. The breakthrough of this study in high speed computing greatly relaxes the limitation on the number of paths to be investigated in functional imaging and maintains the performance of optimization.

Engineering nonlinearity characteristic compensation for commercial steam turbine control valve using linked MARS code and Matlab Simulink

Abstract Steam turbine control valves play a pivotal role in regulating the output power of the turbine in a commercial power plant. They thus have to be operated linearly to be run by an automatic control system. Unfortunately, the control valve has inherently nonlinearity characteristics. The flow increases more significantly near the closed end than near the open end of the stem travel given the valve position signal. The steam flow should nonetheless be proportional to the final desired quantity, output power, of the turbine to obtain a linear operation. This paper presents the valve engineering linked analysis (VELA) for nonlinearity characteristic compensation of the steam turbine control valve by using a linked two existing commercial software. The Multi-dimensional Analysis of Reactor Safety (MARS) code and Matlab Simulink have been selected for VELA to develop a steady state and transient analyzer of Ulchin Units 3&4 powered by the Optimized Power Reactor 1000 MWe (OPR1000). MARS is capable of modeling a wide range of systems from single pipes to full nuclear power plants. As one of standard nuclear power plant thermal hydraulic analysis software tools, MARS simulates the primary and secondary sides of the nuclear power plant. To simulate the electric power flow part, Matlab Simulink is chosen as the standard analysis software. Matlab Simulink having an interactive environment to model analyzes and simulates a wide variety of engineering dynamic systems including multimachine power systems. Based on the MARS code result, Matlab Simulink analyzes the power flow of the generator connected to an infinite bus for representing the grid connection. Three different scenarios are analyzed in VELA by considering the control valves opening sequence mechanism and the change rate of output power reference.

C-A1-01: Using Data Transformations, Derived Values, and Cryptographic Functions to Protect PHI in the VDW

Background and Aims HIPAA policies define values derived from PHI as also being PHI. Consequently, applying algorithmic functions to PHI has been viewed as having little benefit to research data. However, short of full de-identification, the use of transformed PHI may reduce compliance risk and increase security of routine data handling. Our aim is to: present a general framework for evaluating methods of de-identifying/protecting PHI, and evaluate how well selected mathematical functions, including common cryptographic functions, can enhance protection of PHI in the HMORN Virtual Data Warehouse (VDW). Methods The methods used include a review of technical literature/material, from both within and outside traditional research disciplines, followed by analysis and application of findings to the issues addressed here, including: reviewing both the regulatory and practical context for protecting PHI in research data; developing a set of criteria to evaluate the benefits and costs of methods for PHI protection/de-identification; reviewing the basic uses of general cryptography; comparing/contrasting the needs of general cryptography with those of PHI protection in research data; evaluating selected methods of protecting PHI against the proposed criteria. Results The proposed framework for evaluating PHI protection methods includes five criteria: effect on usefulness of data; effect on ease of use or analytical efficiency; net impact on data security; system implementation costs; negative effect on data quality. There are several methods for protecting PHI that can be easily implemented in the VDW, including: the creation of linking variables that eliminate the need to routinely query PHI variables, such as service dates; the MD5 cryptographic hash function, which can be used to obscure any PHI data and is relatively easy to implement in SAS, the standard analysis software platform used in the HMORN. Conclusions Stewards of research data, like the VDW, should adopt the use mathematical functions, including cryptographic hash functions, to transform PHI into derived values. Such methods do not replace the need for full de-identification, but can enhance security and reduce compliance risk during routine data handling.

A method for improving plasma temperature estimates from incoherent scatter analysis during artificial ionospheric modification experiments

