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Results for “parameter optimization”

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PubMed2002

Optimization of a human papillomavirus-specific enzyme-linked immunosorbent assay.

A strategy was developed for the control, standardization, and critical evaluation of an enzyme-linked immunosorbent assay (ELISA) for the detection of human papillomavirus-specific immunoglobulin G in human sera. Control human sera, polyclonal animal sera, and monoclonal antibodies were used to establish optimal assay parameters, including antigen coating, serum dilutions, and criteria for daily reproducibility, monitoring, and rejection of assays. Three evaluation techniques were used in parallel to define an optimal cutoff absorbance value that yields greater than 93% sensitivity and 98.5% specificity in the assay's ability to discriminate positive and negative control sera. This strategy provides an optimal method by which to determine cutoff absorbance values for ELISA.

Animals↗

PubMed1984

A computer study of the left ventricular performance based on fiber structure, sarcomere dynamics, and transmural electrical propagation velocity.

A model of the left ventricle which combines a spheroidal geometry with a spatial fiber angle distribution is presented. The mechanics of each muscle fiber is described by its passive stress-strain relationship, active stress-strain relationship, and an activation function (half a sinusoid) which represents the time-dependent degree of activation of the fiber. A stress-strain rate relationship which characterizes the muscle fibers is used to calculate the mechanics of left ventricular contraction during ejection. Furthermore, a radial electrical signal propagation from the endocardium to the epicardium is used here as a first approximation to the actual depolarization sequence. The model is used to describe the process of contraction throughout the systole. The different calculated parameters and indices of left ventricular function are presented and discussed for different preloading, afterloading and contractility conditions. The maximum elastance is found to be an optimal macroscale parameter of contractility, as it is completely preload and afterload independent, and is a good reflection of the active microscale sarcomere stress-strain relationship.

Computers↗

PubMed2002

A neural network approach to treatment optimization.

Typical medical diagnosis applications of neural networks for prediction and classification require training data (observations) that include the "correct" category for a number of patient records. In this paper, we borrow a technique from control systems applications of neural networks. Optimal control parameters of a system are typically not known. Instead, we only know the effect on a remote system. The correct control action drives the remote system optimally. The learning technique requires two networks: one to model the system to be controlled (here, the patient), and one to optimize the treatment (here, the treating physician). The concept was tested with artificially generated noisy data, and gives promising results.

Drug Therapy, Computer-Assisted↗

PubMed1982

Partial optimization of electrochemical-etching parameters for highly sensitive CR-39 fast neutron dosimeters.

Voltage gradient and frequency were studied for their influence on the electrochemical etching of CR-39 plastic irradiated with fission spectrum, fast neutrons. A power supply having outputs of up to 1.5 kV (rms) and 5 kHz was used. Differential voltage measurements under non-etching conditions indicated that the optimal values in electrochemical etching with this power supply would be 20 kV/cm and 1.3 kHz. That these parameters produced a maximum sensitivity was verified in subsequent electrochemical etching experiments for a standard 4 hr in 9N KOH with foils that were both unirradiated and irradiated. The introduction of a proton irradiator cover and a conventional etching step prior to the electrochemical etching, increased the sensitivity to neutrons (approximately 30-fold) and decreased the background track density to 4.4 +/- 0.6 tracks/cm2. The corresponding sensitivity was then 1.3 tracks/cm2/mrem with a minimum level of detectability (3 sigma) of 1.4 mrem.

Electrochemistry↗

PubMed2007

Addition of antioxidant of bamboo leaves (AOB) effectively reduces acrylamide formation in potato crisps and French fries.

The present study was to demonstrate the efficiency of antioxidant of bamboo leaves (AOB) on the reduction of acrylamide during thermal processing and to summarize the optimal level of AOB applied in potato-based products. Potato crisps and French fries were immersed into different contents of AOB solution, and the frying processing parameters were optimized. The acrylamide content was determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The sensory evaluation was performed in double blind manner. Our results showed that nearly 74.1% and 76.1% of acrylamide in potato crisps and French fries was reduced when the AOB addition ratio was 0.1% and 0.01% (w/w), respectively. The maximum inhibitory rate was achieved when the immersion time was designed as 60 s. Sensory evaluation results showed that the crispness and flavor of potato crisps and French fries processed by AOB solution had no significant difference compared to normal potato matrixes (P > 0.05) when the AOB addition ratio was <0.5% (w/w). These results suggested that AOB could significantly reduce acrylamide formation in potato-based foods and keep original crispness and flavor of potato matrixes. This study could be regarded as a pioneer contribution on the reduction of acrylamide in various foods by natural antioxidants.

Acrylamide↗

PubMedDate not supplied

Parametrized x-ray absorption in diagnostic radiology from Monte Carlo calculations: implications for x-ray detector design.

