Validation of Neural Network-based Fault Diagnosis for Multi-stack Fuel Cell Systems: Stack Voltage Deviation Detection☆

Abstract This paper presents (i) an algorithm for the detection of unexpected stack voltage deviations in an Solid Oxide Fuel Cells (SOFC)-based power system with multiple stacks and (ii) its validation in a simulated online environment. The algorithm is based on recurrent neural networks (RNNs) and is validated by using operating data from the Wartsila WFC20 multi-stack SOFC system. The voltage deviation detection is based on statistical testing. Instead of a hardware implementation in the actual power plant, the algorithm is validated in a simulated online environment that provides data I/O communication based on the OPC (i.e. Object Linking and Embedding (OLE) for Process Control) protocol, which is also the technology utilized in the real hardware environment. The validation tests show that the RNN-based algorithm effectively detects unwanted stack voltage deviations and also that it is online-viable

On the use of neural networks and statistical tools for nonlinear modeling and on-field diagnosis of solid oxide fuel cell stacks

Abstract The paper reports on the activities performed within the European funded project GENIUS to develop black-box models for modeling and diagnosis of solid oxide fuel cell (SOFC) stacks. Two modeling techniques were investigated, i.e. Neural Networks (NNs) and Statistical Tools (STs). The deployment of NNs was twofold: Recurrent Neural Networks (RNNs) and an NN classifier were developed to simulate transient operation of SOFCs and identify some specific faults that may occur in such devices, respectively. On the other hand, STs are based on a stepwise multiple regression. Data for model development were obtained from experiments specifically designed to reach maximal information content. The final aim was to obtain highly general models of SOFC stacks' operation in both transient and steady state. All the developed black-box models exhibited high accuracy and reliability on both training and test data-sets. Moreover, the black-box models were also proven effective in performing real-time monitoring and degradation analysis for different SOFC stack technologies

Study Projectile Motion With Different Initial Conditions Using Digital Image

The aim of this research is building algorithms to study projectile motion in tow dimension  and tracking the object in sequence frames of digital image . Computer program has written in visual basic language (version 6) depend on mathematical models to detect a motion of object in two–dimensions (2-D)with different initial conditions like initial velocity, the height of object from the earth and the angle of motion, to calculate important variables in motion such as distance, displacement, velocity, speed and the energy (kinetic and potential). Color digital images of type (bmp) and (RGB) color model were used in the study for easy handling them, after determining the center of the image on the x-axis, and y-axis and tracking movement on the basis of the center, and the results were expected to conform to the movement of the body. Key words: Projectile, Motion, Digital Image

Plasma levels of conjugated bile acids in newborns after a short period of parenteral nutrition.

Background: Patients receiving parenteral nutrition (PN) frequently exhibit liver dysfunction. The authors previously reported that plant sterols of lipid emulsions added to the nutritional solution of newborns receiving PN accumulate in plasma and cell membranes and may contribute to the development of cholestasis. Conjugated bile acids (BA) have been shown to be useful markers of cholestasis. Plasma levels of several BA in newborns were quantified after administration of PN for less than 2 weeks. Methods: Plasma samples from 15 healthy control infants (CN), 22 patients who had received PN for 3-15 days (T1), and 9 patients scheduled to receive PN (T0) were analyzed. After a simple extraction procedure, plasma BA were analyzed by liquid chromatography-tandem mass spectrometry using a quantitative isotope dilution method. Results: The concentrations of BA did not differ significantly between controls and patients before PN (CN vs T0), with the exception of glycocholic acid (GCA; 2.30 ± 2.60 ??M vs 7.29 ± 5.39 ??M, respectively). There was a significant difference in several BA between controls and patients after PN (2.30 ± 2.60 ??M vs 7.61 ± 6.46 ??M for GCA, respectively; 4.02 ± 3.49 ??M vs 11.88 ± 11.05 ??M for taurocholic acid [TCA], respectively; and 4.81 ± 3.49 ??M vs 13.58 ± 12.22 ??M for taurochenodeoxycholic + taurodeoxycholic + tauroursodeoxycholic acids [TCDCA+TDCA+TUDCA], respectively). Conclusions: In newborns receiving PN, a short period of PN is associated with an early increase of some conjugated BA. These results suggest that GCA, TCA, and TCDCA+TDCA+TUDCA levels could be used as early markers of PN-related cholestasis

