Peak Standard Deviation Research Articles

Tilted global solar irradiance in Bahrain: an experimental study

Abstract In the present work, tilted global solar irradiance data are presented and analysed, measured for a period of 1 year on the campus of Bahrain Polytechnic, Kingdom of Bahrain, from both a fixed photovoltaic panel and a moving one via a two-axis solar tracker. The fixed panel faces south with an angle of 26° with respect to the horizontal, coinciding with the local geographical latitude. The second panel is moved by two motors, controlled by a global positioning system and suitable software so that the Sun’s rays are perpendicular to the panel surface. A pyranometer is installed on each panel, recording the tilted global solar irradiance, stored by using a data logger. The analysis of the data obtained shows a 33% solar energy gain on an annual basis for the moving panel (2780 versus 2088 kWh/m2 on the fixed panel). More importantly, in June, when the energy demand in Bahrain is elevated due to the increased residential cooling loads, the solar energy received by the moving panel is 54.7% higher compared with that of the fixed panel. On a percentage basis, the increase in solar energy from the moving panel is profound in the early morning and late evening hours. Moreover, the reduction in the solar energy received by the fixed panel from May to June does not appear in the moving panel because of the adjustable orientation of the latter. Throughout the year, the mean daily solar power varies between 0.37 and 0.56 kW/m2 for the fixed panel, and 0.45 and 0.70 kW/m2 for the moving panel. In winter, solar energy fluctuations are elevated due to erratic weather conditions that present a peak standard deviation of 28% of the corresponding mean. The data presented are useful for potential solar investments in Gulf countries.

Standard deviations of MR signal intensities show a consistent trend during imaging follow-ups for glioblastoma patients when corrected for non-biological heterogeneity due to hardware and software variation

IntroductionGlioblastoma multiforme (GBM) has a poor prognosis in spite of advanced MRI guided treatments today. Routine MRI using conventional T1 or advanced permeability based MRI of GBM often does not adequately represent changing tumor phases or overall survival. In this work, region of interest (ROI) based tissue MR standard deviation (SD) is demonstrated as an important MRI variable that could be a potential biomarker of GBM heterogeneity and radioresistance. Materials and methodsMRI characterization is often qualitative and lacks reproducibility. Using standardized MRI phantoms we have normalized retrospective records of 12 radioresistant GBM patients that underwent radiation therapy (RT) with concomitant and adjuvant temozolomide (TMZ) chemotherapy followed by serial MR imaging with gadolinium contrast. Results and discussionWe have identified key variables like hardware, software and protocol variation and have standardized those using test phantoms at five MR systems. We suggest GBM growth during the treatment period can be linked to normalized MRI signal and its fluctuations from session to session and from magnet to magnet by using an ROI derived standard deviation that corresponds to heterogeneity of the tumor MRI signal and changes in magnetic susceptibility. The time period observed in our patient group for peak standard deviations is approximately halfway through the tumor course and may correspond to a growth of more aggressive MES subtype of cells. To model the GBM heterogeneity we performed in vitro T1 weighted inversion recovery MRI experiments at 3 T for porous media of silicate particles in 1% aq solution of Gadavist and linked SD with particle size and local gadolinium volume within porous media. Such in vitro models mimic the increased SD in radioresistant GBM and as a novel contribution suggest that finer texture with high surface area might arise approximately halfway through the overall survival duration in GBM. ConclusionStandard deviation as a measure of magnetic susceptibility may be collectively linked to the changes in texture, cell fractions (biological) and trapped contrast media (vascular as well as artifactual consequences) and should be evaluated as a potential biomarker of GBM aggressiveness than the overall MRI signal intensity from a GBM.

Re-Examining the Impact of Minimal Scans in Liquid Chromatography-Mass Spectrometry Analysis.