The integral dose to the patient and image signal to noise ratio (SNR) are inexorably coupled in x-ray-based diagnostic imaging. Advancements and optimal design of imaging devices need to consider the SNR as well as patient dose. The figure of merit, FOM = (SNR)2/(integral dose), is a useful parameter in optimizing detector designs because it is independent of input exposure, and therefore eliminates exposure as a design consideration. Although numerical calculation of the SNR is relatively straightforward in most cases, the integral dose calculation is made complex due to its scatter component's high dependency on both x-ray energy and patient thickness. Monte Carlo calculations over a range of monoenergetic x-ray energies were used to calculate total energy absorption, and the results are parametrized using polynomial expressions. The results are shown to be applicable to any arbitrary polyenergetic spectrum. An example using the above FOM is given to illustrate the utility of the parametrized results. The parametrized results may prove useful in the computer simulations of x-ray detector systems where the above FOM is utilized.

Absorption↗

PubMed2005

Direct reconstruction of kinetic parameter images from dynamic PET data.

Our goal in this paper is the estimation of kinetic model parameters for each voxel corresponding to a dense three-dimensional (3-D) positron emission tomography (PET) image. Typically, the activity images are first reconstructed from PET sinogram frames at each measurement time, and then the kinetic parameters are estimated by fitting a model to the reconstructed time-activity response of each voxel. However, this "indirect" approach to kinetic parameter estimation tends to reduce signal-to-noise ratio (SNR) because of the requirement that the sinogram data be divided into individual time frames. In 1985, Carson and Lange proposed, but did not implement, a method based on the expectation-maximization (EM) algorithm for direct parametric reconstruction. The approach is "direct" because it estimates the optimal kinetic parameters directly from the sinogram data, without an intermediate reconstruction step. However, direct voxel-wise parametric reconstruction remained a challenge due to the unsolved complexities of inversion and spatial regularization. In this paper, we demonstrate and evaluate a new and efficient method for direct voxel-wise reconstruction of kinetic parameter images using all frames of the PET data. The direct parametric image reconstruction is formulated in a Bayesian framework, and uses the parametric iterative coordinate descent (PICD) algorithm to solve the resulting optimization problem. The PICD algorithm is computationally efficient and is implemented with spatial regularization in the domain of the physiologically relevant parameters. Our experimental simulations of a rat head imaged in a working small animal scanner indicate that direct parametric reconstruction can substantially reduce root-mean-squared error (RMSE) in the estimation of kinetic parameters, as compared to indirect methods, without appreciably increasing computation.

Algorithms↗

PubMed2006

Noninvasive assessment of tumor vasculature response to radiation-mediated, vasculature-targeted therapy using quantified power Doppler sonography: implications for improvement of therapy schedules.

OBJECTIVE: Stereotactic radiotherapy (ablative radiation) is a modality that holds considerable promise for effective treatment of intracranial and extracranial malignancies. Although tumor vasculature is relatively resistant to small fractionated doses of ionizing radiation, large ablative doses of ionizing radiation lead to effective demise of the tumor vasculature. The purpose of this study was (1) to noninvasively monitor and compare tumor physiologic parameters in response to ablative radiation treatments and (2) to use these noninvasive parameters to optimize the schedule of administration of radiation therapy. METHODS: Lewis lung carcinoma tumors were implanted into C57BL/6 mice and treated with ablative radiation. The kinetics of change in physiologic parameters of a response to single-dose 20-Gy treatments was measured. Parameters studied included tumor blood flow, apoptosis, and proliferation rates. Serial tumor sections were stained to correlate noninvasive Doppler assessment of tumor blood flow with microvasculature histologic findings. RESULTS: A single administration of 20 Gy led to an incomplete tumor vascular response, with subsequent recovery of tumor blood flow within 4 days after treatment. Sustained reduction of tumor blood flow by administering the successive ablative radiation treatment before tumor blood flow recovery led to a 3-fold tumor growth delay. The difference in tumor volumes at each measurement time point (every 2 days) was statistically significant (P=.016). CONCLUSIONS: This study suggests a rational design of schedule optimization for radiation-mediated, vasculature-directed treatments guided by noninvasive assessment of tumor blood flow levels to ultimately improve the tumor response.

Animals↗

PubMed2005

Optimization of the coupling of high-temperature liquid chromatography and flame ionization detection application to the separations of alcohols.

The feasibility of coupling high-temperature liquid chromatography (HTLC) to flame ionization detection (FID) has been studied. FID parameter values (hydrogen flow-rate, air flow-rate and FID temperature), typically set in gas chromatography are rarely suitable for liquid chromatography. Best values depend obviously on the water flow rate which is defined depending on both column temperature and column internal diameter. The FID parameters were optimized according to the water flow-rate by means of an experimental design. The potential of the method is shown with some alcohol separations and the value of increasing column temperature while reducing the column diameter is highlighted.