MutLα heterodimers modify the molecular phenotype of Friedreich ataxia

This article has been made available through the Brunel Open Access Publishing Fund.Background: Friedreich ataxia (FRDA), the most common autosomal recessive ataxia disorder, is caused by a dynamic GAA repeat expansion mutation within intron 1 of FXN gene, resulting in down-regulation of frataxin expression. Studies of cell and mouse models have revealed a role for the mismatch repair (MMR) MutS-heterodimer complexes and the PMS2 component of the MutLα complex in the dynamics of intergenerational and somatic GAA repeat expansions: MSH2, MSH3 and MSH6 promote GAA repeat expansions, while PMS2 inhibits GAA repeat expansions. Methodology/Principal Findings: To determine the potential role of the other component of the MutLα complex, MLH1, in GAA repeat instability in FRDA, we have analyzed intergenerational and somatic GAA repeat expansions from FXN transgenic mice that have been crossed with Mlh1 deficient mice. We find that loss of Mlh1 activity reduces both intergenerational and somatic GAA repeat expansions. However, we also find that loss of either Mlh1 or Pms2 reduces FXN transcription, suggesting different mechanisms of action for Mlh1 and Pms2 on GAA repeat expansion dynamics and regulation of FXN transcription. Conclusions/Significance: Both MutLα components, PMS2 and MLH1, have now been shown to modify the molecular phenotype of FRDA. We propose that upregulation of MLH1 or PMS2 could be potential FRDA therapeutic approaches to increase FXN transcription. © 2014 Ezzatizadeh et al.This article has been made available through the Brunel Open Access Publishing Fund

Impairing the production of ribosomal RNA activates mammalian target of rapamycin complex 1 signalling and downstream translation factors

Ribosome biogenesis is a key process for maintaining protein synthetic capacity in dividing or growing cells, and requires coordinated production of ribosomal proteins and ribosomal RNA (rRNA), including the processing of the latter. Signalling through mammalian target of rapamycin complex 1 (mTORC1) activates all these processes. Here, we show that, in human cells, impaired rRNA processing, caused by expressing an interfering mutant of BOP1 or by knocking down components of the PeBoW complex elicits activation of mTORC1 signalling. This leads to enhanced phosphorylation of its substrates S6K1 and 4E-BP1, and stimulation of proteins involved in translation initiation and elongation. In particular, we observe both inactivation and downregulation of the eukaryotic elongation factor 2 kinase, which normally inhibits translation elongation. The latter effect involves decreased expression of the eEF2K mRNA. The mRNAs for ribosomal proteins, whose translation is positively regulated by mTORC1 signalling, also remain associated with ribosomes. Therefore, our data demonstrate that disrupting rRNA production activates mTORC1 signalling to enhance the efficiency of the translational machinery, likely to help compensate for impaired ribosome production

Genome-wide genotyping demonstrates a polygenic risk score associated with white matter hyperintensity volume in CADASIL

Background and Purpose—White matter hyperintensities (WMH) on MRI are a quantitative marker for sporadic cerebral small vessel disease and are highly heritable. To date, large-scale genetic studies have identified only a single locus influencing WMH burden. This might in part relate to biological heterogeneity of sporadic WMH. The current study searched for genetic modifiers of WMH volume in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a monogenic small vessel disease. Methods—We performed a genome-wide association study to identify quantitative trait loci for WMH volume by combining data from 517 CADASIL patients collected through 7 centers across Europe. WMH volumes were centrally analyzed and quantified on fluid attenuated inversion recovery images. Genotyping was performed using the Affymetrix 6.0 platform. Individuals were assigned to 2 distinct genetic clusters (cluster 1 and cluster 2) based on their genetic background. Results—Four hundred sixty-six patients entered the final genome-wide association study analysis. The phenotypic variance of WMH burden in CADASIL explained by all single nucleotide polymorphisms in cluster 1 was 0.85 (SE=0.21), suggesting a substantial genetic contribution. Using cluster 1 as derivation and cluster 2 as a validation sample, a polygenic score was significantly associated with WMH burden (P=0.001) after correction for age, sex, and vascular risk factors. No single nucleotide polymorphism reached genome-wide significance. Conclusions—We found a polygenic score to be associated with WMH volume in CADASIL subjects. Our findings suggest that multiple variants with small effects influence WMH burden in CADASIL. The identification of these variants and the biological pathways involved will provide insights into the pathophysiology of white matter disease in CADASIL and possibly small vessel disease in general

