Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure for regression is the mean square error. This paper looks into the possibility of improving the performance of neural networks by selecting or defining error functions that are tailor-made for a specific objective. A neural network trained to simulate tension forces in an anchor chain on a floating offshore platform is designed and tested. The purpose of setting up the network is to reduce calculation time in a fatigue life analysis. Therefore, the networks trained on different error functions are compared with respect to accuracy of rain flow counts of stress cycles over a number of time series simulations. It is shown that adjusting the error function to perform significantly better on a specific problem is possible. On the other hand. it is also shown that weighted error functions actually can impair the performance of an ANN

Determination of PCR efficiency in chelex-100 purified clinical samples and comparison of real-time quantitative PCR and conventional PCR for detection of Chlamydia pneumoniae

BACKGROUND: Chlamydia pneumoniae infection has been detected by serological methods, but PCR is gaining more interest. A number of different PCR assays have been developed and some are used in combination with serology for diagnosis. Real-time PCR could be an attractive new PCR method; therefore it must be evaluated and compared to conventional PCR methods. RESULTS: We compared the performance of a newly developed real-time PCR with a conventional PCR method for detection of C. pneumoniae. The PCR methods were tested on reference samples containing C. pneumoniae DNA and on 136 nasopharyngeal samples from patients with a chronic cough. We found the same detection limit for the two methods and that clinical performance was equal for the real-time PCR and for the conventional PCR method, although only three samples tested positive. To investigate whether the low prevalence of C. pneumoniae among patients with a chronic cough was caused by suboptimal PCR efficiency in the samples, PCR efficiency was determined based on the real-time PCR. Seventeen of twenty randomly selected clinical samples had a similar PCR efficiency to samples containing pure genomic C. pneumoniae DNA. CONCLUSIONS: These results indicate that the performance of real-time PCR is comparable to that of conventional PCR, but that needs to be confirmed further. Real-time PCR can be used to investigate the PCR efficiency which gives a rough estimate of how well the real-time PCR assay works in a specific sample type. Suboptimal PCR efficiency of PCR is not a likely explanation for the low positivity rate of C. pneumoniae in patients with a chronic cough

Mass-Spectrometry Based Proteome Comparison of Extracellular Vesicle Isolation Methods:Comparison of ME-kit, Size-Exclusion Chromatography, and High-Speed Centrifugation

Extracellular vesicles (EVs) are small membrane-enclosed particles released by cells under various conditions specific to cells’ biological states. Hence, mass-spectrometry (MS) based proteome analysis of EVs in plasma has gained much attention as a method to discover novel protein biomarkers. MS analysis of EVs in plasma is challenging and EV isolation is usually necessary. Therefore, we compared differences in abundance, subtypes, and contamination for EVs isolated by high-speed centrifugation, size exclusion chromatography (SEC), and peptide-affinity precipitation (PAP/ME kit) for subsequent MS-based proteome analysis. Successful EV isolation was evaluated by nanoparticle-tracking analysis, immunoblotting, and transmission electron microscopy, while EV abundance, EV subtypes, and contamination was evaluated by label-free tandem MS. High-speed centrifugation and SEC isolates showed high EV abundance at the expense of contamination by non-EV proteins and lipoproteins, respectively. These two methods also resulted in EVs of a similar type, however, with smaller EVs in SEC isolates. PAP isolates had a relatively low EV abundance and high contamination. We consider high-speed centrifugation and SEC suitable as EV isolation for MS biomarker studies, where the choice between the two should depend on the scientific questions and whether the focus is on larger or smaller EVs or a combination of both

Model for the alpha and beta shear-mechanical properties of supercooled liquids and its comparison to squalane data

This paper presents data for supercooled squalane's frequency-dependent shear modulus covering frequencies from 10 mHz to 30 kHz and temperatures from 168 K to 190 K; measurements are also reported for the glass phase down to 146 K. The data reveal a strong mechanical beta process. A model is proposed for the shear response of supercooled liquids. The model is an electrical equivalent-circuit characterized by additivity of the dynamic shear compliances of the alpha and beta processes. The nontrivial parts of the alpha and beta processes are represented by a "Cole-Cole retardation element", resulting in the Cole-Cole compliance function well-known from dielectrics. The model, which assumes that the high-frequency decay of the alpha shear compliance loss varies with angular frequency as $\omega^{-1/2}$, has seven parameters. Assuming time-temperature superposition for the alpha and the beta processes separately, the number of parameters varying with temperature is reduced to four. From the temperature dependence of the best-fit model parameters the following conclusions are drawn: 1) the alpha relaxation time conforms to the shoving model; 2) the beta relaxation loss-peak frequency is almost temperature independent; 3) the alpha compliance magnitude, which in the model equals the inverse of the instantaneous shear modulus, is only weakly temperature dependent; 4) the beta compliance magnitude decreases by a factor of three upon cooling in the temperature range studied. The final part of the paper briefly presents measurements of the dynamic adiabatic bulk modulus covering frequencies from 10 mHz to 10 kHz in the temperature range 172 K to 200 K. The data are qualitatively similar to the shear data by having a significant beta process. A single-order-parameter framework is suggested to rationalize these similarities