Alcohols↗

PubMed2005

Approach to abdominal imaging at 1.5 Tesla and optimization at 3 Tesla.

This article reviews fundamental principles and sequence techniques that have been used successfully for imaging diseases of the abdomen and pelvis at 1.5 Tesla. This article also introduces concepts and the specific alteration of sequence parameters for optimization of abdominal-pelvic imaging at 3 Tesla.

Abdomen↗

PubMed2004

Analysis and application of ADM1 for anaerobic methane production.

An anaerobic model for the serum bottle test was developed and analyzed with sensitivities of stoichiometric and kinetic parameters to the components in order to establish a basis for appropriate application of the model. Anaerobic glucose degradation in a serum bottle was selected as an example. The anaerobic model was developed based on the anaerobic digestion model no. 1 (ADM1), which had five processes with 17 kinetic and stoichiometric parameters. Sensitivity analysis showed that the yield of product on the substrate (f) has high sensitivities to model components, and that the methane concentration was the most sensitive component. Important parameters including yield of product on the substrate (f), yield of biomass on the substrate (Y), and half-saturation values (K) were estimated using genetic algorithms, which optimized the parameters with experimental results. The Monod maximum specific uptake rate (k) was, however, so strongly associated with the concentration of biomass, that values could not be estimated individually. Simulation with estimated parameters showed good agreement with experimental results in the case of methane production. However, there were some differences in acetate and propionate concentrations.

Algorithms↗

PubMed2005

3D multi-scale vessel enhancement filtering based on curvature measurements: application to time-of-flight MRA.

In this paper we evaluate the use of voxel intensity curvature measurements to enhance vessels in 3D MRA images. We compare a multi-scale discrete kernel filter (MaxCurve) to the Hessian matrix based filter proposed by Frangi and co-workers. The MaxCurve filter is based on the maximum difference between the negative curvature computed along orthogonal lines defined by a 3x3x3 kernel. Filter performance is assessed using measures of vessel and background separation (contrast and the area under the ROC curve). Filter parameters are optimized using a training set of four typical time-of-flight MRA images and tested on a separate set of ten MRA images with the same acquisition parameters. The filters tended to provide good MIP image contrast enhancement. The filters are applied to MRA images acquired with different parameters and field strengths indicating potential usefulness for a variety of images. Overall the discrete kernel and Hessian matrix filter performed quite similarly.

Algorithms↗

PubMed2005

Composite adaptive control with locally weighted statistical learning.

This paper introduces a probably stable learning adaptive control framework with statistical learning. The proposed algorithm employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the proposed learning adaptive control algorithm uses both the tracking error and the estimation error to update the parameters. We first discuss statistical learning of nonlinear functions, and motivate our choice of the locally weighted learning framework. Second, we begin with a class of first order SISO systems for theoretical development of our learning adaptive control framework, and present a stability proof including a parameter projection method that is needed to avoid potential singularities during adaptation. Then, we generalize our adaptive controller to higher order SISO systems, and discuss further extension to MIMO problems. Finally, we evaluate our theoretical control framework in numerical simulations to illustrate the effectiveness of the proposed learning adaptive controller for rapid convergence and high accuracy of control.

Algorithms↗

PubMed2005

Reconstruction of stochastic nonlinear dynamical models from trajectory measurements.

An algorithm is presented for reconstructing stochastic nonlinear dynamical models from noisy time-series data. The approach is analytical; consequently, the resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. The strengths of the algorithm are illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. The efficiency and accuracy of the algorithm are further demonstrated by inferring a model for a system of five globally and locally coupled noisy oscillators.

Journal Article↗

PubMed2002

Potential of feature selection methods in heart rate variability analysis for the classification of different cardiovascular diseases.

In this study heart rate variability (HRV) analysis was applied to characterize patients suffering from coronary heart disease (CHD), dilated cardiomyopathy (DCM) and patients who had survived an acute myocardial infarction (MI). On the basis of several HRV parameters, an optimal discrimination between the different kinds of cardiovascular diseases and between the diseases and healthy controls (HC) was derived by feature selection and linear classification. For each task a small favourable subset of a set of 33 potentially interesting HRV measures was selected with the intention of improving the diagnostic value and facilitating the physiological interpretation of HRV analysis. Time- and frequency-domain parameters as well as parameters from non-linear dynamics were included in the analysis. With the expectation that different diseases are characterized by different phenomena, feature selection was applied for each task separately. Using the features optimal for one task to another task can reveal a loss in performance, but it turned out that one specific parameter set (set1: normalized low frequency LF/P and a non-linear variability measure WPSUM13) was applicable for all tasks, where diseased and healthy subjects have to be distinguished, without significant reduction in performance. This set seems to be a general marker for pathologic changes in HRV and might be used for early detection of heart diseases. The classification between different heart diseases requires another parameter set (set2: meanNN and sdaNN, reflecting the steady state behaviour of the heart rate and long and short term SEAR describing the spectral composition). However, the use of set1 for the separation of different kinds of diseases, where set2 is appropriate, led to significant reduction in performance and vice versa. This observation may be important for future developments of HRV measures especially suitable for the assessment of disease severity.

