A multi-level decomposition of variance in somatic symptom reporting in families with adolescent children

OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

Concordance Probability and Discriminatory Power in Proportional Hazards Regression

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.

Power Calculations for Preclinical Studies Using a K-Sample Rank Test and the Lehmann Alternative Hypothesis

Power calculations in a small sample comparative study, with a continuous outcome measure, are typically undertaken using the asymptotic distribution of the test statistic. When the sample size is small, this asymptotic result can be a poor approximation. An alternative approach, using a rank based test statistic, is an exact power calculation. When the number of groups is greater than two, the number of calculations required to perform an exact power calculation is prohibitive. To reduce the computational burden, a Monte Carlo resampling procedure is used to approximate the exact power function of a k-sample rank test statistic under the family of Lehmann alternative hypotheses. The motivating example for this approach is the design of animal studies, where the number of animals per group is typically small.

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.

Statistics of the received power for free space optical channels

Free space optical (FSO) communication links can experience extreme signal degradation due to atmospheric turbulence induced spatial and temporal irradiance fuctuations (scintillation) in the laser wavefront. In addition, turbulence can cause the laser beam centroid to wander resulting in power fading, and sometimes complete loss of the signal. Spreading of the laser beam and jitter are also artifacts of atmospheric turbulence. To accurately predict the signal fading that occurs in a laser communication system and to get a true picture of how this affects crucial performance parameters like bit error rate (BER) it is important to analyze the probability density function (PDF) of the integrated irradiance fuctuations at the receiver. In addition, it is desirable to find a theoretical distribution that accurately models these ?uctuations under all propagation conditions. The PDF of integrated irradiance fuctuations is calculated from numerical wave-optic simulations of a laser after propagating through atmospheric turbulence to investigate the evolution of the distribution as the aperture diameter is increased. The simulation data distribution is compared to theoretical gamma-gamma and lognormal PDF models under a variety of scintillation regimes from weak to very strong. Our results show that the gamma-gamma PDF provides a good fit to the simulated data distribution for all aperture sizes studied from weak through moderate scintillation. In strong scintillation, the gamma-gamma PDF is a better fit to the distribution for point-like apertures and the lognormal PDF is a better fit for apertures the size of the atmospheric spatial coherence radius ρ0 or larger. In addition, the PDF of received power from a Gaussian laser beam, which has been adaptively compensated at the transmitter before propagation to the receiver of a FSO link in the moderate scintillation regime is investigated. The complexity of the adaptive optics (AO) system is increased in order to investigate the changes in the distribution of the received power and how this affects the BER. For the 10 km link, due to the non-reciprocal nature of the propagation path the optimal beam to transmit is unknown. These results show that a low-order level of complexity in the AO provides a better estimate for the optimal beam to transmit than a higher order for non-reciprocal paths. For the 20 km link distance it was found that, although minimal, all AO complexity levels provided an equivalent improvement in BER and that no AO complexity provided the correction needed for the optimal beam to transmit. Finally, the temporal power spectral density of received power from a FSO communication link is investigated. Simulated and experimental results for the coherence time calculated from the temporal correlation function are presented. Results for both simulation and experimental data show that the coherence time increases as the receiving aperture diameter increases. For finite apertures the coherence time increases as the communication link distance is increased. We conjecture that this is due to the increasing speckle size within the pupil plane of the receiving aperture for an increasing link distance.

Parametric combustion modeling for ethanol-gasoline fuelled spark ignition engines

Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.

