Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

Differences in the activity of the muscles in the forearm of individuals with a congenital absence of the hand

The spectral content of the myoelectric signals from the muscles of the remnant forearms of three persons with congenital absences (CA) of their forearms was compared with signals from their intact contra-lateral limbs, similar muscles in three persons with acquired losses (AL) and seven persons without absences [no loss (NL)]. The observed bandwidth for the CA subjects was broader with peak energy between 200 and 300 Hz. While the signals from the contra-lateral limbs and the AL and NL subjects was in the 100-150 Hz range: The mean skew of the signals from the AL subjects was 46.3 +/- 6.7 and those with NL of 45.4 +/- 8.7, while the signals from those with CAs had a skew of 11.0 +/- 11. The structure of the muscles of one CA subject was observed ultrasonically. The muscle showed greater disruption than normally developed muscles. It is speculated that the myographic signal reflects the structure of the muscle. which has developed in a more disorganized manner as a result of the muscle not being stretched by other muscles across the missing distal joint, even in the muscles that are used regularly to control arm prostheses.

Development and experimental identification of a biomechanical model of the trunk for functional electrical stimulation control in paraplegia

Objectives. Theoretic modeling and experimental studies suggest that functional electrical stimulation (FES) can improve trunk balance in spinal cord injured subjects. This can have a positive impact on daily life, increasing the volume of bimanual workspace, improving sitting posture, and wheelchair propulsion. A closed loop controller for the stimulation is desirable, as it can potentially decrease muscle fatigue and offer better rejection to disturbances. This paper proposes a biomechanical model of the human trunk, and a procedure for its identification, to be used for the future development of FES controllers. The advantage over previous models resides in the simplicity of the solution proposed, which makes it possible to identify the model just before a stimulation session ( taking into account the variability of the muscle response to the FES). Materials and Methods. The structure of the model is based on previous research on FES and muscle physiology. Some details could not be inferred from previous studies, and were determined from experimental data. Experiments with a paraplegic volunteer were conducted in order to measure the moments exerted by the trunk-passive tissues and artificially stimulated muscles. Data for model identification and validation also were collected. Results. Using the proposed structure and identification procedure, the model could adequately reproduce the moments exerted during the experiments. The study reveals that the stimulated trunk extensors can exert maximal moment when the trunk is in the upright position. In contrast, previous studies show that able-bodied subjects can exert maximal trunk extension when flexed forward. Conclusions. The proposed model and identification procedure are a successful first step toward the development of a model-based controller for trunk FES. The model also gives information on the trunk in unique conditions, normally not observable in able-bodied subjects (ie, subject only to extensor muscles contraction).

Bayesian model averaging and identification of structural breaks in time series

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.

Identification of linear systems in the presence of piecewise polynomial disturbances

The paper proposes a method of performing system identification of a linear system in the presence of bounded disturbances. The disturbances may be piecewise parabolic or periodic functions. The method is demonstrated effectively on two example systems with a range of disturbances.

Early identification of stimulant treatment responders, partial responders and non-responders using objective measures in children and adolescents with hyperkinetic disorder

Background: The aim of this study was to evaluate stimulant medication response following a single dose of methylphenidate (MPH) in children and young people with hyperkinetic disorder using infrared motion analysis combined with a continuous performance task (QbTest system) as objective measures. The hypothesis was put forward that a moderate testdose of stimulant medication could determine a robust treatment response, partial response and non-response in relation to activity, attention and impulse control measures. Methods: The study included 44 children and young people between the ages of 7-18 years with a diagnosis of hyperkinetic disorder (F90 & F90.1). A single dose-protocol incorporated the time course effects of both immediate release MPH and extended release MPH (Concerta XL, Equasym XL) to determine comparable peak efficacy periods post intake. Results: A robust treatment response with objective measures reverting to the population mean was found in 37 participants (84%). Three participants (7%) demonstrated a partial response to MPH and four participants (9%) were determined as non-responders due to deteriorating activity measures together with no improvements in attention and impulse control measures. Conclusion: Objective measures provide early into prescribing the opportunity to measure treatment response and monitor adverse reactions to stimulant medication. Most treatment responders demonstrated an effective response to MPH on a moderate testdose facilitating a swift and more optimal titration process.

Linear-wavelet models applied to the identification of a two-link manipulator

This paper shows that a wavelet network and a linear term can be advantageously combined for the purpose of non linear system identification. The theoretical foundation of this approach is laid by proving that radial wavelets are orthogonal to linear functions. A constructive procedure for building such nonlinear regression structures, termed linear-wavelet models, is described. For illustration, sim ulation data are used to identify a model for a two-link robotic manipulator. The results show that the introduction of wavelets does improve the prediction ability of a linear model.

