Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI

Purpose: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted magnetic resonance imaging (DW-MRI) data and evaluates its performance. Methods: In May 2011, ten male volunteers (age range: 29 to 53 years, mean: 37 years) underwent DW-MRI of the upper abdomen on 1.5T and 3.0T magnetic resonance scanners. Regions of interest in the left and right liver lobe, pancreas, spleen, renal cortex, and renal medulla were delineated independently by two readers. DNNs were trained for IVIM model fitting using these data; results were compared to least-squares and Bayesian approaches to IVIM fitting. Intraclass Correlation Coefficients (ICC) were used to assess consistency of measurements between readers. Intersubject variability was evaluated using Coefficients of Variation (CV). The fitting error was calculated based on simulated data and the average fitting time of each method was recorded. Results: DNNs were trained successfully for IVIM parameter estimation. This approach was associated with high consistency between the two readers (ICCs between 50 and 97%), low intersubject variability of estimated parameter values (CVs between 9.2 and 28.4), and the lowest error when compared with least-squares and Bayesian approaches. Fitting by DNNs was several orders of magnitude quicker than the other methods but the networks may need to be re-trained for different acquisition protocols or imaged anatomical regions. Conclusion: DNNs are recommended for accurate and robust IVIM model fitting to DW-MRI data. Suitable software is available at (1)

Influence of coating on the thermal resistance of a Ni-Based superalloy

In this paper, the influence of M-CrAlY polycrystalline coating on the thermal fatigue behavior of a Nickel-base superalloy has been investigated. A special device using a rotating bending machine and two thermal sources has been used to perform thermo-mechanical tests. The two thermal sources have been set to obtain temperature variations between 750 and 1120 °C in the central part of the specimens, with a frequency of 0.1 Hz. The results showed a deleterious effect of the coating on the fatigue resistance. Numerical simulations have been carried out on SAMCEF to determine the thermo-mechanical field of the so-tested specimens. Calculated thermo-mechanical cycles of critical sites are associated with microstructure evolution and damage by cracking observed on the specimens. Damage mechanisms related to the presence of coating are discussed

Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

We express the mean and variance terms in a double exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the model, and whether they enter linearly or flexibly. When the variance term is null we obtain a generalized additive model, which becomes a generalized linear model if the predictors enter the mean linearly. The model is estimated using Markov chain Monte Carlo simulation and the methodology is illustrated using real and simulated data sets.Comment: 8 graphs 35 page

"Body-In-The-Loop": Optimizing Device Parameters Using Measures of Instantaneous Energetic Cost

This paper demonstrates methods for the online optimization of assistive robotic devices such as powered prostheses, orthoses and exoskeletons. Our algorithms estimate the value of a physiological objective in real-time (with a body “in-the-loop”) and use this information to identify optimal device parameters. To handle sensor data that are noisy and dynamically delayed, we rely on a combination of dynamic estimation and response surface identification. We evaluated three algorithms (Steady-State Cost Mapping, Instantaneous Cost Mapping, and Instantaneous Cost Gradient Search) with eight healthy human subjects. Steady-State Cost Mapping is an established technique that fits a cubic polynomial to averages of steady-state measures at different parameter settings. The optimal parameter value is determined from the polynomial fit. Using a continuous sweep over a range of parameters and taking into account measurement dynamics, Instantaneous Cost Mapping identifies a cubic polynomial more quickly. Instantaneous Cost Gradient Search uses a similar technique to iteratively approach the optimal parameter value using estimates of the local gradient. To evaluate these methods in a simple and repeatable way, we prescribed step frequency via a metronome and optimized this frequency to minimize metabolic energetic cost. This use of step frequency allows a comparison of our results to established techniques and enables others to replicate our methods. Our results show that all three methods achieve similar accuracy in estimating optimal step frequency. For all methods, the average error between the predicted minima and the subjects’ preferred step frequencies was less than 1% with a standard deviation between 4% and 5%. Using Instantaneous Cost Mapping, we were able to reduce subject walking-time from over an hour to less than 10 minutes. While, for a single parameter, the Instantaneous Cost Gradient Search is not much faster than Steady-State Cost Mapping, the Instantaneous Cost Gradient Search extends favorably to multi-dimensional parameter spaces