Generation and characterisation of Friedreich ataxia YG8R mouse fibroblast and neural stem cell models

This article has been made available through the Brunel Open Access Publishing Fund.Background: Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disease caused by GAA repeat expansion in the first intron of the FXN gene, which encodes frataxin, an essential mitochondrial protein. To further characterise the molecular abnormalities associated with FRDA pathogenesis and to hasten drug screening, the development and use of animal and cellular models is considered essential. Studies of lower organisms have already contributed to understanding FRDA disease pathology, but mammalian cells are more related to FRDA patient cells in physiological terms. Methodology/Principal Findings: We have generated fibroblast cells and neural stem cells (NSCs) from control Y47R mice (9 GAA repeats) and GAA repeat expansion YG8R mice (190+120 GAA repeats). We then differentiated the NSCs in to neurons, oligodendrocytes and astrocytes as confirmed by immunocytochemical analysis of cell specific markers. The three YG8R mouse cell types (fibroblasts, NSCs and differentiated NSCs) exhibit GAA repeat stability, together with reduced expression of frataxin and reduced aconitase activity compared to control Y47R cells. Furthermore, YG8R cells also show increased sensitivity to oxidative stress and downregulation of Pgc-1α and antioxidant gene expression levels, especially Sod2. We also analysed various DNA mismatch repair (MMR) gene expression levels and found that YG8R cells displayed significant reduction in expression of several MMR genes, which may contribute to the GAA repeat stability. Conclusions/Significance: We describe the first fibroblast and NSC models from YG8R FRDA mice and we confirm that the NSCs can be differentiated into neurons and glia. These novel FRDA mouse cell models, which exhibit a FRDA-like cellular and molecular phenotype, will be valuable resources to further study FRDA molecular pathogenesis. They will also provide very useful tools for preclinical testing of frataxin-increasing compounds for FRDA drug therapy, for gene therapy, and as a source of cells for cell therapy testing in FRDA mice. © 2014 Sandi et al

Cloud computing: survey on energy efficiency

International audienceCloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions

A Combined Nucleic Acid and Protein Analysis in Friedreich Ataxia: Implications for Diagnosis, Pathogenesis and Clinical Trial Design

BACKGROUND: Friedreich's ataxia (FRDA) is the most common hereditary ataxia among caucasians. The molecular defect in FRDA is the trinucleotide GAA expansion in the first intron of the FXN gene, which encodes frataxin. No studies have yet reported frataxin protein and mRNA levels in a large cohort of FRDA patients, carriers and controls. METHODOLOGY/PRINCIPAL FINDINGS: We enrolled 24 patients with classic FRDA phenotype (cFA), 6 late onset FRDA (LOFA), all homozygous for GAA expansion, 5 pFA cases who harbored the GAA expansion in compound heterozygosis with FXN point mutations (namely, p.I154F, c.482+3delA, p.R165P), 33 healthy expansion carriers, and 29 healthy controls. DNA was genotyped for GAA expansion, mRNA/FXN was quantified in real-time, and frataxin protein was measured using lateral-flow immunoassay in peripheral blood mononuclear cells (PBMCs). Mean residual levels of frataxin, compared to controls, were 35.8%, 65.6%, 33%, and 68.7% in cFA, LOFA, pFA and healthy carriers, respectively. Comparison of both cFA and pFA with controls resulted in 100% sensitivity and specificity, but there was overlap between LOFA, carriers and controls. Frataxin levels correlated inversely with GAA1 and GAA2 expansions, and directly with age at onset. Messenger RNA expression was reduced to 19.4% in cFA, 50.4% in LOFA, 52.7% in pFA, 53.0% in carriers, as compared to controls (p<0.0001). mRNA levels proved to be diagnostic when comparing cFA with controls resulting in 100% sensitivity and specificity. In cFA and LOFA patients mRNA levels correlated directly with protein levels and age at onset, and inversely with GAA1 and GAA2. CONCLUSION/SIGNIFICANCE: We report the first explorative study on combined frataxin and mRNA levels in PBMCs from a cohort of FRDA patients, carriers and healthy individuals. Lateral-flow immunoassay differentiated cFA and pFA patients from controls, whereas determination of mRNA in q-PCR was sensitive and specific only in cFA