Enhancing operational fault diagnosis by assessing multiple operational modes

Operating a modern technical system, such as a train or aircraft, calls for good organised engineering, operation and maintenance to keep the system in an optimal operational condition. Predictive maintenance is being studied and has as aim to identify errors early enough to still be able to propose a suitable solution before a real incident occurs. After all, technical problems in service may lead to delays or even interruptions of service due to extensive repair actions, such as the replacement of components. Often, predictive maintenance aims at recognising patterns in time series of monitored data and classifying these patterns as known conditions (faulty or correct). As such it provides a vital source of information for maintaining a healthy operational status. However, these approaches are still in their early phases and rely still heavily on skill and experience from the expert. In this paper, the use of self-organising maps for predictive maintenance is being discussed, applied to data of a jet engine. The aim of the study was to assess the usability of such approaches to real-life situations, assessing the learning and validation phases

A fault mode identification methodology based on self-organizing map

One of the main goals of predictive maintenance is to be able to trigger the right maintenance actions at the right moment in time building upon the monitoring of the health status of the concerned systems and their components. As such, it allows identifying incipient faults and forecasting the moment of failure at the earliest stage. Many different data-driven methods are used in such approaches (Naderi and Khorasani in 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE), Windsor, ON, IEEE, pp 1–6, 2017. https://doi.org/10.1109/ccece.2017.7946715; Sarkar et al. in J Eng Gas Turbines Power 1338(8):081602, 2011. https://doi.org/10.1115/1.4002877; Svärd et al. in Mech Syst Signal Process 45(1):170–192, 2014. https://doi.org/10.1016/j.ymssp.2013.11.002; Pourbabaee et al. Mech Syst Signal Process 76–77:136–156, 2016. https://doi.org/10.1016/j.ymssp.2016.02.023). This work uses the self-organizing maps (SOMs) or Kohonen map, thanks to its ability to emphasize underlying behavior such as fault modes. An automatic fault mode detection is presented based on a SOM network and the kernel density estimation with as less as possible prior knowledge. The different SOM development steps are presented and the suitable solutions proposed to structure the approach are accompanied by mathematical methods. The generated maps are then used with kernel density analysis to isolate fault modes on them. Finally, a methodology is presented to identify the different fault modes. The work is illustrated with an aircraft jet engines case study

An unsupervised approach for health index building and for similarity-based remaining useful life estimation

Predictive maintenance techniques attempt to trigger a maintenance intervention at the right moment by estimating the life expectation. Predictive maintenance is increasingly implemented by automated approaches able to perform diagnostics and prognostics. The main part of recent research in these approaches is focused in machine learning structures whose reasoning is implicit and cannot be easily explained. This poses a problem for their implementation in highly constrained area such as aeronautics. To overcome this constraint, explicit reasoning approaches such as the Similarity-Based Model (SBM) can be implemented. The SBM has been widely used for fault diagnostics and the remaining useful life (RUL) estimation, but the development of SBM includes tasks that often rely on high skilled experts. For instance, data reduction techniques required for SBM are often performed by experts judgment whose outcomes are not always consistent. The produced features from these techniques are used to build the Health Index that can be used to create the degradation trends that serve as a reference for the SBM. To overcome these difficulties, an automatic and unsupervised approach based on the Kernel Principal Component Analysis is proposed to enhance the Health Index creation. It preserves as much of the sensor information as possible improving the similarity-based RUL estimation. Additionally, when estimating the RUL of a system, the most similar degradation trends stored in the SBM library are used to compute individual RULs, the final RUL is obtained by a fusion rule technique that combines all these individual RULs into a consolidated value. For the fusion rule techniques, a self-adaptive method that does not rely on human expertize is proposed. This fusion rule can benefit of the accumulated knowledge over the SBM operation. This unsupervised approach to develop a SBM is validated with promising results against an equivalent and supervised algorithm that came out best in the 2008 prognostic health management challenge

Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics

The use of a modern technological system requires a good engineering approach, optimized operations, and proper maintenance in order to keep the system in an optimal state. Predictive maintenance focuses on the organization of maintenance actions according to the actual health state of the system, aiming at giving a precise indication of when a maintenance intervention will be necessary. Predictive maintenance is normally implemented by means of specialized computational systems that incorporate one of several models to fulfil diagnostics and prognostics tasks. As complexity of technological systems increases over time, single-model approaches hardly fulfil all functions and objectives for predictive maintenance systems. It is increasingly common to find research studies that combine different models in multi-model approaches to overcome complexity of predictive maintenance tasks, considering the advantages and disadvantages of each single model and trying to combine the best of them. These multi-model approaches have not been extensively addressed by previous review studies on predictive maintenance. Besides, many of the possible combinations for multi-model approaches remain unexplored in predictive maintenance applications; this offers a vast field of opportunities when architecting new predictive maintenance systems. This systematic survey aims at presenting the current trends in diagnostics and prognostics giving special attention to multi-model approaches and summarizing the current challenges and research opportunities

Un viaje al Cosmos en 52 semanas

230 p.Este libro se plantea como una serie de artículos que dibujan un recorrido por el Universo, desde lo más cercano a lo más distante. Constituye una herramienta útil y actualizada para los interesados en la astronomía, y combina el conocimiento básico con los resultados científicos más novedosos. La astrofísica constituye una ciencia viva y en permanente avance por ello nos encontramos con un Plutón que ya no es considerado planeta; con nuevos datos sobre la posible presencia de agua en Marte; con géiseres en Encelado, un pequeño satélite de Saturno que se creía geológicamente inactivo; con una miríada de nuevos planetas girando alrededor de otras estrellas; con, quizá, un nuevo tipo de agujero negro y fascinantes resultados sobre las explosiones cortas de rayos gamma, uno de los eventos más energéticos del Universo y, hasta hace poco, también uno de los más desconocidos; con la mision COROT, y otras, como BepiColombo, que ya se encuentran en su fase de desarrollo instrumental.Peer reviewe

Comparative and functional genomics of the protozoan parasite Babesia divergens highlighting the invasion and egress processes

Babesiosis is considered an emerging disease because its incidence has significantly increased in the last 30 years, providing evidence of the expanding range of this rare but potentially life-threatening zoonotic disease. Babesia divergens is a causative agent of babesiosis in humans and cattle in Europe. The recently sequenced genome of B. divergens revealed over 3,741 protein coding-genes and the 10.7-Mb high-quality draft become the first reference tool to study the genome structure of B. divergens. Now, by exploiting this sequence data and using new computational tools and assembly strategies, we have significantly improved the quality of the B. divergens genome. The new assembly shows better continuity and has a higher correspondence to B. bovis chromosomes. Moreover, we present a differential expression analysis using RNA sequencing of the two different stages of the asexual lifecycle of B. divergens: the free merozoite capable of invading erythrocytes and the intraerythrocytic parasite stage that remains within the erythrocyte until egress. Comparison of mRNA levels of both stages identified 1,441 differentially expressed genes. From these, around half were upregulated and the other half downregulated in the intraerythrocytic stage. Orthogonal validation by real-time quantitative reverse transcription PCR confirmed the differential expression. A moderately increased expression level of genes, putatively involved in the invasion and egress processes, were revealed in the intraerythrocytic stage compared with the free merozoite. On the basis of these results and in the absence of molecular models of invasion and egress for B. divergens, we have proposed the identified genes as putative molecular players in the invasion and egress processes. Our results contribute to an understanding of key parasitic strategies and pathogenesis and could be a valuable genomic resource to exploit for the design of diagnostic methods, drugs and vaccines to improve the control of babesiosis.This work was funded by grants from Ministerio de Economía y Competitividad from Spain (AGL2010-21774 and AGL2014-56193 R to EM and LMG). ES was awarded a research fellowship from Plan Estatal de Investigación Científica y Técnica y de Innovación, Ministerio de Economía y Competitividad, Spain (http://www.mineco.gob.es/portal/site/mineco/). Work in CL’s laboratory is funded by a grant from the National Institutes of Health (https://www.nih.gov/) NIH- 1R01HL140625-01. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptS

Functional Proteomics Characterization of the Role of SPRYD7 in Colorectal Cancer Progression and Metastasis

SPRY domain-containing protein 7 (SPRYD7) is a barely known protein identified via spatial proteomics as being upregulated in highly metastatic-to-liver KM12SM colorectal cancer (CRC) cells in comparison to its isogenic poorly metastatic KM12C CRC cells. Here, we aimed to analyze SPRYD7’s role in CRC via functional proteomics. Through immunohistochemistry, the overexpression of SPRYD7 was observed to be associated with the poor survival of CRC patients and with an aggressive and metastatic phenotype. Stable SPRYD7 overexpression was performed in KM12C and SW480 poorly metastatic CRC cells and in their isogenic highly metastatic-to-liver-KM12SM-and-to-lymph-nodes SW620 CRC cells, respectively. Upon upregulation of SPRYD7, in vitro and in vivo functional assays confirmed a key role of SPRYD7 in the invasion and migration of CRC cells and in liver homing and tumor growth. Additionally, transient siRNA SPRYD7 silencing allowed us to confirm in vitro functional results. Furthermore, SPRYD7 was observed as an inductor of angiogenesis. In addition, the dysregulated SPRYD7-associated proteome and SPRYD7 interactors were elucidated via 10-plex TMT quantitative proteins, immunoproteomics, and bioinformatics. After WB validation, the biological pathways associated with the stable overexpression of SPRYD7 were visualized. In conclusion, it was demonstrated here that SPRYD7 is a novel protein associated with CRC progression and metastasis. Thus, SPRYD7 and its interactors might be of relevance in identifying novel therapeutic targets for advanced CRC

Involvement of stanniocalcins in the deregulation of glycaemia in obese mice and type 2 diabetic patients