Detection of x-rays from galaxy groups associated with the gravitationally lensed systems PG 1115+080 and B1422+231

Gravitational lenses that produce multiple images of background quasars can be an invaluable cosmological tool. Deriving cosmological parameters, however, requires modeling the potential of the lens itself. It has been estimated that up to a quarter of lensing galaxies are associated with a group or cluster which perturbs the gravitational potential. Detection of X-ray emission from the group or cluster can be used to better model the lens. We report on the first detection in X-rays of the group associated with the lensing system PG 1115+080 and the first X-ray image of the group associated with the system B1422+231. We find a temperature and rest-frame luminosity of 0.8 +/- 0.1 keV and 7 +/- 2 x 10^{42} ergs/s for PG 1115+080 and 1.0 +infty/-0.3 keV and 8 +/- 3 x 10^{42} ergs/s for B1422+231. We compare the spatial and spectral characteristics of the X-ray emission to the properties of the group galaxies, to lens models, and to the general properties of groups at lower redshift.Comment: Accepted for publication in ApJ. 17 pages, 5 figures. Minor changes to tex

Response Surface Optimization of a Plastic Powder Processing Machine using Desirability Function Approach

Optimal performance and operational parameters of a plastic powder processing machine used for converting used PET bottles into powdered form was assessed in this study. The geometrical (operational) parameters investigated include: speed of hammermill shaft, number of blades on the hammermill, length of hammermill blade and intrinsic viscosity of the PET processed while grain size produced, throughput and conversion efficiency constitute the machine’s (performance) parameters. The interactions of these factors (operational parameters) and responses (performance parameters) were evaluated and estimated using a completely randomized Box-Behnken blocked design layout which comprises twenty seven (27) experimental runs. Desirability function approach was the optimization technique applied. Results revealed the optimal values of hammermill speed, number of blades, blade length and intrinsic viscosity as 1400 rpm, 4, 109.6 mm and 0.82798 respectively with responses of 89.71%, 1.9953 kg/min and 139.9998 for conversion efficiency, throughput and grain size respectively. These optimal operational parameters will make the machine economical to operate in terms of labour, time and energy requirement

New high-technology products for the treatment of haemophilia

This review will focus on new technologies in development that promise to lead to further advances in haemophilia therapeutics. There has been continued interest in the bioengineering of recombinant factor VIII (rFVIII) and factor IX (rFIX) with improved function to overcome some of the limitations in current treatment, the high costs of therapy and to increase availability to a broader world haemophilia population. Bioengineered forms of rFVIII, rFIX or alternative haemostatic molecules may ultimately have an impact on improving the efficacy of therapeutic strategies for the haemophilias by improving biosynthesis and secretion, functional activity, half-life and immunogenicity. Preventing and suppressing inhibitors to factor (F) VIII remain a challenge for both clinicians and scientists. Recent experiments have shown that it is possible to obtain anti-idiotypic antibodies with a number of desirable properties: (i) strong binding avidity to FVIII inhibitors; (ii) neutralization of inhibitory activity both in vitro and in vivo ; (iii) cross-reactivity with antibodies from unrelated patients, and (iv) no interference with FVIII function. An alternative, although complementary approach, makes use of peptides derived from filamentous-phage random libraries. Mimotopes of FVIII can be obtained, which bind to the paratope of inhibitory activity and neutralize their activity both in vitro and in vivo . In this paper, we review advanced genetic strategies for haemophilia therapy. Until recently the traditional concept for gene transfer of inherited and acquired haematological diseases has been focused on how best to obtain stable insertion of a cDNA into a target-cell genome, allowing expression of a therapeutic protein. However, as gene-transfer vector systems continue to improve, the requirement for regulated gene transcription and hence regulated protein expression will become more critical. Inappropriate protein expression levels or expression of transferred cDNAs in non-intended cell types or tissues may lead to target-cell toxicity or activation of unwanted host immune responses. Regulated protein expression requires that the transferred gene be transferred with its own regulatory cassette that allows for gene transcription and translation approaching that of the normal gene in its endogenous context. New molecular techniques, in particular the use of RNA molecules, now allow for transcription of corrective genes that mimic the normal state.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75577/1/j.1365-2516.2004.00996.x.pd