Liquid chromatography-mass spectrometry (LC-MS) is one of the most widely used analytical tools. High analysis volumes and sample complexity often demand more informative LC-MS acquisition schemes to improve efficiency and throughput without compromising data quality, and such a demand has been always hindered by the prerequisite that a minimum of 13-20 MS scans (data points) across an analyte peak are required for accurate quantitation. The current study systematically re-evaluated and compared the impact of different scan numbers on quantitation analysis using both triple quadrupoles mass spectrometry (TQMS) and high-resolution mass spectrometry (HRMS). Contrary to the 13-20 minimal scan prerequisite, the data obtained from a group of eight commercial drugs in the absence and presence of biological matrices suggest that 6 scans per analyte peak are sufficient to achieve highly comparable quantitation results compared to that obtained using 10 and 20 scans, respectively. The fewer minimal scan prerequisite is presumably attributed to an improved LC system and advanced column technology, better MS detector, and more intelligent peak detection and integration algorithms leading to a more symmetric peak shape and smaller peak standard deviation. As a result, more informative acquisition schemes can be broadly set up for higher throughput and more data-rich LC-MS/MS analysis as demonstrated in a hepatocyte clearance assay in which fewer MS scans executed on HRMS led to broader metabolite coverage without compromising data quality in hepatic clearance assessment. The demonstrated acquisition scheme would substantially increase the throughput, robustness, and richness of the nonregulatory analysis, which can be broadly applied in diverse fields including pharmaceutical, environmental, forensic, toxicological, and biotechnological.

The influence of injection volume on efficiency of microbore liquid chromatography columns for gradient and isocratic elution

The injection volume and the associated column volume overload is one of the most common issues in miniaturized chromatography. The injection volume should not exceed 10% of the effective column volume. A further reduction of the injection volume leads to an increase in chromatographic efficiency. However, the signal intensity must be above a certain threshold to generate a chromatographic peak that can be detected. Therefore, the injection volume has to be optimized to reach the ideal balance between chromatographic efficiency and sensitivity. This study examined the general influence of the injection volume for both isocratic and gradient elution, depending on the retention factor and peak standard deviation. For this purpose, substances of different polarity were selected to represent a broad elution spectrum. Besides the model analyte naphthalene, these were mainly pharmaceuticals. For all measurements a microbore column with an ID of 300 µm and packed with 1.9 μm fully porous particles was used. For isocratic elution, the injection volume was varied between 4 and 16% of the effective column volume. The retention factors were adjusted between 2 and 10. For gradient elution, the injection volume was varied between 4 and 160% of the effective column volume. The observed effects were further investigated using the gradient kinetic plot theory. In isocratic elution, a loss in plate height up to 50% was observed for components that elute near the void time. A significant reduction of the chromatographic efficiency was noticed up to a retention factor of 4. In gradient elution, a reduction in peak capacity could only be observed if the injection volume exceeded 40% of the effective column volume. For some substances, only a slight loss in peak capacity was noticed even with a volume overload of 160%.

Wind Tunnel Pressure Series Statistics for the Case of a Large Span Canopy Roof

This paper investigates pressure coefficient and peak factor statistics for a hyperbolic paraboloid canopy roof used as a tensile structure to cover a soccer arena. The non-Gaussian properties of the pressure coefficient processes are measured at different roof locations for different wind angles of attack. Peak factor statistics, estimated using pressure coefficient time histories experimentally measured in wind tunnel tests and measured on the bottom and on the top of the roof, are compared with corresponding peak factor statistics estimated through use of four analytical models available in the literature, namely the Davenport, classical Hermite, revised Hermite, and translated-peak-process (TPP) models. It was found that: (1) all analytical models underestimate the mean and standard deviations of the experimental peak factors; (2) the non-Gaussianity region is significantly affected by the position on the roof, i.e., up and down, whereas it is less affected by the wind angle; (3) the two Hermite models provide accurate estimates of peak factor mean and standard deviations.

Simulation of peak position and response profiles in comprehensive two-dimensional gas chromatography

Approaches to simulate peak time and intensity profiles of compounds in comprehensive two dimensional gas chromatography (GC × GC) were developed, and which are demonstrated for separation of a mixture of saturated and unsaturated fatty acid methyl esters (FAME) using a range of column sets. The simulation of first and second dimension time (1tR and 2tR) of FAME relies on use of a Gibbs energy additivity approach to correlate with the structures of FAME. First and second dimension peak standard deviations (1σ and 2σ) of the compounds were further calculated from the 1tR and 2tR data according to the plate height concept which provided good agreement between the predicted and experimental peak widths at half height in one dimension GC (1DGC) with an overall R2 of 0.9628. The effect of 1σ distortion caused by the modulation process was also taken into account in the peak width simulation where the simulated 1σ data were rounded up to multiples of the scale of modulation period (PM). Two dimension Gaussian equations were then used to generate GC × GC results (2D contour plots) from simulated 1tR, 2tR, 1σ and 2σ data for FAME separation on different column sets employing ionic liquid and conventional columns. Good overall correlations between experimental and simulated 1tR and 2tR were obtained with R2 of 0.9951 and 0.9802, respectively, and the simulated 2D contour plots were an acceptable match with the experimental results.

