[Comparison of balneotherapy and balneotherapy combined with magnetic-laser therapy at a sanatorium-resort stage of treatment of patients with eczema]. / Sravnenie bal'neoterapii i bal'neoterapii v sochetanii s magnitolazernoi terapiei na sanatorno-kurortnom etape lecheniya bol'nykh s istinnoi ekzemoi.

The search for new rational ways to improve the effectiveness of treatment and rehabilitation measures of patients with true eczema continues to be one of the pressing issues in modern clinical dermatology. OBJECTIVE: The comparative analysis of influence of different variants of SCL: balneotherapy and balneotherapy combined with magnetic laser therapy on the dermatological status, IL-4 and IL-13 level, psycho-emotional state and QOL evaluation in patients with true eczema. MATERIAL AND METHODS: The study involved 112 patients with true eczema undergoing spa treatment (SCR) (54 in the balneotherapy group and 58 in the balneotherapy group combined with magnetic laser therapy. The effectiveness of SCR was assessed using the EASI, HARS and MADRS scales, and the DLQI questionnaire. The dynamics of IL-4 and IL-13 plasma levels were studied. The duration of the study was 6 months and 14 days. RESULTS: After 14 days of SCR, a statistically significant reduction of the EASI index was more pronounced in the balneotherapy group in combination with MLT compared to the balneotherapy group (p=0.041). Balneotherapy combined with MLT contributed to a statistically significant reduction in the HARS and HDRS scores. The decrease in IL-4 and IL-13 levels was statistically more significant in the balneotherapy group in combination with MLT. The combined use of balneotherapy and MLT in comparison with the balneotherapy group was accompanied by a more pronounced improvement in QOL. The combined use of balneotherapy and MLT in the follow-up phase showed a long-term positive effect: 6 months after completing SCR, the number of patients who had clinical remission was statistically significantly higher than that of the balneotherapy group (87.4% vs 22.5%). CONCLUSION: The combined use of balneotherapy and MLT compared with balneotherapy in patients with true eczema on SCR was shown to be advantageous. The complex application of balneotherapy and MLT decreases inflammatory biomarker scores, improves dermatological and psychoemotional status, QOL parameters and is well tolerated.

Recurrent neural network-based approach for early recognition of Alzheimer's disease in EEG.

OBJECTIVE: We explored the ability of specifically designed and trained recurrent neural networks (RNNs), combined with wavelet preprocessing, to discriminate between the electroencephalograms (EEGs) of patients with mild Alzheimer's disease (AD) and their age-matched control subjects. METHODS: Twomin recordings of resting eyes-closed continuous EEGs (as well as their wavelet-filtered subbands) obtained from parieto-occipital channels of 10 early AD patients and 10 healthy controls were input into RNNs for training and testing purposes. The RNNs were chosen because they can implement extremely non-linear decision boundaries and possess memory of the state, which is crucial for the considered task. RESULTS: The best training/testing results were achieved using a 3-layer RNN on left parietal channel level 4 high-pass wavelet subbands. When trained on 3 AD and 3 control recordings, the resulting RNN tested well on all remaining controls and 5 out of 7 AD patients. This represented a significantly better than chance performance of about 80% sensitivity at 100% specificity. CONCLUSION: The suggested combined wavelet/RNN approach may be useful in analyzing long-term continuous EEGs for early recognition of AD. This approach should be extended on larger patient populations before its clinical diagnostic value can be established. Further lines of investigation might also require that EEGs be recorded from patients engaged in certain mental (cognitive) activities.

Stability analysis of discrete-time recurrent neural networks.

