Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

Dynamics of Viral RNA Synthesis during Measles Virus Infection

We propose a reference model of the kinetics of a viral RNA-dependent RNA polymerase (vRdRp) activities and its regulation during infection of eucaryotic cells. After measles virus infects a cell, mRNAs from all genes immediately start to accumulate linearly over the first 5 to 6 h and then exponentially until approximately 24 h. The change from a linear to an exponential accumulation correlates with de novo synthesis of vRdRp from the incoming template. Expression of the virus nucleoprotein (N) prior to infection shifts the balance in favor of replication. Conversely, inhibition of protein synthesis by cycloheximide favors the latter. The in vivo elongation speed of the viral polymerase is approximately 3 nucleotides/s. A similar profile with fivefold-slower kinetics can be obtained using a recombinant virus expressing a structurally altered polymerase. Finally, virions contain only encapsidated genomic, antigenomic, and 5'-end abortive replication fragment RNAs.

Dynamics and Function of Langerhans Cells In Vivo: Dermal Dendritic Cells Colonize Lymph Node Areas Distinct from Slower Migrating Langerhans Cells

Langerhans cells (LCs) are prominent dendritic cells (DCs) in epithelia, but their role in immunity is poorly defined. To track and discriminate LCs from dermal DCs in vivo, we developed knockin mice expressing enhanced green fluorescent protein (EGFP) under the control of the langerin (CD207) gene. By using vital imaging, we showed that most EGFP(+) LCs were sessile under steady-state conditions, whereas skin inflammation induced LC motility and emigration to lymph nodes (LNs). After skin immunization, dermal DCs arrived in LNs first and colonized areas distinct from slower migrating LCs. LCs reaching LNs under steady-state or inflammatory conditions expressed similar levels of costimulatory molecules. Langerin and EGFP were also expressed on thymic DCs and on blood-derived, CD8alpha(+) DCs from all secondary lymphoid organs. By using a similar knockin strategy involving a diphtheria toxin receptor (DTR) fused to EGFP, we demonstrated that LCs were dispensable for triggering hapten-specific T cell effectors through skin immunization.