Optimal current control for sub-unity power factor correction

Switching mode power supplies (SMPS) are subject to low power factor and high harmonic distortions. Active power-factor correction (APFC) is a technique to improve the power factor and to reduce the harmonic distortion of SMPSs. However, this technique results in double frequency output voltage variation which can be reduced by using a large output capacitance. Using large capacitors increases the cost and size of the converter. Furthermore, the capacitors are subject to frequent failures mainly caused by evaporation of the electrolytic solution which reduce the converter reliability. This thesis presents an optimal control method for the input current of a boost converter to reduce the size of the output capacitor. The optimum current waveform as a function of weighing factor is found by using the Euler Lagrange equation. A set of simulations are performed to determine the ideal weighing which gives the lowest possible output voltage variation as the converter still meets the IEC-61000-3-2 class-A harmonics requirements with a power factor of 0.8 or higher. The proposed method is verified by the experimental work. A boost converter is designed and it is run for different power levels, 100 W, 200 W and 400 W. The desired output voltage ripple is 10 V peak to peak for the output voltage of 200 Vdc. This ripple value corresponds to a ± 2.5% output voltage ripple. The experimental and the simulation results are found to be quite matching. A significant reduction in capacitor size, as high as 50%, is accomplished by using the proposed method.

Relationship between inflammation and cognitive function in obstructive sleep apnea

OBJECTIVES: Obstructive sleep apnea (OSA) can have adverse effects on cognitive functioning, mood, and cardiovascular functioning. OSA brings with it disturbances in sleep architecture, oxygenation, sympathetic nervous system function, and inflammatory processes. It is not clear which of these mechanisms is linked to the decrease in cognitive functioning. This study examined the effect of inflammatory parameters on cognitive dysfunction. MATERIALS AND METHODS: Thirty-nine patients with untreated sleep apnea were evaluated by polysomnography and completed a battery of neuropsychological tests. After the first night of evaluation in the sleep laboratory, blood samples were taken for analysis of interleukin 6, tumor necrosis factor-alpha (TNF-alpha), and soluble TNF receptor 1 (sTNF-R1). RESULTS: sTNF-R1 significantly correlated with cognitive dysfunction. In hierarchical linear regression analysis, measures of obstructive sleep apnea severity explained 5.5% of the variance in cognitive dysfunction (n.s.). After including sTNF-R1, percentage of variance explained by the full model increased more than threefold to 19.6% (F = 2.84, df = 3, 36, p = 0.05). Only sTNF-R1 had a significant individual relationship with cognitive dysfunction (beta = 0.376 t = 2.48, p = 0.02). CONCLUSIONS: sTNF-R1 as a marker of chronic inflammation may be associated with diminished neuropsychological functioning in patients with OSA.

Diminished prefrontal brain function in adults with psychopathology in childhood related to attention deficit hyperactivity disorder

The aim of the present study was to investigate prefrontal brain function and cognitive response control in patients with personality disorders who either suffered or did not suffer from psychopathology related to attention deficit hyperactivity disorder (ADHD) during childhood. For this purpose, 36 psychiatric out-patients with personality disorders--24 of whom showed ADHD-related psychopathology during childhood assessed by the German short form of the Wender Utah Rating Scale--and 24 healthy controls were investigated electrophysiologically by means of a cued Go-NoGo task (Continuous Performance Test). Topographical analyses were conducted to individually quantify the NoGo anteriorisation (NGA), a neurophysiological correlate of prefrontal response control that has been suggested to reflect activation of the anterior cingulate cortex. ADHD patients exhibited a significantly reduced mean NGA and diminished amplitudes of the Global Field Power, as well as a reduced increase of fronto-central P300 amplitudes, in NoGo-trials compared with the healthy controls, whereas patients with personality disorders alone did not differ from the control group in any of the electrophysiological parameters. The results indicate that ADHD-related psychopathology is associated with prefrontal brain dysfunction, probably related to processes of response inhibition and/or cognitive response control.

Improvement of cardiac function with device-based diaphragmatic stimulation in chronic heart failure patients: the randomized, open-label, crossover Epiphrenic II Pilot Trial.

