Bayesian network approach to fault diagnosis of a hydroelectric generation system

This study focuses on the fault diagnosis of a hydroelectric generation system with hydraulic-mechanical-electric structures. To achieve this analysis, a methodology combining Bayesian network approach and fault diagnosis expert system is presented, which enables the time-based maintenance to transform to the condition-based maintenance. First, fault types and the associated fault characteristics of the generation system are extensively analyzed to establish a precise Bayesian network. Then, the Noisy-Or modeling approach is used to implement the fault diagnosis expert system, which not only reduces node computations without severe information loss but also eliminates the data dependency. Some typical applications are proposed to fully show the methodology capability of the fault diagnosis of the hydroelectric generation system

Avalanches in self-organized critical neural networks: A minimal model for the neural SOC universality class

The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, alone. Such physical mechanisms from the class of self-organized criticality exhibit characteristic dynamical signatures, similar to seismic activity related to earthquakes. Measurements of cortex rest activity showed first signs of dynamical signatures potentially pointing to self-organized critical dynamics in the brain. Indeed, recent more accurate measurements allowed for a detailed comparison with scaling theory of non-equilibrium critical phenomena, proving the existence of criticality in cortex dynamics. We here compare this new evaluation of cortex activity data to the predictions of the earliest physics spin model of self-organized critical neural networks. We find that the model matches with the recent experimental data and its interpretation in terms of dynamical signatures for criticality in the brain. The combination of signatures for criticality, power law distributions of avalanche sizes and durations, as well as a specific scaling relationship between anomalous exponents, defines a universality class characteristic of the particular critical phenomenon observed in the neural experiments. The spin model is a candidate for a minimal model of a self-organized critical adaptive network for the universality class of neural criticality. As a prototype model, it provides the background for models that include more biological details, yet share the same universality class characteristic of the homeostasis of activity in the brain.Comment: 17 pages, 5 figure

Electrical behaviour, characteristics and properties of anodic aluminium oxide films coloured by nickel electrodeposition

Porous anodic films on 1050 aluminium substrate were coloured by AC electrodeposition of nickel. Several experiments were performed at different deposition voltages and nickel concentrations in the electrolyte in order to correlate the applied electrical power to the electrical behaviour, as well as the characteristics and properties of the coatings. The content of nickel inside the coatings reached 1.67 g/m2, depending on the experimental conditions. According to the applied AC voltage in comparison with the threshold voltage Ut, the coating either acted only as a capacitor when U\Ut and, when U[Ut, the behaviour during the anodic and cathodic parts of the power sine wave was different. In particular, due to the semi-conducting characteristics of the barrier layer, additional oxidation of the aluminium substrate occurred during the anodic part of the electrical signal, whilst metal deposition (and solvent reduction) occurred during the cathodic part; these mechanisms correspond to the blocked and pass directions of the barrier layer/electrolyte junction, respectively

Back reaction, covariant anomaly and effective action

In the presence of back reaction, we first produce the one-loop corrections for the event horizon and Hawking temperature of the Reissner-Nordstr\"om black hole. Then, based on the covariant anomaly cancelation method and the effective action technique, the modified expressions for the fluxes of gauge current and energy momentum tensor, due to the effect of back reaction, are obtained. The results are consistent with the Hawking fluxes of a (1+1)-dimensional blackbody at the temperature with quantum corrections, thus confirming the robustness of the covariant anomaly cancelation method and the effective action technique for black holes with back reaction.Comment: 17 page

Intervention effects of Ganoderma lucidum spores on epileptiform discharge hippocampal neurons and expression of Neurotrophin-4 and N-Cadherin

