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1.
Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect
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Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity. 相似文献
2.
João Marcos G. Barbosa Milenna K. Fernandes Rodrigues Lurian C. David Taynara C. e Silva Danielly A. Fortuna Lima Naiara Z. Pereira Emmanuel B. D'Alessandro Anselmo E. de Oliveira Paulo H. Jorge da Cunha Maria Clorinda S. Fioravanti Nelson R. Antoniosi Filho 《Biomedical chromatography : BMC》2020,34(11):e4935
An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds (‘Curraleiro Pé-Duro’ and ‘Pantaneiro’) were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC–MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC–MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication. 相似文献
3.
Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods. 相似文献
4.
Peter Imkeller 《Probability Theory and Related Fields》1996,106(1):105-135
Summary. The analytic treatment of problems related to the asymptotic behaviour of random dynamical systems generated by stochastic
differential equations suffers from the presence of non-adapted random invariant measures. Semimartingale theory becomes accessible
if the underlying Wiener filtration is enlarged by the information carried by the orthogonal projectors on the Oseledets spaces
of the (linearized) system.
We study the corresponding problem of preservation of the semimartingale property and the validity of a priori inequalities
between the norms of stochastic integrals in the enlarged filtration and norms of their quadratic variations in case the random
element F enlarging the filtration is real valued and possesses an absolutely continuous law. Applying the tools of Malliavin’s calculus,
we give smoothness conditions on F under which the semimartingale property is preserved and a priori martingale inequalities are valid.
Received: 12 April 1995 / In revised form: 7 March 1996 相似文献
5.
Laser welding is one of the most precise welding processes in joining sheet metals. In laser welding, performing real time evaluation of the welding quality is very important to enhance the efficiency of the welding process. In this study, the plasma and spatter, which are generated during laser welding, are measured using UV and IR photodiodes. The factors that influence weld quality are classified into five categories; optimal heat input, slightly low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. The data number deviated from reference signals and their standard deviations were also considered to evaluate the qualities. A system was also formulated to perform real time evaluations of the weld quality using a fuzzy multi-feature pattern recognition with the measured signals. 相似文献
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7.
根据生产任务选择加工设备进行制造资源重组是实现可重构制造系统的关键问题之一,由于设备的选择涉及到多种因素,既有定量指标,又有定性指标,传统的依靠人工经验的方法显得力不从心。本文首先结合实际情况,提出了一套设备选择评价体系,通过对模糊判断矩阵采用最小对数二乘法确定各评价因素的权重系数,针对定性指标和定量指标采用不同的方法确定其性能指标值,通过模糊积分对评判指标进行综合评判,最后进行了实例研究。所提出的方法有效地简化了决策过程,为可重构制造系统设备选择提供了一套行之有效的方法。 相似文献
8.
A new family of proximity graphs: Class cover catch digraphs 总被引:1,自引:0,他引:1
Jason DeVinney 《Discrete Applied Mathematics》2006,154(14):1975-1982
Motivated by issues in machine learning and statistical pattern classification, we investigate a class cover problem (CCP) with an associated family of directed graphs—class cover catch digraphs (CCCDs). CCCDs are a special case of catch digraphs. Solving the underlying CCP is equivalent to finding a smallest cardinality dominating set for the associated CCCD, which in turn provides regularization for statistical pattern classification. Some relevant properties of CCCDs are studied and a characterization of a family of CCCDs is given. 相似文献
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