Diagnostic accuracy of the EMG parameters associated with anterior knee pain in the diagnosis of patellofemoral pain syndrome

Objective To assess the diagnostic accuracy of the surface electromyography (sEMG) parameters associated with referred anterior knee pain in diagnosing patellofemoral pain syndrome (PFPS). Design Sensitivity and specificity analysis. Setting Physical rehabilitation center and laboratory of biomechanics and motor control. Participants Pain-free subjects (n=29) and participants with PFPS (n=22) selected by convenience. Interventions Not applicable. Main Outcome Measure The diagnostic accuracy was calculated for sEMG parameters’ reliability, precision, and ability to differentiate participants with and without PFPS. The selected sEMG parameter associated with anterior knee pain was considered as an index test and was compared with the reference standard for the diagnosis of PFPS. Intraclass correlation coefficient, SEM, independent t tests, sensitivity, specificity, negative and positive likelihood ratios, and negative and positive predictive values were used for the statistical analysis. Results The medium-frequency band (B2) parameter was reliable (intraclass correlation coefficient=.80–.90), precise (SEM=2.71–3.87 normalized unit), and able to differentiate participants with and without PFPS (P<.05). The association of B2 with anterior knee pain showed positive diagnostic accuracy values (specificity, .87; sensitivity, .70; negative likelihood ratio, .33; positive likelihood ratio, 5.63; negative predictive value, .72; and positive predictive value, .86). Conclusions The results provide evidence to support the use of EMG signals (B2 – frequency band of 45–96Hz) of the vastus lateralis and vastus medialis muscles with referred anterior knee pain in the diagnosis of PFPS.

Feasibility of solar heating systems composed of recyclable packaging for low-income rural communities

Solar heaters are an appropriate technology in tropical and sub-tropical climates to heat bath water by solar energy. Low-cost solar heaters meet the demand of low-income rural communities which currently do not have access to this technology. Current research analyzes the economic viability of solar heaters, built with recyclable materials, to reduce electric energy bill. A solar heating system was built consisting of recyclable materials in accordance with the manuals provided by the Secretariat of Environment of the state of Paraná (SEMA). Duration of use of electric showers by families of rural properties was determined to calculate expenses and billing of electricity. Simulation and material costs showed that the system was feasible. Commercial solar heaters could be replaced at a cost of R$ 22.61 per month during 13 months.

The Effects of High Pressure Processing on Peanut Sauce Inoculated with Salmonella

Recent Salmonella outbreaks have prompted the need for new processing options for peanut products. Traditional heating kill-steps have shown to be ineffective in lipid-rich matrices such as peanut products. High pressure processing is one such option for peanut sauce because it has a high water activity, which has proved to be a large contributing factor in microbial lethality due to high pressure processing. Four different formulations of peanut sauce were inoculated with a five strain Salmonella cocktail and high pressure processed. Results indicate that increasing pressure or increasing hold time increases log10 reductions. The Weibull model was fitted to each kill curve, with b and n values significantly optimized for each curve (p-value < 0.05). Most curves had an n parameter value less than 1, indicating that the population had a dramatic initial reduction, but tailed off as time increased, leaving a small resistant population. ANOVA analysis of the b and n parameters show that there are more significant differences between b parameters than n parameters, meaning that most treatments showed similar tailing effect, but differed on the shape of the curve. Comparisons between peanut sauce formulations at the same pressure treatments indicate that increasing amount of organic peanut butter within the sauce formulation decreases log10 reductions. This could be due to a protective effect from the lipids in the peanut butter, or it may be due to other factors such as nutrient availability or water activity. Sauces pressurized at lower temperatures had decreased log10 reductions, indicating that cooler temperatures offered some protective effect. Log10 reductions exceeded 5 logs, indicating that high pressure processing may be a suitable option as a kill-step for Salmonella in industrial processing of peanut sauces. Future research should include high pressure processing on other peanut products with high water activities such as sauces and syrups as well as research to determine the effects of water activity and lipid composition with a food matrix such as peanut sauces.