AIMS Device-based pacing-induced diaphragmatic stimulation (PIDS) may have therapeutic potential for chronic heart failure (HF) patients. We studied the effects of PIDS on cardiac function and functional outcomes. METHODS AND RESULTS In 24 chronic HF patients with CRT, an additional electrode was attached to the left diaphragm. Randomized into two groups, patients received the following PIDS modes for 3 weeks in a different sequence: (i) PIDS off (control group); (ii) PIDS 0 ms mode (PIDS simultaneously with ventricular CRT pulse); or (iii) PIDS optimized mode (PIDS with optimized delay to ventricular CRT pulse). For PIDS optimization, acoustic cardiography was used. Effects of each PIDS mode on dyspnoea, power during exercise testing, and LVEF were assessed. Dyspnoea improved with the PIDS 0 ms mode (P = 0.057) and the PIDS optimized mode (P = 0.034) as compared with the control group. Maximal power increased from median 100.5 W in the control group to 104.0 W in the PIDS 0 ms mode (P = 0.092) and 109.5 W in the PIDS optimized mode (P = 0.022). Median LVEF was 33.5% in the control group, 33.0% in the PIDS 0 ms mode, and 37.0% in the PIDS optimized mode (P = 0.763 and P = 0.009 as compared with the control group, respectively). PIDS was asymptomatic in all patients. CONCLUSION PIDS improves dyspnoea, working capacity, and LVEF in chronic HF patients over a 3 week period in addition to CRT. This pilot study demonstrates proof of principle of an innovative technology which should be confirmed in a larger sample. TRIAL REGISTRATION NCT00769678.

Cost and power analysis of linkage disequilibrium methods for locating genes influencing quantitative traits in humans

Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

Can infant lung function predict respiratory morbidity during the first year of life in preterm infants?

Compared with term-born infants, preterm infants have increased respiratory morbidity in the first year of life. We investigated whether lung function tests performed near term predict subsequent respiratory morbidity during the first year of life and compared this to standard clinical parameters in preterms.The prospective birth cohort included randomly selected preterm infants with and without bronchopulmonary dysplasia. Lung function (tidal breathing and multiple-breath washout) was measured at 44 weeks post-menstrual age during natural sleep. We assessed respiratory morbidity (wheeze, hospitalisation, inhalation and home oxygen therapy) after 1 year using a standardised questionnaire. We first assessed the association between lung function and subsequent respiratory morbidity. Secondly, we compared the predictive power of standard clinical predictors with and without lung function data.In 166 preterm infants, tidal volume, time to peak tidal expiratory flow/expiratory time ratio and respiratory rate were significantly associated with subsequent wheeze. In comparison with standard clinical predictors, lung function did not improve the prediction of later respiratory morbidity in an individual child.Although associated with later wheeze, noninvasive infant lung function shows large physiological variability and does not add to clinically relevant risk prediction for subsequent respiratory morbidity in an individual preterm.

Interhemispheric cerebral blood flow balance during recovery of motor hand function after ischemic stroke - a longitudinal MRI study using arterial spin labeling perfusion

BACKGROUND Unilateral ischemic stroke disrupts the well balanced interactions within bilateral cortical networks. Restitution of interhemispheric balance is thought to contribute to post-stroke recovery. Longitudinal measurements of cerebral blood flow (CBF) changes might act as surrogate marker for this process. OBJECTIVE To quantify longitudinal CBF changes using arterial spin labeling MRI (ASL) and interhemispheric balance within the cortical sensorimotor network and to assess their relationship with motor hand function recovery. METHODS Longitudinal CBF data were acquired in 23 patients at 3 and 9 months after cortical sensorimotor stroke and in 20 healthy controls using pulsed ASL. Recovery of grip force and manual dexterity was assessed with tasks requiring power and precision grips. Voxel-based analysis was performed to identify areas of significant CBF change. Region-of-interest analyses were used to quantify the interhemispheric balance across nodes of the cortical sensorimotor network. RESULTS Dexterity was more affected, and recovered at a slower pace than grip force. In patients with successful recovery of dexterous hand function, CBF decreased over time in the contralesional supplementary motor area, paralimbic anterior cingulate cortex and superior precuneus, and interhemispheric balance returned to healthy control levels. In contrast, patients with poor recovery presented with sustained hypoperfusion in the sensorimotor cortices encompassing the ischemic tissue, and CBF remained lateralized to the contralesional hemisphere. CONCLUSIONS Sustained perfusion imbalance within the cortical sensorimotor network, as measured with task-unrelated ASL, is associated with poor recovery of dexterous hand function after stroke. CBF at rest might be used to monitor recovery and gain prognostic information.