Identification of nonlinear systems with a dynamic recurrent neural network

Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

Identification of potential mechanisms of toxicity after di-(2-ethylhexyl)-phthalate (DEHP) adult exposure in the liver using a systems biology approach

Phthalates are industrial additives widely used as plasticizers. In addition to deleterious effects on male genital development, population studies have documented correlations between phthalates exposure and impacts on reproductive tract development and on the metabolic syndrome in male adults. In this work we investigated potential mechanisms underlying the impact of DEHP on adult mouse liver in vivo. A parallel analysis of hepatic transcript and metabolic profiles from adult mice exposed to varying DEHP doses was performed. Hepatic genes modulated by DEHP are predominantly PPARalpha targets. However, the induction of prototypic cytochrome P450 genes strongly supports the activation of additional NR pathways, including Constitutive Androstane Receptor (CAR). Integration of transcriptomic and metabonomic profiles revealed a correlation between the impacts of DEHP on genes and metabolites related to heme synthesis and to the Rev-erbalpha pathway that senses endogenous heme level. We further confirmed the combined impact of DEHP on the hepatic expression of Alas1, a critical enzyme in heme synthesis and on the expression of Rev-erbalpha target genes involved in the cellular clock and in energy metabolism. This work shows that DEHP interferes with hepatic CAR and Rev-erbalpha pathways which are both involved in the control of metabolism. The identification of these new hepatic pathways targeted by DEHP could contribute to metabolic and endocrine disruption associated with phthalate exposure. Gene expression profiles performed on microdissected testis territories displayed a differential responsiveness to DEHP. Altogether, this suggests that impacts of DEHP on adult organs, including testis, could be documented and deserve further investigations.

Detection and identification of species-specific bacteria associated with synanthropic mites

Internal bacterial communities of synanthropic mites Acarus siro, Dermatophagoides farinae, Lepidoglyphus destructor, and Tyrophagus putrescentiae (Acari: Astigmata) were analyzed by culturing and culture-independent approaches from specimens obtained from laboratory colonies. Homogenates of surface-sterilized mites were used for cultivation on non-selective agar and DNA extraction. Isolated bacteria were identified by sequencing of the 16S rRNA gene. PCR amplified 16S rRNA genes were analyzed by terminal restriction fragment length polymorphism analysis (T-RFLP) and cloning sequencing. Fluorescence in situ hybridization using universal bacterial probes was used for direct bacterial localization. T-RFLP analysis of 16S rRNA gene revealed distinct species-specific bacterial communities. The results were further confirmed by cloning and sequencing (284 clones). L. destructor and D. farinae showed more diverse communities then A. siro and T. putrescentiae. In the cultivated part of the community, the mean CFUs from four mite species ranged from 5.2 × 102 to 1.4 × 103 per mite. D. farinae had significantly higher CFUs than the other species. Bacteria were located in the digestive and reproductive tract, parenchymatical tissue, and in bacteriocytes. Among the clones, Bartonella-like bacteria occurring in A. siro and T. putresecentiae represented a distinct group related to Bartonellaceae and to Bartonella-like symbionts of ants. The clones of high similarity to Xenorhabdus cabanillasii were found in L. destructor and D. farinae, and one clone related to Photorhabdus temperata in A. siro. Members of Sphingobacteriales cloned from D. farinae and A. siro clustered with the sequences of “Candidatus Cardinium hertigii” and as a separate novel cluster.

Identification of metabolites in human hepatic bile using 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS

The first application of high field NMR spectroscopy (800 MHz for 1H observation) to human hepatic bile (as opposed to gall bladder bile) is reported. The bile sample used for detailed investigation was from a donor liver with mild fat infiltration, collected during organ retrieval prior to transplantation. In addition, to focus on the detection of bile acids in particular, a bile extract was analysed by 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS. In the whole bile sample, 40 compounds have been assigned with the aid of two-dimensional 1H–1H TOCSY and 1H–13C HSQC spectra. These include phosphatidylcholine, 14 amino acids, 10 organic acids, 4 carbohydrates and polyols (glucose, glucuronate, glycerol and myo-inositol), choline, phosphocholine, betaine, trimethylamine-N-oxide and other small molecules. An initial NMR-based assessment of the concentration range of some key metabolites has been made. Some observed chemical shifts differ from expected database values, probably due to a difference in bulk diamagnetic susceptibility. The NMR spectra of the whole extract gave identification of the major bile acids (cholic, deoxycholic and chenodeoxycholic), but the glycine and taurine conjugates of a given bile acid could not be distinguished. However, this was achieved by HPLC-NMR/MS, which enabled the separation and identification of ten conjugated bile acids with relative abundances varying from approximately 0.1% (taurolithocholic acid) to 34.0% (glycocholic acid), of which, only the five most abundant acids could be detected by NMR, including the isomers glycodeoxycholic acid and glycochenodeoxycholic acid, which are difficult to distinguish by conventional LC-MS analysis. In a separate experiment, the use of UPLC-MS allowed the detection and identification of 13 bile acids. This work has shown the complementary potential of NMR spectroscopy, MS and hyphenated NMR/MS for elucidating the complex metabolic profile of human hepatic bile. This will be useful baseline information in ongoing studies of liver excretory function and organ transplantation.