A Method to Reduce the Effect on Image Quality Caused by Resistance of Column Bus

In this paper, a method to reduce the effect on image quality caused by the parasitic resistance of column bus in high-resolution cMOS image sensors is presented. Through the mathematical model of the column bus, the effect on image quality caused by the resistance is analyzed. The resistance would cause two nonideal factors: dynamic swing reduction and nonlinearity. To reduce the effect of the nonideal factors, this paper utilizes a layout design by putting the readout circuit and column bias circuit on different sides of the pixel array. The relationship among the resistance, light intensity of input, and standard deviation of output gray levels is analyzed. In a 0.13- $\mu \text{m}$ CMOS process and a 12 cm $\times$ 12 cm pixel array, the simulation result shows that the resistance would cause column stripes or gradient under a traditional method. Under the proposed method, the peak standard deviation under uniform illumination decreases from 16.25 to 1.44. The peak signal-to-noise ratio increases from 64.66 to 91.64 dB and the structural similarity index increases from 0.79 to 0.97. The proposed method can enhance image quality for high-resolution image sensors significantly.

Effects of different ultrasound power application on left ventricular myocardium synchrony in vivo open-chest Beagle canines

Objective To evaluate left ventricular (LV) myocardial mechanical synchrony with contrast agent and different power irradiation in open-chest Beagle canines. Methods The anesthetized open-chest Beagle canines were assigned into two groups randomly: Group A (n=6) for baseline, diagnostic ultrasound power irradiation (300 mW) 5 min, combined with contrast agent irradiation 5 min and contrast agent 20 min conditions; Group B (n=6) for baseline and intensity ultrasound irradiation (1 W, 2 W and 3 W, 5 min respectively) conditions. The standard short-axis gray-scale views at levels of mitral annulus (MV), papillary muscle(PM), and apex(AP) during 3 complete cardiac cycles in open-chest Beagle canine models were acquired. The global radial displacement peak time (RD-PT) and standard deviation of peak time (RD-PTSD) of LV subendomyocardium (subendo) and subepimyocardium (subepi) were measured and analyzed by using a dedicated Syngo velocity vector imaging (VVI) method. Results In group A, compared with baseline condition, the RD-PT and RD-PTSD of subendo and subepi had no significant different among diagnostic power irradiation, contrast agent irradiation 5 min and contrast agent 20 min (all P<0.05). There was no significant different in the RD-PT and RD-PTSD between subendo and subepi in A group in all conditions (all P<0.05). In group B, the RD-PT and RD-PTSD of subendo and subepi with power 1 W, 2 W and 3 W was higher than those with baseline condition; the RD-PT and RD-PTSD of subendo were significant different on 2 W compared with those on baseline condition (all P<0.05); the RD-PT and RD-PTSD of subendo, subepi were significant different on 3 W compared with baseline condition (all P<0.05); the RD-PT and RD-PTSD were significant difference between subendo and subepi in only 3 W condition (all P<0.05). Conclusions Diagnostic ultrasound power irradiation 5 min and combined with contrast agent irradiation 5 min and contrast agent 20 min conditions do not effect the synchrony of LV myocardial mechanics. Power more than 1 W can induce the delay of RD-PT and RD-PTSD of LV subendo and subepi. Power 3 W can result in dyssynchrony of LV myocardial mechanics. Key words: Sonication; Ventricular function, left; Beagle canines; Synchrony

