478 research outputs found
La manipulación de la memoria histórica en el nacionalismo español
El autor analiza el tema propuesto desde una doble perspectiva: por un lado, la selección del recuerdo a evocar en función de la legitimidad histórica reivindicada por los poderes establecidos. Por otro, la falsificación de las fuentes de base y la distorsión interpretativa de la realidad histórica, distorsión ligada, fundamentalmente a partir del siglo XIX, a la emergencia de los nacionalismos.The author analyzes the proposed theme from a double perspective: the selection of memory for legitimizing the History favoured by the Establishment and the falsification of the original sources and the interpretative distortion of historical reality, basically bound to the emergence of nationalisms since the XIX century
Statistical process monitoring of a multiphase flow facility
Industrial needs are evolving fast towards more flexible manufacture schemes. As a consequence, it is often required to adapt the plant production to the demand, which can be volatile depending on the application. This is why it is important to develop tools that can monitor the condition of the process working under varying operational conditions. Canonical Variate Analysis (CVA) is a multivariate data driven methodology which has been demonstrated to be superior to other methods, particularly under dynamically changing operational conditions. These comparative studies normally use computer simulated data in benchmark case studies such as the Tennessee Eastman Process Plant (Ricker, N.L. Tennessee Eastman Challenge Archive, Available at 〈http://depts.washington.edu/control/LARRY/TE/download.html〉 Accessed 21.03.2014).
The aim of this work is to provide a benchmark case to demonstrate the ability of different monitoring techniques to detect and diagnose artificially seeded faults in an industrial scale multiphase flow experimental rig. The changing operational conditions, the size and complexity of the test rig make this case study an ideal candidate for a benchmark case that provides a test bed for the evaluation of novel multivariate process monitoring techniques performance using real experimental data. In this paper, the capabilities of CVA to detect and diagnose faults in a real system working under changing operating conditions are assessed and compared with other methodologies. The results obtained demonstrate that CVA can be effectively applied for the detection and diagnosis of faults in real complex systems, and reinforce the idea that the performance of CVA is superior to other algorithms
Alterations in EGF-Endocytosis, Lysosomal Enzyme Transport and Maturation of Cathepsins in Juvenile Neuronal Ceroid Lipofuscinosis Fibroblasts
Background: Juvenile neuronal ceroid lipofuscinosis (JNCL), one of the most frequent forms of the NCL storage diseases, is known to be caused by loss-of-function mutations in ceroid-lipofuscinosis neuronal protein 3 (CLN3), but its cell function has not been fully elucidated. We previously reported increased lysosomal pH in CLN3 deficient cells. In the present study, we analysed the consequences of this effect in the endo-lysosomal pathways in CLN3 cells.Methods: The present study investigated different endo-lysosomal pathways in control, CLN2, CLN3 human skin fibroblasts under high and low proteolysis conditions. Cell surface biotinylation after EGF (2 ng/mL) stimulation, EGF phosphorylation (Tyr-845), retromer and cation-independent mannose-6-phosphate receptor (CI-MPR) levels and stability, EGF degradation pathways and cathepsin L and D levels were analysed by western blots. Caveolae mediated endocytosis was analysed by flow cytometry. CIMPR subcellular localization was ascertained by immunocytochemistry, confocal microscopy and further image analysis.Results: Whereas caveolae-mediated endocytosis was not affected in CLN3 cells, clathrin-mediated epidermal growth factor (EGF) internalization was reduced, along with EGF receptor (EGFR) phosphorylation. In addition, cell surface EGFR levels and recycling to the cell membrane were increased. EGFR lysosomal degradation was impaired and our results suggest that the receptor was diverted to proteasomal degradation. We also analysed the machinery responsible for lysosomal hydrolase transport to the lysosome and found increased stability of CIMPR, a major receptor implicated in the transport of hydrolases. The subcellular distribution of the CI-MPR was also altered in CLN3 cells, since it accumulated within the Trans-Golgi network (TGN) and did not progress into the lysosomes. In addition, we found a reduced turnover of retromer subunits, a complex that retrieves the CI-MPR from endosomes to the TGN. Finally and as a possible consequence of these alterations in lysosomal enzyme transport, cathepsin L and D maturation were found suppressed in CLN3 cells.Conclusion: Altogether, these results point to increased lisosomal pH as a pivotal event causing various alterations in intracellular traffic associated to the development of JNCL disease