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Reducing the parameter space for unparticle-inspired models using white dwarf masses

Based on astrophysical constraints derived from Chandrasekhar's mass limit for white dwarfs, we study the effects of the model on the parameters of unparticle-inspired gravity, on scales Lambda(U) > 1 TeV and d(U) approximate to 1.

Charcot foot: Skin temperature as a good clinical parameter for predicting disease outcome

Twenty-eight diabetics presenting with acute Charcot foot were immobilized and the temperature difference between limbs measured at each month. All patients had monthly follow-up visits for a year and the relapse rate was zero. We found that skin temperature is a good parameter to ensure safe immobilization withdrawal. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Transformer Operation at Deep Saturation: Model and Parameter Determination

This paper proposes a model that adequately describes the operation of the transformer at deep saturation, suitable for power-electronics applications, and a method for determining its parameters. Simulation and experimental results are presented to confirm the validity of the model and the method.

Linear parameter varying control design for rotating systems supported by journal bearings

Linear parameter varying (LPV) control is a model-based control technique that takes into account time-varying parameters of the plant. In the case of rotating systems supported by lubricated bearings, the dynamic characteristics of the bearings change in time as a function of the rotating speed. Hence, LPV control can tackle the problem of run-up and run-down operational conditions when dynamic characteristics of the rotating system change significantly in time due to the bearings and high vibration levels occur. In this work, the LPV control design for a flexible shaft supported by plain journal bearings is presented. The model used in the LPV control design is updated from unbalance response experimental results and dynamic coefficients for the entire range of rotating speeds are obtained by numerical optimization. Experimental implementation of the designed LPV control resulted in strong reduction of vibration amplitudes when crossing the critical speed, without affecting system behavior in sub- or supercritical speeds. (C) 2012 Elsevier Ltd. All rights reserved.

Coupling Between GABA(A)-R Ligand-Binding Activity and Membrane Organization in beta-Cyclodextrin-Treated Synaptosomal Membranes from Bovine Brain Cortex: New Insights from EPR Experiments

Correlations between GABA(A) receptor (GABA(A)-R) activity and molecular organization of synaptosomal membranes (SM) were studied along the protocol for cholesterol (Cho) extraction with beta-cyclodextrin (beta-CD). The mere pre-incubation (PI) at 37A degrees C accompanying the beta-CD treatment was an underlying source of perturbations increasing [H-3]-FNZ maximal binding (70%) and K (d) (38%), plus a stiffening of SMs' hydrocarbon core region. The latter was inferred from an increased compressibility modulus (K) of SM-derived Langmuir films, a blue-shifted DPH fluorescence emission spectrum and the hysteresis in DPH fluorescence anisotropy (A (DPH)) in SMs submitted to a heating-cooling cycle (4-37-4A degrees C) with A (DPH,heating) < A (DPH,cooling). Compared with PI samples, the beta-CD treatment reduced B (max) by 5% which correlated with a 45%-decrement in the relative Cho content of SM, a decrease in K and in the order parameter in the EPR spectrum of a lipid spin probe labeled at C5 (5-SASL), and significantly increased A (TMA-DPH). PI, but not beta-CD treatment, could affect the binding affinity. EPR spectra of 5-SASL complexes with beta-CD-, SM-partitioned, and free in solution showed that, contrary to what is usually assumed, beta-CD is not completely eliminated from the system through centrifugation washings. It was concluded that beta-CD treatment involves effects of at least three different types of events affecting membrane organization: (a) effect of PI on membrane annealing, (b) effect of residual beta-CD on SM organization, and (c) Cho depletion. Consequently, molecular stiffness increases within the membrane core and decreases near the polar head groups, leading to a net increase in GABA(A)-R density, relative to untreated samples.