Cardiovascular Diseases↗

PubMedDate not supplied

Simulation/optimization modeling for robust pumping strategy design.

A new simulation/optimization modeling approach is presented for addressing uncertain knowledge of aquifer parameters. The Robustness Enhancing Optimizer (REO) couples genetic algorithm and tabu search as optimizers and incorporates aquifer parameter sensitivity analysis to guide multiple-realization optimization. The REO maximizes strategy robustness for a pumping strategy that is optimal for a primary objective function (OF), such as cost. The more robust a strategy, the more likely it is to achieve management goals in the field, even if the physical system differs from the model. The REO is applied to trinitrotoluene and Royal Demolition Explosive plumes at Umatilla Chemical Depot in Oregon to develop robust least cost strategies. The REO efficiently develops robust pumping strategies while maintaining the optimal value of the primary OF-differing from the common situation in which a primary OF value degrades as strategy reliability increases. The REO is especially valuable where data to develop realistic probability density functions (PDFs) or statistically derived realizations are unavailable. Because they require much less field data, REO-developed strategies might not achieve as high a mathematical reliability as strategies developed using many realizations based upon real aquifer parameter PDFs. REO-developed strategies might or might not yield a better OF value in the field.

Computer Simulation↗

PubMed2005

Raman spectrum, conformational stability, barriers to internal rotations and DFT calculations of 1,1,1-trifluoro-propane-2-thione with double-internal-symmetric rotor.

The Raman spectrum (3500-100 cm-1) of 1,1,1-trifluoro-propane-2-thione (TFPT), CF3C(S)CH3 of the solid phase has been recorded. The internal rotation of CH3 and/or CF3 moieties around CC bonds in TFPT allow five hypothetical conformers (Cs and C1 point groups). Aided by quantum chemical (QC) calculations, the Cc conformer is the only stable form (CF3 and CH3 groups are eclipsing the CS bond) which contains a planar FCC(S)CH backbone and possess intramolecular hydrogen sulfur interactions. However, other conformations (with the orientation of sulfur atom being trans to either hydrogen or fluorine atom) are either transition states or not fully converged geometry with "gauche" orientation. Moreover, the calculation were carried out at the level of Becke three Lee-Yan-Parr (B3LYP) parameters up to 6-311++G(d,p) basis sets. The torsional barriers are adequately described by a three-fold potential, V3 which have been determined utilizing the optimized structural parameters from the B3LYP/6-31G(d) basis set along with potential surface scan. Barriers of 1.28 kcal/mol (448 cm-1) and 1.94 kcal/mol (678 cm-1) were calculated for CH3 and CF3 symmetric rotors, respectively. Complete vibrational assignments have been reported for the stable Cc isomer which is supported by normal coordinate analysis and potential energy distributions (PEDs) for all fundamentals. Moreover, equilibrium geometries, vibrational frequencies are compared to the corresponding experimental values of acetone, 1,1,1-trifluoroacetone (TFA), hexafluoroacetone (HFA) and other molecules having the CF3 moiety whenever appropriate.

Fluorine↗

PubMed1999

The use of collagen-GAG membranes in reconstructive surgery.

Porous collagen-glycosaminoglycan (PCG) membranes with a porous silicone elastomer coating have been useful as a scaffold for dermal replacement in burn victims. Critical physicochemical parameters of these membranes include pore size, cross-link density, the percentage of glycosaminoglycan, and the degree of banding of the collagen. These factors govern the immunobiological response. Optimizing these parameters can reduce inflammation, scarring, and contraction of wounds grafted with PCG membranes. PCG membranes are currently commercially manufactured (Integra, Integra Life Sciences, New Jersey) and available for clinical use. Because clinical outcomes have improved using these membranes for burn wound coverage, other skin reconstruction problems including scar resurfacing, keloids, treatment of donor sites, and treatment of chronic wounds can be considered as potential applications. This manuscript illustrates our early experience using Integra as a CG membrane for dermal replacement in reconstructive surgery. Our results indicate that CG membranes can lead to improved compliance and appearance compared to a meshed graft and may be sequentially placed in multiple layers to correct contour deformities. Also, in one case, we observed that, if placed on a wound bed with embedded skin epithelial cells, the PCG promotes epithelialization through the PCG matrix. The use of this material results in a supple integument with many similarities to normal skin.

Adult↗