[1] Spectral features in incoherent scatter data, such as those caused by the purely growing mode (PGM), can often be strongly enhanced during the first few seconds of artificial ionospheric heating experiments, such as those carried out using the high-power European Incoherent Scatter HF at Tromso. These features, often referred to as effects, are indicators of turbulent non-Maxwellian plasma, and the analysis of these spectra using standard incoherent scatter data analysis software leads to a poor estimation of the plasma parameters (particularly electron and ion temperature) during RF heating experiments. In this study, a procedure is developed to derive a more reliable estimate of plasma temperature during periods when the incoherent scatter spectrum is affected by contamination from the PGM. This is achieved by removing the PGM from the measured spectrum and then analyzing the modified spectrum using standard software. The results are compared to those obtained from the analysis of the original, contaminated spectra. It is found that the differences between the results obtained from the corrected and uncorrected spectra are strongly proportional to the magnitude of the PGM feature. We also show that the bulk temperatures during the remainder of the heater on period after the overshoot can generally be estimated reliably by the standard analysis software, though with some important exceptions. These results are important since the plasma temperatures play a crucial role in governing thermal conduction processes, and their correct estimation is thus very important to understanding the underlying physical processes which occur during ionospheric heating.

A method for improving plasma temperature estimates from incoherent scatter analysis during artificial ionospheric modification experiments

Spectral features in incoherent scatter data, such as those caused by the purely growing mode (PGM), can often be strongly enhanced during the first few seconds of artificial ionospheric heating experiments, such as those carried out using the high‐power European Incoherent Scatter HF heater at Tromsø. These features, often referred to as “overshoot” effects, are indicators of turbulent non‐Maxwellian plasma, and the analysis of these spectra using standard incoherent scatter data analysis software leads to a poor estimation of the plasma parameters (particularly electron and ion temperature) during RF heating experiments. In this study, a procedure is developed to derive a more reliable estimate of plasma temperature during periods when the incoherent scatter spectrum is affected by contamination from the PGM. This is achieved by removing the PGM from the measured spectrum and then analyzing the modified spectrum using standard software. The results are compared to those obtained from the analysis of the original, contaminated spectra. It is found that the differences between the results obtained from the corrected and uncorrected spectra are strongly proportional to the magnitude of the PGM feature. We also show that the bulk temperatures during the remainder of the “heater on” period after the overshoot can generally be estimated reliably by the standard analysis software, though with some important exceptions. These results are important since the plasma temperatures play a crucial role in governing thermal conduction processes, and their correct estimation is thus very important to understanding the underlying physical processes which occur during ionospheric heating.

Crystal Structure of SmcR, a Quorum-sensing Master Regulator of Vibrio vulnificus, Provides Insight into Its Regulation of Transcription

Quorum sensing has been implicated as an important global regulatory system controlling the expression of numerous virulence factors in bacterial pathogens. SmcR, a homologue of Vibrio harveyi LuxR, has been proposed as a quorum-sensing master regulator of Vibrio vulnificus, an opportunistic human pathogen. Previous studies demonstrated that SmcR is essential for the survival and pathogenesis of V. vulnificus, indicating that inhibiting SmcR is an attractive approach to combat infections by the bacteria. Here, we determined the crystal structure of SmcR at 2.1 Å resolution. The protein structure reveals a typical TetR superfamily fold consisting of an N-terminal DNA binding domain and a C-terminal dimerization domain. In vivo and in vitro functional analysis of the dimerization domain suggested that dimerization of SmcR is vital for its biological regulatory function. The N-terminal DNA recognition and binding residues were assigned based on the protein structure and the results of in vivo and in vitro mutagenesis experiments. Furthermore, protein-DNA interaction experiments suggested that SmcR may have a sophisticated mechanism that enables the protein to recognize each of its many target operators with different affinities.

On Deriving Plasma Velocity Information from CDS/NIS Observations: Application to the Dynamics of Blinkers

Using standard instrument software and two independently developed data reduction and analysis procedures, we re-examine the accuracy of plasma velocity information derived from data obtained by the Solar and Heliospheric Observatory (SOHO)–Coronal Diagnostic Spectrometer (CDS). We discuss only the Ov 629 A line data obtained by the Normal Incidence Spectrometer (NIS) and analyse a quiet Sun (QS) and active region (AR) dataset. Using the QS data, we demonstrate that the well-known North-South tilt in wavelength along the NIS slit varies significantly with time, which is not accounted for in the standard CDS correction procedures. In addition, when residual N – S trends exist in the data after processing, they may not be detected, nor removed, using the standard analysis software. This underscores the need for careful analysis of velocity results for individual datasets when using standard correction procedures. Furthermore, even when the results obtained by the two independent methods are well correlated (coefficients greater than 0.9), discrepancies in the values of the derived Doppler velocities can remain (95% within ±5 km s−1). Therefore, we apply the results to examine the velocities obtained for EUV blinkers by previous authors. It is found that a strong correlation exists in the patterns of variation of the blinker velocities (> 0.98), even though there may be differences in their magnitudes. That is, in a clear majority of cases, the methods agree that a blinker is red-shifted or blue-shifted, although the uncertainty in the absolute velocity may be large.

