In-flight novelty detection with convolutional neural networks

Gas turbine engines are complex machines that typically generate a vast amount of data, and require careful monitoring to allow for cost-effective preventative maintenance. In aerospace applications, returning all measured data to ground is prohibitively expensive, often causing useful, high value, data to be discarded. The ability to detect, prioritise, and return useful data in real-time is therefore vital. This paper proposes that system output measurements, described by a convolutional neural network model of normality, are prioritised in real-time for the attention of preventative maintenance decision makers. Due to the complexity of gas turbine engine time-varying behaviours, deriving accurate physical models is difficult, and often leads to models with low prediction accuracy and incompatibility with real-time execution. Data-driven modelling is a desirable alternative producing high accuracy, asset specific models without the need for derivation from first principles. We present a data-driven system for online detection and prioritisation of anomalous data. Biased data assessment deriving from novel operating conditions is avoided by uncertainty management integrated into the deep neural predictive model. Testing is performed on real and synthetic data, showing sensitivity to both real and synthetic faults. The system is capable of running in real-time on low-power embedded hardware and is currently in deployment on the Rolls-Royce Pearl 15 engine flight trials

Conformal fields in the pp-wave limit

The pp-wave (Penrose limit) in conformal field theory can be viewed as a special contraction of the unitary representations of the conformal group. We study the kinematics of conformal fields in this limit in a geometric approach where the effect of the contraction can be visualized as an expansion of space-time. We discuss the two common models of space-time as carrier spaces for conformal fields: One is the usual Minkowski space and the other is the coset of the conformal group over its maximal compact subgroup. We show that only the latter manifold and the corresponding conformal representation theory admit a non-singular contraction limit. We also address the issue of correlation functions of conformal fields in the pp-wave limit. We show that they have a well-defined contraction limit if their space-time dependence merges with the dependence on the coordinates of the R symmetry group. This is a manifestation of the fact that in the limit the space-time and R symmetries become indistinguishable. Our results might find applications in actual calculations of correlation functions of composite operators in N=4 super Yang-Mills theory.Comment: LaTex, 32 pages, 1 figure, discussion of correlation functions extended; some corrections made; references adde

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure

Collective coherence in planar semiconductor microcavities

Semiconductor microcavities, in which strong coupling of excitons to confined photon modes leads to the formation of exciton-polariton modes, have increasingly become a focus for the study of spontaneous coherence, lasing, and condensation in solid state systems. This review discusses the significant experimental progress to date, the phenomena associated with coherence which have been observed, and also discusses in some detail the different theoretical models that have been used to study such systems. We consider both the case of non-resonant pumping, in which coherence may spontaneously arise, and the related topics of resonant pumping, and the optical parametric oscillator.Comment: 46 pages, 12 figure

An X-ray investigation of the NGC346 field in the SMC (1) : the LBV HD5980 and the NGC346 cluster

We present results from a Chandra observation of the NGC346 cluster. This cluster contains numerous massive stars and is responsible for the ionization of N66, the most luminous HII region and the largest star formation region in the SMC. In this first paper, we will focus on the characteristics of the main objects of the field. The NGC346 cluster itself shows only relatively faint X-ray emission (with L_X^{unabs} ~ 1.5 times 10^{34} erg s^{-1}), tightly correlated with the core of the cluster. In the field also lies HD5980, a LBV star in a binary (or possibly a triple system) that is detected for the first time at X-ray energies. The star is X-ray bright, with an unabsorbed luminosity of L_X^{unabs} ~ 1.7 times 10^{34} erg s^{-1}, but needs to be monitored further to investigate its X-ray variability over a complete 19d orbital cycle. The high X-ray luminosity may be associated either with colliding winds in the binary system or with the 1994 eruption. HD5980 is surrounded by a region of diffuse X-ray emission, which is a supernova remnant. While it may be only a chance alignment with HD5980, such a spatial coincidence may indicate that the remnant is indeed related to this peculiar massive star.Comment: 12 pages, 9 figures (3 in jpg and 6 in ps), to be published in Ap

Collaborative Physical and Biological Dosimetry Studies for Neutron Capture Therapy at the RA-1 Research Reactor Facility

Initial physical dosimetry measurements have been completed using activation spectrometry and thermoluminiscent dosimeters to characterize the BNCT irradiation facility developed at the RA-1 research reactor operated by the Argentine National Atomic Energy Commission in Buenos Aires. Some biological scoping irradiations have also been completed using a small-animal (hamster) oral mucosa tumor model. Results indicate that the RA-1 neutron source produces useful dose rates but that some improvements in the initial configuration will be needed to optimize the spectrum for thermal-neutron BNCT research applications

Statistical mechanics of complex networks

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic

DNA Damage during G2 Phase Does Not Affect Cell Cycle Progression of the Green Alga Scenedesmus quadricauda

DNA damage is a threat to genomic integrity in all living organisms. Plants and green algae are particularly susceptible to DNA damage especially that caused by UV light, due to their light dependency for photosynthesis. For survival of a plant, and other eukaryotic cells, it is essential for an organism to continuously check the integrity of its genetic material and, when damaged, to repair it immediately. Cells therefore utilize a DNA damage response pathway that is responsible for sensing, reacting to and repairing damaged DNA. We have studied the effect of 5-fluorodeoxyuridine, zeocin, caffeine and combinations of these on the cell cycle of the green alga Scenedesmus quadricauda. The cells delayed S phase and underwent a permanent G2 phase block if DNA metabolism was affected prior to S phase; the G2 phase block imposed by zeocin was partially abolished by caffeine. No cell cycle block was observed if the treatment with zeocin occurred in G2 phase and the cells divided normally. CDKA and CDKB kinases regulate mitosis in S. quadricauda; their kinase activities were inhibited by Wee1. CDKA, CDKB protein levels were stabilized in the presence of zeocin. In contrast, the protein level of Wee1 was unaffected by DNA perturbing treatments. Wee1 therefore does not appear to be involved in the DNA damage response in S. quadricauda. Our results imply a specific reaction to DNA damage in S. quadricauda, with no cell cycle arrest, after experiencing DNA damage during G2 phase

Prioritization of gene regulatory interactions from large-scale modules in yeast

<p>Abstract</p> <p>Background</p> <p>The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources.</p> <p>Results</p> <p>Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes.</p> <p>Conclusion</p> <p>We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for further experimental studies.</p