Analysis of shock unsteadiness in a supersonic over-expanded planar nozzle

An experimental investigation has been conducted to study the unsteady nature of the shock structure in an over-expanded planar nozzle. The main emphasis was to investigate (i) the effect of resonance associated with laminar shock-wave/boundary-layer interactions on the unsteady characteristics of the wall pressure signals in the region of the interaction and, (ii) the change in these characteristics as the state of boundary layer undergoes transition to turbulence and a resonance free interaction. The tests were conducted in a Mach 2 planar nozzle with wall-half angle of 5.7∘. For almost all the NPR for which the nozzle is tested, the boundary layer state is seen to be in the laminar/transitional range and exhibits resonance for nozzle pressure ratios less than 2.3. The resonance tones associated with the laminar interactions result in a considerable increase in the length of the intermittent region. However, as the boundary layer state goes into the transitional regime and the resonance tones disappear, the length of intermittent region is seen to decrease significantly. A decrease in this length also causes the peak standard deviation values to decrease. Further a free interaction region is observed for separated nozzle flows irrespective of the NPR of operation for resonance free interactions.

Coherent anti-Stokes Raman spectroscopy of a premixed ethylene–air flame in a dual-mode scramjet

As part of a broader effort to provide detailed measurements of turbulent flames in dual-mode scramjets, promote a deeper understanding of the relevant combustion physics, and aid appropriate computational model development, a high-subsonic cavity-stabilized premixed ethylene–air flame (typical of ramjet operation) is studied using coherent anti-Stokes Raman spectroscopy. This technique provides simultaneous measurements of temperature, separate O2 temperature, and mole fraction of N2, O2, CO, CO2, and C2H4. The experiments reveal a highly unsteady turbulent flame, approximately two-dimensional in the mean, which propagates downstream from the cavity and towards the observation wall. Measurements in the flame region reveal a flow that is largely divided into reactants (freestream fluid) and (nearly) equilibrium products, separated by flames that cannot be resolved by the CARS measurement volume, which is about 1 mm long. Mean and standard deviation of the resolved fluctuations of the temperature and mole fractions of species are quantified. The peak standard deviation in each profile across the flame occurs where the mean gradient is steepest, and is about 37% the difference between reactants (freestream) and products conditions. Several cases were investigated including limiting combustion cases near the lean fuel and low air temperature blowouts; in all cases the flame propagation angles are the same and distributions of suitably normalized mean and fluctuation parameters are similar at all locations and for all cases.

Origin of side-loads in a subscale truncated ideal contour nozzle

An experimental investigation was conducted in a cold flow test facility to identify the origin of various flow conditions that lead to side-load generation in a truncated ideal contour nozzle (of area-ratio 20.66) especially at moderate nozzle pressure ratio range of 20 to 42 during the start-up and shutdown sequences. The major contributors seem to be the transition in flow conditions namely, the change in the circumferential shape of re-circulation region inside the nozzle from a cylindrically dominated regime to a conical one and the end-effect regime that initiate highly unsteady flow conditions in the separation region preceding these transitions. Other flow transitions such as those initiated by the onset of test gas condensation and vice-versa result in a downstream or an upstream jump in separation, respectively, that causes the overall side-load signal to increase. During this flow regime, an increase in the length of the upstream influence region accompanied by a rise in the peak standard deviation value is also observed.

Cost heterogeneity and peak prediction in collective actions

The peak of participants indicates the success probability of collective actions. The mathematical model is built to explore the mechanism and prediction values of peaks. Besides of utility heterogeneity, cost heterogeneity is added into to simulate the situation of multiple heterogeneities in reality. Each simulation is run one hundred times repeatedly to get stable expectations and standard deviations of peaks under each combination of parameter values. Based on results of simulation, effects of related factors on peaks is investigated and estimated statistically, making it possible to predict peaks. In addition to forecasting the mean of peaks, the variability of peaks is estimated as well. Therefore, the distribution of peaks is predicted. Utility heterogeneity, cost heterogeneity and the Jointness of supply (J) exert significant effects on the distribution of peaks. It indicates that both utility heterogeneity and cost heterogeneity reduce the values and increase the variability (standard deviation) of peaks. Facilitating chain actions among individuals, heterogeneity promotes the outbreak of collective actions. However, it reduces the peaks and decreases the success probability of collective actions, while homogeneity increases the peak of participants and enhances the success chance of collective actions.