We address the problem of global Lyapunov stability of discrete-time recurrent neural networks (RNNs) in the unforced (unperturbed) setting. It is assumed that network weights are fixed to some values, for example, those attained after training. Based on classical results of the theory of absolute stability, we propose a new approach for the stability analysis of RNNs with sector-type monotone nonlinearities and nonzero biases. We devise a simple state-space transformation to convert the original RNN equations to a form suitable for our stability analysis. We then present appropriate linear matrix inequalities (LMIs) to be solved to determine whether the system under study is globally exponentially stable. Unlike previous treatments, our approach readily permits one to account for non-zero biases usually present in RNNs for improved approximation capabilities. We show how recent results of others on the stability analysis of RNNs can be interpreted as special cases within our approach. We illustrate how to use our approach with examples. Though illustrated on the stability analysis of recurrent multilayer perceptrons, the approach proposed can also be applied to other forms of time-lagged RNNs.

Adaptive critic designs.

We discuss a variety of adaptive critic designs (ACDs) for neurocontrol. These are suitable for learning in noisy, nonlinear, and nonstationary environments. They have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Our discussion of these origins leads to an explanation of three design families: heuristic dynamic programming, dual heuristic programming, and globalized dual heuristic programming (GDHP). The main emphasis is on DHP and GDHP as advanced ACDs. We suggest two new modifications of the original GDHP design that are currently the only working implementations of GDHP. They promise to be useful for many engineering applications in the areas of optimization and optimal control. Based on one of these modifications, we present a unified approach to all ACDs. This leads to a generalized training procedure for ACDs.

Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks.

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenience.

Neurocontroller alternatives for "fuzzy" ball-and-beam systems with nonuniform nonlinear friction.

The ball-and-beam problem is a benchmark for testing control algorithms. In the World Congress on Neural Networks, 1994, Prof. L. Zadeh proposed a twist to the problem, which, he suggested, would require a fuzzy logic controller. This experiment uses a beam, partially covered with a sticky substance, increasing the difficulty of predicting the ball's motion. We complicated this problem even more by not using any information concerning the ball's velocity. Although it is common to use the first differences of the ball's consecutive positions as a measure of velocity and explicit input to the controller, we preferred to exploit recurrent neural networks, inputting only consecutive positions instead. We have used truncated backpropagation through time with the node-decoupled extended Kalman filter (NDEKF) algorithm to update the weights in the networks. Our best neurocontroller uses a form of approximate dynamic programming called an adaptive critic design. A hierarchy of such designs exists. Our system uses dual heuristic programming (DHP), an upper-level design. To our best knowledge, our results are the first use of DHP to control a physical system. It is also the first system we know of to respond to Zadeh's challenge. We do not claim this neural network control algorithm is the best approach to this problem, nor do we claim it is better than a fuzzy controller. It is instead a contribution to the scientific dialogue about the boundary between the two overlapping disciplines.

Comments on "A self-organizing network for hyperellipsoidal clustering (HEC)" [and reply].

In the above paper by Mao-Jain (ibid., vol.7 (1996)), the Mahalanobis distance is used instead of Euclidean distance as the distance measure in order to acquire the hyperellipsoidal clustering. We prove that the clustering cost function is a constant under this condition, so hyperellipsoidal clustering cannot be realized. We also explains why the clustering algorithm developed in the above paper can get some good hyperellipsoidal clustering results. In reply, Mao-Jain state that the Wang-Xia failed to point out that their HEC clustering algorithm used a regularized Mahalanobis distance instead of the standard Mahalanobis distance. It is the regularized Mahalanobis distance which plays an important role in realizing hyperellipsoidal clusters. In conclusion, the comments made by Wang-Xia together with this response provide some new insights into the behavior of their HEC clustering algorithm. It further confirms that the HEC algorithm is a useful tool for understanding the structure of multidimensional data.

[Effect of Erbisol on indices of endogenous intoxication in patients with microbial eczema]. / Vliianie "Erbisola" na pokazateli éndogennoi intoksikatsii u bol'nykh mikrobnoi ékzemoi.

Identified in 66 patients with microbial eczema were changes in the blood serum and urine levels of medium-weight molecules. In a combined treatment of the test group patients the home-produces drug erbisol has been shown to secure good results, which fact permits recommending the use of erbisol in the therapy of microbial eczema.