Epilepsy can cause cerebral transient dysfunctions. Ganoderma lucidum spores (GLS), a traditional Chinese medicinal herb, has shown some antiepileptic effects in our previous studies. This was the first study of the effects of GLS on cultured primary hippocampal neurons, treated with Mg2+ free medium. This in vitro model of epileptiform discharge hippocampal neurons allowed us to investigate the anti-epileptic effects and mechanism of GLS activity. Primary hippocampal neurons from <1 day old rats were cultured and their morphologies observed under fluorescence microscope. Neurons were confirmed by immunofluorescent staining of neuron specific enolase (NSE). Sterile method for GLS generation was investigated and serial dilutions of GLS were used to test the maximum non-toxic concentration of GLS on hippocampal neurons. The optimized concentration of GLS of 0.122 mg/ml was identified and used for subsequent analysis. Using the in vitro model, hippocampal neurons were divided into 4 groups for subsequent treatment i) control, ii) model (incubated with Mg2+ free medium for 3 hours), iii) GLS group I (incubated with Mg2+ free medium containing GLS for 3 hours and replaced with normal medium and incubated for 6 hours) and iv) GLS group II (neurons incubated with Mg2+ free medium for 3 hours then replaced with a normal medium containing GLS for 6 hours). Neurotrophin-4 and N-Cadherin protein expression were detected using Western blot. The results showed that the number of normal hippocampal neurons increased and the morphologies of hippocampal neurons were well preserved after GLS treatment. Furthermore, the expression of neurotrophin-4 was significantly increased while the expression of N-Cadherin was decreased in the GLS treated group compared with the model group. This data indicates that GLS may protect hippocampal neurons by promoting neurotrophin-4 expression and inhibiting N-Cadherin expression

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

A Nonaqueous Approach to the Preparation of Iron Phosphide Nanowires

Previous preparation of iron phosphide nanowires usually employed toxic and unstable iron carbonyl compounds as precursor. In this study, we demonstrate that iron phosphide nanowires can be synthesized via a facile nonaqueous chemical route that utilizes a commonly available iron precursor, iron (III) acetylacetonate. In the synthesis, trioctylphosphine (TOP) and trioctylphosphine oxide (TOPO) have been used as surfactants, and oleylamine has been used as solvent. The crystalline structure and morphology of the as-synthesized products were characterized by powder X-ray diffraction (XRD) and transmission electron microscopy (TEM). The obtained iron phosphide nanowires have a typical width of ~16 nm and a length of several hundred nanometers. Structural and compositional characterization reveals a hexagonal Fe2P crystalline phase. The morphology of as-synthesized products is greatly influenced by the ratio of TOP/TOPO. The presence of TOPO has been found to be essential for the growth of high-quality iron phosphide nanowires. Magnetic measurements reveal ferromagnetic characteristics, and hysteresis behaviors below the blocking temperature have been observed

Fat Mass and Obesity-Associated Gene (FTO) in Eating Disorders: Evidence for Association of the rs9939609 Obesity Risk Allele with Bulimia nervosa and Anorexia nervosa

Objective: The common single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity-associated gene (FTO) is associated with obesity. As genetic variants associated with weight regulation might also be implicated in the etiology of eating disorders, we evaluated whether SNP rs9939609 is associated with bulimia nervosa (BN) and anorexia nervosa (AN). Methods: Association of rs9939609 with BN and AN was assessed in 689 patients with AN, 477 patients with BN, 984 healthy non-population-based controls, and 3,951 population-based controls (KORA-S4). Based on the familial and premorbid occurrence of obesity in patients with BN, we hypothesized an association of the obesity risk A-allele with BN. Results: In accordance with our hypothesis, we observed evidence for association of the rs9939609 A-allele with BN when compared to the non-population-based controls (unadjusted odds ratio (OR) = 1.142, one-sided 95% confidence interval (CI) 1.001-infinity; one-sided p = 0.049) and a trend in the population-based controls (OR = 1.124, one-sided 95% CI 0.932-infinity; one-sided p = 0.056). Interestingly, compared to both control groups, we further detected a nominal association of the rs9939609 A-allele to AN (OR = 1.181, 95% CI 1.027-1.359, two-sided p = 0.020 or OR = 1.673, 95% CI 1.101-2.541, two-sided p = 0.015,). Conclusion: Our data suggest that the obesity-predisposing FTO allele might be relevant in both AN and BN. Copyright (C) 2012 S. Karger GmbH, Freibur

Rpair: Rescaling RePair with Rsync

Data compression is a powerful tool for managing massive but repetitive datasets, especially schemes such as grammar-based compression that support computation over the data without decompressing it. In the best case such a scheme takes a dataset so big that it must be stored on disk and shrinks it enough that it can be stored and processed in internal memory. Even then, however, the scheme is essentially useless unless it can be built on the original dataset reasonably quickly while keeping the dataset on disk. In this paper we show how we can preprocess such datasets with context-triggered piecewise hashing such that afterwards we can apply RePair and other grammar-based compressors more easily. We first give our algorithm, then show how a variant of it can be used to approximate the LZ77 parse, then leverage that to prove theoretical bounds on compression, and finally give experimental evidence that our approach is competitive in practice