Kinetics of thermal decomposition of niobium hydride

High-purity niobium powders can be obtained from the well-known hydride-dehydride (HDH) process. The aim of this work was the investigation of the structural phase transition of the niobium hydride to niobium metal as function of temperature, heating rate and time. The niobium powder used in this work was obtained by high-temperature hydriding of niobium machining chips followed by conventional ball milling and sieving. X-ray diffraction measurements were carried out in vacuum using a high-temperature chamber coupled to an X-ray diffractometer. During the dehydriding process, it is possible to follow the phase transition from niobium hydride to niobium metal starting at about 380 degrees C for a heating rate of 20 degrees C/min. The heating rate was found to be an important parameter, since complete dehydriding was obtained at 490 degrees C for a heating rate of 20 degrees C/min. The higher dehydriding rate was found at 500 degrees C. Results contribute to a better understanding of the kinetics of thermal decomposition of niobium hydride to niobium metal. (C) 2011 Elsevier Ltd. All rights reserved.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Exploration of the parameter space in an agent-based model of tuberculosis spread: emergence of drug resistance in developing vs developed countries

In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.

THE FIRST DETERMINATION OF THE VISCOSITY PARAMETER IN THE CIRCUMSTELLAR DISK OF A Be STAR

Be stars possess gaseous circumstellar decretion disks, which are well described using standard alpha-disk theory. The Be star 28 CMa recently underwent a long outburst followed by a long period of quiescence, during which the disk dissipated. Here we present the first time-dependent models of the dissipation of a viscous decretion disk. By modeling the rate of decline of the V-band excess, we determine that the viscosity parameter alpha = 1.0 +/- 0.2, corresponding to a mass injection rate (M) over dot = (3.5 +/- 1.3) x 10(-8) M-circle dot yr(-1). Such a large value of a suggests that the origin of the turbulent viscosity is an instability in the disk whose growth is limited by shock dissipation. The mass injection rate is more than an order of magnitude larger than the wind mass-loss rate inferred from UV observations, implying that the mass injection mechanism most likely is not the stellar wind, but some other mechanism.

Deviation from quark number scaling of the anisotropy parameter v(2) of pions, kaons, and protons in Au+Au collisions at root s(NN)=200 GeV

Measurements of the anisotropy parameter v(2) of identified hadrons (pions, kaons, and protons) as a function of centrality, transverse momentum p(T), and transverse kinetic energy KET at midrapidity (vertical bar eta vertical bar < 0.35) in Au + Au collisions at root s(N N) = 200 GeV are presented. Pions and protons are identified up to p(T) = 6 GeV/c, and kaons up to p(T) = 4 GeV/c, by combining information from time-of-flight and aerogel Cerenkov detectors in the PHENIX Experiment. The scaling of v(2) with the number of valence quarks (n(q)) has been studied in different centrality bins as a function of transverse momentum and transverse kinetic energy. A deviation from previously observed quark-number scaling is observed at large values of KET/n(q) in noncentral Au + Au collisions (20-60%), but this scaling remains valid in central collisions (0-10%).

Constraining the dark energy and smoothness parameter with type Ia supernovae and gamma-ray bursts

The existence of inhomogeneities in the observed Universe modifies the distance-redshift relations thereby affecting the results of cosmological tests in comparison to the ones derived assuming spatially uniform models. By modeling the inhomogeneities through a Zeldovich-Kantowski-Dyer-Roeder approach which is phenomenologically characterized by a smoothness parameter alpha, we rediscuss the constraints on the cosmic parameters based on type Ia supernovae (SNe Ia) and gamma-ray bursts (GRBs) data. The present analysis is restricted to a flat Lambda CDM model with the reasonable assumption that Lambda does not clump. A chi(2) analysis using 557 SNe Ia data from the Union2 compilation data (R. Amanullah et al., Astrophys. J. 716, 712 (2010).) constrains the pair of parameters (Omega(m), alpha) to Omega(m) = 0.27(-0.03)(+0.08) (2 sigma) and alpha >= 0.25. A similar analysis based only on 59 Hymnium GRBs (H. Wei, J. Cosmol. Astropart. Phys. 08 (2010) 020.) constrains the matter density parameter to be Omega(m) = 0.35(-0.24)(+0.62) (2 sigma) while all values for the smoothness parameter are allowed. By performing a joint analysis, it is found that Omega(m) = 0.27(-0.06)(+0.06) and alpha >= 0.52. As a general result, although considering that current GRB data alone cannot constrain the smoothness alpha parameter, our analysis provides an interesting cosmological probe for dark energy even in the presence of inhomogeneities.