Las estanniocalcinas se expresan en el tejido del páncreas, y se sugirió una correlación directa entre la insulina circulante y las concentraciones de STC2 en el ser humano. Aquí, mostramos una correlación significativa entre STC1 y tanto la glucemia como la hemoglobina glicosilada entre los pacientes con DM2, mientras que los pacientes con DM2 que presentan los mayores valores de hemoglobina glicosilada exhibieron la menor expresión de STC2. Sin embargo, el tratamiento de los pacientes con fármacos antiglicémicos no modifica significativamente la expresión de ambas STC. Por otra parte, los ratones STC2-/- que mostraron sobrepeso neonatal y adulto presentaron además una glucemia desregulada cuando fueron alimentados con una dieta hipercalórica (pellet de cría, BP). Esta alteración es más evidente en las primeras etapas de la vida animal. La glucemia desregulada en estos ratones se confirmó mediante una prueba oral de glucosa. Además, los ratones STC2-/- presentan un aumento del tamaño del páncreas; así, el análisis histológico revela que los ratones WT responden a la dieta BP aumentando el tamaño de los islotes pancreáticos a través de la inducción de la división celular, y los ratones STC2-/- carecen de este mecanismo compensatorio. Contrariamente, los ratones alimentados con STC2-/- muestran un mayor número de islotes pero de tamaño similar a los alimentados con el pellet regular. El análisis histopatológico demuestra la alteración de la estructura de los tejidos y las infiltraciones de eritrocitos en los ratones STC2-/-, posiblemente debido al estrés evocado por la dieta BP. Por último, se observó una mayor inmunotinción de glucagón en el islote de los ratones STC2-/-, y el ensayo ELISA de glucagón confirmó el aumento del glucagón circulante. En resumen, presentamos pruebas del papel de los STC, principalmente el STC2, como posible marcador temprano durante el desarrollo de la diabetes mellitus.Stanniocalcins are expressed in the pancreas tissue, and it was suggested a direct correlation between circulating insulin and STC2 concentrations in human. Here, we show a significant correlation between STC1 and both glycaemia and glycosylated haemoglobin among DM2 patients, while DM2 patients who present the greatest glycosylated haemoglobin values exhibited the lowest STC2 expression. However, treatment of patients with antiglycaemic drugs does not significantly modify the expression of both STCs. On the other hand, STC2-/- mice that exhibited neonatal and adult overweight further presented deregulated glycaemia when they were feed with a hypercaloric diet (breeding pellet, BP). This alteration is more evident at the early stages of the animal life. Deregulated glycaemia in these mice was confirmed using glucose oral test. In addition, STC2-/- mice present enhanced pancreas size; thus, the histological analysis reveals that WT mice respond to BP diet by increasing the size of the pancreatic islets through inducing cell division, and STC2-/- mice lack this compensatory mechanism. Contrary, BP fed STC2-/- mice show enhanced number of islets but of similar size than those fed with regular pellet. Histopathological analysis demonstrates tissue structure disruption and erythrocytes infiltrations in STC2-/- mice, possibly due to the stress evoked by the BP diet. Finally, enhanced glucagon immunostaining was observed in the islet of STC2-/- mice, and the glucagon ELISA assay confirmed the increase in the circulating glucagon. Summarizing, we present evidence of the role of STCs, mainly STC2, as a possible early marker during development of diabetes mellitus.• Ministerio de Economía y Competitividad. Becas 2013‐45564C2‐1‐P, BFU‐2016‐74932‐C2‐1‐P • Programa Juan de la Cierva. Becas IJCI‐2015‐25665, JC‐2012‐ 2934 • Junta de Extremadura. Beca PRIIB16046peerReviewe

Effects and Mechanisms of Cognitive, Aerobic Exercise, and Combined Training on Cognition, Health, and Brain Outcomes in Physically Inactive Older Adults: The Projecte Moviment Protocol

Introduction: Age-related health, brain, and cognitive impairment is a great challenge in current society. Cognitive training, aerobic exercise and their combination have been shown to benefit health, brain, cognition and psychological status in healthy older adults. Inconsistent results across studies may be related to several variables. We need to better identify cognitive changes, individual variables that may predict the effect of these interventions, and changes in structural and functional brain outcomes as well as physiological molecular correlates that may be mediating these effects. Projecte Moviment is a multi-domain randomized trial examining the effect of these interventions applied 5 days per week for 3 months compared to a passive control group. The aim of this paper is to describe the sample, procedures and planned analyses. Methods: One hundred and forty healthy physically inactive older adults will be randomly assigned to computerized cognitive training (CCT), aerobic exercise (AE), combined training (COMB), or a control group. The intervention consists of a 3 month home-based program 5 days per week in sessions of 45 min. Data from cognitive, physical, and psychological tests, cardiovascular risk factors, structural and functional brain scans, and blood samples will be obtained before and after the intervention. Results: Effects of the interventions on cognitive outcomes will be described in intention-to-treat and per protocol analyses. We will also analyze potential genetic, demographic, brain, and physiological molecular correlates that may predict the effects of intervention, as well as the association between cognitive effects and changes in these variables using the per protocol sample. Discussion: Projecte Moviment is a multi-domain intervention trial based on prior evidence that aims to understand the effects of CCT, AE, and COMB on cognitive and psychological outcomes compared to a passive control group, and to determine related biological correlates and predictors of the intervention effects.Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03123900

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

17 Pág.  Departamento de ​Mejora Genética Animal (INIA)The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.This research was financed by the METALGEN project (RTA2015-00022-C03) from the national plan for research, development, and innovation 2013–2020 and the Department of Economic Development and Competitiveness (Madrid, Spain).Peer reviewe