A peak-cluster assessment method for the identification of upland planation surfaces

ABSTRACTResidual upland planation surfaces serve as strong evidence of peneplains during long intervals of base-level stability in the peneplanation process. Multi-stage planation surfaces could aid the calculation of uplift rates and the reconstruction of upland plateau evolution. However, most planation surfaces have been damaged by crustal uplift, tectonic deformation, and surface erosion, thus increasing the difficulty in automatically identifying residual planation surfaces. This study proposes a peak-cluster assessment method for the automatic identification of potential upland planation surfaces. It consists of two steps: peak extraction and peak-cluster characterization. Three critical parameters, namely, landform planation index (LPI), peak elevation standard deviation, and peak density, are employed to assess peak clusters. The proposed method is applied and validated in five case areas in the Tibetan Plateau using a Shuttle Radar Topography Mission digital elevation model (SRTM DEM) with 3 arc-second resolution. Results show that the proposed method can effectively extract potential planation surfaces, which are found to be stable with different resolutions of DEM data. A significant planation characteristic can be obtained in the relatively flat areas of the Gangdise–Nyainqentanglha Mountains and Qaidam Basin. Several vestiges of potential former planation areas are also extracted in the hilly-gully areas of the western part of the Himalaya Mountains, the northern part of the Tangula–Hengduan Mountains, and the northeastern part of the Kunlun–Qinling Mountains despite the absence of significant topographical features characterized by low slope angles or low terrain reliefs. Vestiges of planation surfaces are also identified in these hilly-gully upland areas. Hence, the proposed method can be effectively used to extract potential upland planation surfaces not only in flat areas but also in hilly-gully areas.

Effect of lower-limb joint models on subject-specific musculoskeletal models and simulations of daily motor activities

Understanding the validity of using musculoskeletal models is critical, making important to assess how model parameters affect predictions. In particular, assumptions on joint models can affect predictions from simulations of movement, and the identification of image-based joints is unavoidably affected by uncertainty that can decrease the benefits of increasing model complexity. We evaluated the effect of different lower-limb joint models on muscle and joint contact forces during four motor tasks, and assessed the sensitivity to the uncertainties in the identification of anatomical four-bar-linkage joints. Three MRI-based musculoskeletal models having different knee and ankle joint models were created and used for the purpose. Model predictions were compared against a baseline model including simpler and widely-adopted joints. In addition, a probabilistic analysis was performed by perturbing four-bar-linkage joint parameters according to their uncertainty. The differences between models depended on the motor task analyzed, and there could be marked differences at peak loading (up to 2.40 BW at the knee and 1.54 BW at the ankle), although they were rather small over the motor task cycles (up to 0.59 BW at the knee and 0.31 BW at the ankle). The model including more degrees of freedom showed more discrepancies in predicted muscle activations compared to measured muscle activity. Further, including image-based four-bar-linkages was robust to simulate walking, chair rise and stair ascent, but not stair descent (peak standard deviation of 2.66 BW), suggesting that joint model complexity should be set according to the imaging dataset available and the intended application, performing sensitivity analyses.

Application of polymeric macroporous supports for temperature-responsive chromatography of pharmaceuticals

A macroporous particulate support prepared previously by reactive gelation under shear and functionalized with poly(N-isopropylacrylamide), PNIPAM, brushes of variable length is applied for temperature-responsive chromatography, whereby temperature modulates hydrophobic interactions. Several different analytes, including small pharmaceuticals, peptides, proteins and monoclonal antibodies are employed. Contrary to the most commonly observed behavior in conventional chromatography, increasing retention is observed at elevated temperatures. Peak broadening is quantified using the peak standard deviation, which depends on both the polymer chain conformation and analyte adsorptivity. The favorable effect of grafted polymer thickness on retention becomes progressively less pronounced for thicker grafted PNIPAM layers. The effect of eluent composition on solute–sorbent interactions was investigated by introducing NaCl, methanol, dioxane and by varying the pH. Salt or organic solvent addition affects apart from the analytes solution properties, the hydrophobicity of the stationary phase itself. Frontal analyses performed at different temperatures to determine dynamic binding capacities, indicate small mass transfer resistances imposed by this novel packing material.