Finite element analysis of forces created by root separation and resection modelling.

Natural teeth with a healthy periodontal support exhibit stress transfer when functional forces are applied to them. These stress patterns show considerable variations during differing treatment modalities, which may influence both the tooth and supporting alveolar bone. The purpose of this study was to evaluate variations in the stress transfer under functional loads on first molars with periodontal furcation involvement, which were treated either with by root resection or root separation. This study used a two dimensional mathematical model of a mandibular first molar that was subjected to either a root separation or a root resection procedure. An evenly distributed dynamic load (600 N) was applied on two buccal cusps and distal fossae of the molar in centric occlusion. The analysis was performed using an IBM-compatible computer running standard analysis software. It was found that in the root resection model the stress values were maximum on the centre of rotation, and compressive stresses increased towards the middle of the cervical line. For the root separation model, the maximum shear stress values were observed in the distal portion, and a uniform stress distribution was observed in the mesial portion. Shear stress values for bone increased towards the centre in the bifurcation area. The outcomes of this study may be useful as a guide in clinical restorative procedures.

Overestimation of osteopenia using standard analysis software for peripheral quantitative computed tomography

It is well established that measurement of bone mineral density (BMD) can estimate the risk of future fractures. To assess individual fracture risk BMD measurements are compared with a reference range provided by the manufacturer of the respective BMD technology. However, the power of trabecular bone measured by peripheral quantitative computed tomography (pQCT) to predict future fractures has not been shown up to now. We conducted measurements of trabecular bone density (TBD) at the distal radius (pQCT XCT 900, Stratec, Germany) in a sample of 506 healthy white women aged 40-60 years (mean 48) and compared the results with the manufacturer's normal range. We found a remarkable difference in TBD values between our healthy study population and the manufacturer's reference data in all age groups (e.g., age 50-54 years, 143.1 +/- 43.2 mg/cm3 versus 181.1 +/- 39.0 mg/cm3). Compared to the +/- 2 SD limits of the manufacturer's reference range our study population showed mean TBD values that were about 1 SD below the mean of the reference range. About 50% of our healthy cohort were below the -1 SD limit of the reference range. Almost ten times as many normal subjects as expected (22.1%) were found below the -2 SD limit and therefore classified as individuals with increased fracture risk. This overestimation of fracture risk leads to discomfort of the patient, unnecessary therapeutic intervention, and significant costs to the public.(ABSTRACT TRUNCATED AT 250 WORDS)

ROSAT Observations of Symbiotic Stars

The German X-ray astronomy satellite ROSAT (launched 1990 June 1) performed an all-sky survey (from 1990 Jul 30 till 1991 Jan 26) with the Position Sensitive Proportional Counter (2 deg FoV, .1–2.4 keV) covering 96% of the sky. Analysis of bright X-ray sources suggests PSPC positions can be accurately determined to within 30 arcsec, and 1‥2 arcmin for soft weak ones. We have examined the survey data for detections from among a list of 189 symbiotic and symbiotic-like objects compiled by Vaidis (1988) with own extensions, chosen for completeness. For 178 objects, all-sky data was available. Standard Analysis Software System (SASS) and EXtended Standard Analysis Software packages (EXSAS) both use a three-step approach to detect sources. After quality screening, a sliding-window algorithm (LD) locates bright sources. These are excluded in the 2D-spline interpolated smoothed background map. A second sliding window MD runs on the background subtracted event files. All possible sources were then tested by maximum likelihood in the background-subtracted, exposure-corrected image. If LD, MD, or ML did not detected a source at the optical position, an upper limit ML program tried to find enhanced emission. For EXSAS, photon event files contain all photons within 20 arcmin radius around a source. Cut radii, background determination, and other parameters can be iteratively improved.