Relation between Excitation Power Density and Er3+ Doping Yielding the Highest Absolute Upconversion Quantum Yield

The upconversion quantum yield (UCQY) is one of the most significant parameters for upconverter materials. A high UCQY is essential for a succesful integration of upconversion in many applications, such as harvesting of the solar radiation. However, little is known about which doping level of the rare-earth ions yields the highest UCQY in the different host lattices and what are the underlying causes. Here, we investigate which Er3+ doping yields the highest UCQY in the host lattices β-NaYF4 and Gd2O2S under 4I15/2 → 4I13/2 excitation. We show for both host lattices that the optimum Er3+ doping is not fixed and it actually decreases as the irradiance of the excitation increases. To find the optimum Er3+ doping for a given irradiance, we determined the peak position of the internal UCQY as a function of the average Er−Er distance. For this purpose, we used a fit on experimental data, where the average Er−Er distance was calculated from the Er3+ doping of the upconverter samples and the lattice parameters of the host materials. We observe optimum average Er−Er distances for the host lattices β-NaYF4 and Gd2O2S with differences <14% at the same irradiance levels, whereas the optimum Er3+ doping are around 2× higher for β-NaYF4 than for Gd2O2S. Estimations by extrapolation to higher irradiances indicate that the optimum average Er−Er distance converges to values around 0.88 and 0.83 nm for β-NaYF4 and Gd2O2S, respectively. Our findings point to a fundamental relationship and focusing on the average distance between the active rare-earth ions might be a very efficient way to optimize the doping of rare-earth ions with regard to the highest achievable UCQY.

Minimized extracorporeal circulation does not impair cognitive brain function after coronary artery bypass grafting

OBJECTIVES Objective evaluation of the impact of minimized extracorporeal circulation (MECC) on perioperative cognitive brain function in coronary artery bypass grafting (CABG) by electroencephalogram P300 wave event-related potentials and number connection test (NCT) as metrics of cognitive function. METHODS Cognitive brain function was assessed in 31 patients in 2013 with a mean age of 65 years [standard deviation (SD) 10] undergoing CABG by the use of MECC with P300 auditory evoked potentials (peak latencies in milliseconds) directly prior to intervention, 7 days after and 3 months later. Number connection test, serving as method of control, was performed simultaneously in all patients. RESULTS Seven days following CABG, cognitive P300 evoked potentials were comparable with preoperative baseline values [vertex (Cz) 376 (SD 11) ms vs 378 (18) ms, P = 0.39; frontal (Fz) 377 (11) vs 379 (21) ms, P = 0.53]. Cognitive brain function at 3 months was compared with baseline values [(Cz) 376 (11) ms vs 371 (14 ms) P = 0.09; (Fz) 377 (11) ms vs 371 (15) ms, P = 0.04]. Between the first postoperative measurement and 3 months later, significant improvement was observed [(Cz) 378 (18) ms vs 371 (14) ms, P = 0.03; (Fz) 379 (21) vs 371 (15) ms, P = 0.02]. Similar clearly corresponding patterns could be obtained via the number connection test. Results could be confirmed in repeated measures analysis of variance for Cz (P = 0.05) and (Fz) results (P = 0.04). CONCLUSIONS MECC does not adversely affect cognitive brain function after CABG. Additionally, these patients experience a substantial significant cognitive improvement after 3 months, evidentiary proving that the concept of MECC ensures safety and outcome in terms of brain function.