WE-C-116-10: Univariate, Multivariate, and Nonlinear Uncertainty Quantification for Magnetic Resonance-Guided Laser Induced Thermal Therapy

Purpose: MR‐guided laser‐induced thermal therapy (MRgLITT) is an emerging minimally invasive neurosurgical tool being explored as a treatment alternative for conditions such as motion disorder, radiation necrosis, and intracranial metastases. The primary goal is to reduce complications and normal tissue morbidity associated with conventional surgery. Computational models are being investigated to aid prospective LITT planning; however, accuracy is undermined by imprecise and non‐patient specific knowledge of parameters. This work explores incorporating uncertainty quantification (UQ) of temperature output from the stochastic Pennes bioheat transfer equation (BHT). Methods: A five parameter (perfusion, thermal conductivity, optical absorption, optical scattering) stochastic BHT LITT model was used. Parameters were considered to be uniform distributions with ranges informed by literature values. Generalized polynomial chaos (gPC) was employed to calculate spatio‐temporal, voxel‐wise functions of the output temperature distributions for UQ. BHT parameter sensitivity in linear and nonlinear models was explored in silico using univariate gPC. Retrospective analysis of MR thermography (MRTI) from both phantom and MRgLITT in normal canine brain in vivo (n=4) was explored using multivariate gPC. Isotherms, temporal and linear profiles were reported. Results: Univariate simulations demonstrated that optical parameters explained the majority of model variance (peak standard deviation: anisotropy 3.75 °C, absorption 2.94 °C, scattering 1.84 °C, conductivity 1.42 °C, and perfusion 0.94 °C). Linear model variance enclosed nonlinear model variance. Mean temperature and 95% confidence interval from multivariate simulations correlated well with measured heating even near the applicator. Conclusion: gPC may provide robust and relatively fast UQ facilitating useful prospective LITT planning in brain tissue despite imprecise knowledge of parameters. The faster linear simulation approximated the nonlinear simulation without excessive variance. Further, the computational burden was reduced with minimal accuracy loss by including only the most sensitive parameters. Subsequent work includes applying stochastic BHT to retrospective human brain tumor LITT.

Generalised polynomial chaos-based uncertainty quantification for planning MRgLITT procedures

Purpose: A generalised polynomial chaos (gPC) method is used to incorporate constitutive parameter uncertainties within the Pennes representation of bioheat transfer phenomena. The stochastic temperature predictions of the mathematical model are critically evaluated against MR thermometry data for planning MR-guided laser-induced thermal therapies (MRgLITT). Methods: The Pennes bioheat transfer model coupled with a diffusion theory approximation of laser tissue interaction was implemented as the underlying deterministic kernel. A probabilistic sensitivity study was used to identify parameters that provide the most variance in temperature output. Confidence intervals of the temperature predictions are compared to MR temperature imaging (MRTI) obtained during phantom and in vivo canine (n = 4) MRgLITT experiments. The gPC predictions were quantitatively compared to MRTI data using probabilistic linear and temporal profiles as well as 2-D 60 °C isotherms. Results: Optical parameters provided the highest variance in the model output (peak standard deviation: anisotropy 3.51 °C, absorption 2.94 °C, scattering 1.84 °C, conductivity 1.43 °C, and perfusion 0.94 °C). Further, within the statistical sense considered, a non-linear model of the temperature and damage-dependent perfusion, absorption, and scattering is captured within the confidence intervals of the linear gPC method. Multivariate stochastic model predictions using parameters with the dominant sensitivities show good agreement with experimental MRTI data. Conclusions: Given parameter uncertainties and mathematical modelling approximations of the Pennes bioheat model, the statistical framework demonstrates conservative estimates of the therapeutic heating and has potential for use as a computational prediction tool for thermal therapy planning.

Relationship between mechanical and metabolic dyssynchrony with left bundle branch block: Evaluation by 18-fluorodeoxyglucose positron emission tomography in patients with non-ischemic heart failure