Data-based detection and diagnosis of faults in linear actuators
Modern industrial facilities, as well as vehicles and many other assets, are becoming highly automated and instrumented. As a consequence, actuators are required to perform a wide variety of tasks, often for linear motion. However, the use of tools to monitor the condition of linear actuators is not widely extended in industrial applications. This paper presents a data-based method to monitor linear electro-mechanical actuators. The proposed algorithm makes use of features extracted from electric current and position measurements, typically available from the controller, to detect and diagnose mechanical faults. The features are selected to characterize the system dynamics during transient and steady-state operation and are then combined to produce a condition indicator. The main advantage of this approach is the independence from a need for a physical model or additional sensors. The capabilities of the method are assessed using a novel experimental linear actuator test rig specially designed to recreate fault scenarios under different operating conditions
From spin-Peierls to superconductivity: (TMTTF)_2PF_6 under high pressure
The nature of the attractive electron-electron interaction, leading to the
formation of Cooper-pairs in unconventional superconductors has still to be
fully understood and is subject to intensive research. Here we show that the
sequence spin-Peierls, antiferromagnetism, superconductivity observed in
(TMTTF)_2PF_6 under pressure makes the (TM)_2X phase diagram universal. We
argue that the suppression of the spin-Peierls transition under pressure, the
close vicinity of antiferromagnetic and superconducting phases at high pressure
as well as the existence of critical antiferromagnetic fluctuations above T_c
strongly support the intriguing possibility that the interchain exchange of
antiferromagnetic fluctuations provides the pairing mechanism required for
bound charge carriers.Comment: 4 pages, revtex, 4 figures (jpeg,eps,png
Estimation of powder mass flow rate in a screw feeder using acoustic emissions
Screw feeders are widely used in powder processes to provide an accurate and consistent flow rate of particles. However this flow rate is rarely measured or controlled. This investigation explores the use of generalised norms and moments from structural-borne acoustic emission (AE) measurements as key statistics indicators for the estimation of powder mass flow rate in a screw feeder.
Experimental work was carried out acquiring AE measurements from an industrial screw feeder working with four different types of material at different dispensation rates. Signal enveloping was used in first place to eliminate high frequency components while retaining essential information such as peaks or bursts caused by particle impacts. Secondly a set of generalised norms and moments is extracted from the signal, and their correlation with mass flow rate was studied and assessed. Finally a general model able to estimate mass flow rate for the four different types of powders tested was developed
Data-Driven Wheel Slip Diagnostics for Improved Railway Operations
Wheel slip activity detection is crucial in railway maintenance, as it can contribute to avoiding wheel damage but also track deteriorations leading to significant maintenance costs, trains delays, as well as the risk of accidents. Wheel slip activity is characterised by lower adhesion between track and wheel, especially in braking conditions, locking the wheels. It is complex to model or predict, being influenced by a multitude of factors including ambient conditions, global vehicle load, track and axle quality, leaves and objects present on the rail, steep incline, oxidation of the rails, and braking forces applied to the wheels. This paper presents a combined wavelet and tuned Long-Short Term Memory (LSTM) approach for the detection of wheel slip from time series data collected from real-world trains. Results provide evidence of superior performance over methods such as decision trees and random forests, naïve Bayes, k-nearest neighbours, logistic regression, and support vector machines
CAMPANAR: GENÉSIS Y EVOLUCIÓN DE UN ASENTAMIENTO URBANO SOBRE LA HUERTA HISTÓRICA DE VALENCIA
Carcel García, C. (2014). CAMPANAR: GENÉSIS Y EVOLUCIÓN DE UN ASENTAMIENTO URBANO SOBRE LA HUERTA HISTÓRICA DE VALENCIA [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39312TESI
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