Ventricular dyssynchrony is a common finding in patients with heart failure (HF), especially in the presence of conduction delays. The loss of ventricular synchrony leads to progressive impairment of contractile function, which may be explained in part by segmental abnormalities of myocardial metabolism. However, the association of these metabolic disarrangements with parameters of ventricular dyssynchrony and electrocardiography (ECG) findings has not yet been studied. Our aim was to determine the correlation between the presence of left bundle branch block (LBBB) with left ventricular (LV) mechanical synchrony assessed by multiple-gated acquisition scan (MUGA) and with patterns of 18-fluorodeoxyglucose (18FDG) uptake in patients with non-ischemic heart failure. Twenty-two patients with non-ischemic cardiomyopathy, LV ejection fraction (LVEF) ≤45% and New York Heart Association (NYHA) Functional Class II or III symptoms under standard medical therapy were included, along with 10 healthy controls matched for age and gender. A 12-lead ECG was obtained to measure the length of the QRS. Mechanical LV synchrony was assessed by MUGA using phase analysis. All patients and controls underwent positron emission tomography with 18FDG to determine the distribution of myocardial glucose uptake. The standard deviation of peak (18)FDG uptake was used as an index of metabolic heterogeneity. Student's t-test and Pearson's correlation were used for statistical analysis. The mean age of the patients with HF was 54 ± 12 years and 72% were male. The length of the QRS was 129 ± 31 milliseconds and LBBB was present in 9 patients. Patients with HF had decreased LV 18FDG uptake compared with controls (7.56 ± 3.36 vs. 11.63 ± 4.55 standard uptake value; p = 0.03). The length of the QRS interval correlated significantly with glucose uptake heterogeneity (r = 0.62; p = 0.002) and mechanical dyssynchrony (r = 0.63; p = 0.006). HF patients with LBBB showed marked glucose uptake heterogeneity compared with HF patients without LBBB (41.4 ± 10 vs 34.7 ± 4.9 ml/100 g/min, respectively; p = 0.01). Patients with non-ischemic heart failure exhibit a global decrease in myocardial glucose uptake. Within this group, subjects who also have LBBB exhibit a marked heterogeneity in segmental glucose uptake, which directly correlates with QRS duration.

Use of an iterative convolution approach for qualitative and quantitative peak analysis in low resolution gamma-ray spectra

In many applications, low resolution gamma-ray spectrometers, such as sodium iodide scintillation detectors, are widely used primarily due to their relatively low cost and high detection efficiency. There is widespread interest in improved methods for analyzing spectral data acquired with such devices, using inverse analysis. Peak means and peak areas in gamma- and X-ray spectra are needed for both qualitative and quantitative analysis. This paper introduces the PEAKSI code package that was developed at the Center for Engineering Applications of Radioisotopes (CEAR). The basic approach described here is to use accurate forward models and iterative convolution instead of direct deconvolution. Rather than smoothing and differentiation a combination of linear regression and non-linear searching is used to minimize the reduced chi-square, since this approach retains the capability of establishing uncertainties in the estimated peak parameters. The PEAKSI package uses a Levenberg–Marquardt (LM) non-linear search method combined with multiple linear regression (MLR) to minimize the reduced chi-square value for fitting single or multiple overlapping peaks to determine peak parameters, including peak means, peak standard deviations or full width at half maximum (FWHM), net peak counts, and background counts of peaks in experimental gamma-ray spectra. This approach maintains the natural error structure so that parameter uncertainties can be estimated. The plan is to release this code to the public in the near future.

Estimation of Migration-Time and Mobility Distributions in Organelle Capillary Electrophoresis with Statistical-Overlap Theory

The separation of organelles by capillary electrophoresis (CE) produces large numbers of narrow peaks, which commonly are assumed to originate from single particles. In this paper, we show this is not always true. Here, we use established methods to partition simulated and real organelle CEs into regions of constant peak density and then use statistical-overlap theory to calculate the number of peaks (single particles) in each region. The only required measurements are the number of observed peaks (maxima) and peak standard deviation in the regions and the durations of the regions. Theory is developed for the precision of the estimated peak number and the threshold saturation above which the calculation is not advisable due to fluctuation of peak numbers. Theory shows that the relative precision is good when the saturation lies between 0.2 and 1.0 and is optimal when the saturation is slightly greater than 0.5. It also shows the threshold saturation depends on the peak standard deviation divided by the region's duration. The accuracy and precision of peak numbers estimated in different regions of organelle CEs are verified by computer simulations having both constant and nonuniform peak densities. The estimates are accurate to 6%. The estimated peak numbers in different regions are used to calculate migration-time and electrophoretic-mobility distributions. These distributions are less biased by peak overlap than ones determined by counting maxima and provide more correct measures of the organelle properties. The procedure is applied to a mitochondrial CE, in which over 20% of peaks are hidden by peak overlap.