13 resultados para Root cause analysis

em Cambridge University Engineering Department Publications Database


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BACKGROUND: After investing significant amounts of time and money in conducting formal risk assessments, such as root cause analysis (RCA) or failure mode and effects analysis (FMEA), healthcare workers are left to their own devices in generating high-quality risk control options. They often experience difficulty in doing so, and tend toward an overreliance on administrative controls (the weakest category in the hierarchy of risk controls). This has important implications for patient safety and the cost effectiveness of risk management operations. This paper describes a before and after pilot study of the Generating Options for Active Risk Control (GO-ARC) technique, a novel tool to improve the quality of the risk control options generation process. OUTCOME MEASURES: The quantity, quality (using the three-tiered hierarchy of risk controls), variety, and novelty of risk controls generated. RESULTS: Use of the GO-ARC technique was associated with improvement on all measures. CONCLUSIONS: While this pilot study has some notable limitations, it appears that the GO-ARC technique improved the risk control options generation process. Further research is needed to confirm this finding. It is also important to note that improved risk control options are a necessary, but not sufficient, step toward the implementation of more robust risk controls.

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Modern high performance motorcycles often employ a steering damper producing a moment that opposes the angular velocity of the steering assembly relative to the main frame. When modeling the motorcycle in a conventional manner, the steering damper is included as an integral part of the machine. The reduction in the wobble-mode frequency is caused by the effective increase in the steering system's moment of inertia. The compensators show the potential to significantly improve the damping of both wobble and weave modes simultaneously. The dynamic characteristics of high-performance motorcycles can be improved by replacing the conventional steering damper with a passive mechanical steering compensator. The design methodology adopted uses Nyquist frequency response ideas, root-locus analysis and loop-shaping design to obtain a preliminary choice of parameters.

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Campylobacter jejuni is a prevalent cause of food-borne diarrhoeal illness in humans. Understanding of the physiological and metabolic capabilities of the organism is limited. We report a detailed analysis of the C. jejuni growth cycle in batch culture. Combined transcriptomic, phenotypic and metabolic analysis demonstrates a highly dynamic 'stationary phase', characterized by a peak in motility, numerous gene expression changes and substrate switching, despite transcript changes that indicate a metabolic downshift upon the onset of stationary phase. Video tracking of bacterial motility identifies peak activity during stationary phase. Amino acid analysis of culture supernatants shows a preferential order of amino acid utilization. Proton NMR (1H-NMR) highlights an acetate switch mechanism whereby bacteria change from acetate excretion to acetate uptake, most probably in response to depletion of other substrates. Acetate production requires pta (Cj0688) and ackA (Cj0689), although the acs homologue (Cj1537c) is not required. Insertion mutants in Cj0688 and Cj0689 maintain viability less well during the stationary and decline phases of the growth cycle than wild-type C. jejuni, suggesting that these genes, and the acetate pathway, are important for survival.

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Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community. © 2011 SGM.

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Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Empirically measured rankings are often incomplete, i.e. different numbers of filled rank positions cause heterogeneity in the data. We propose a mixture approach for clustering of heterogeneous rank data. Rankings of different lengths can be described and compared by means of a single probabilistic model. A maximum entropy approach avoids hidden assumptions about missing rank positions. Parameter estimators and an efficient EM algorithm for unsupervised inference are derived for the ranking mixture model. Experiments on both synthetic data and real-world data demonstrate significantly improved parameter estimates on heterogeneous data when the incomplete rankings are included in the inference process.

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An implementation of the inverse vector Jiles-Atherton model for the solution of non-linear hysteretic finite element problems is presented. The implementation applies the fixed point method with differential reluctivity values obtained from the Jiles-Atherton model. Differential reluctivities are usually computed using numerical differentiation, which is ill-posed and amplifies small perturbations causing large sudden increases or decreases of differential reluctivity values, which may cause numerical problems. A rule based algorithm for conditioning differential reluctivity values is presented. Unwanted perturbations on the computed differential reluctivity values are eliminated or reduced with the aim to guarantee convergence. Details of the algorithm are presented together with an evaluation of the algorithm by a numerical example. The algorithm is shown to guarantee convergence, although the rate of convergence depends on the choice of algorithm parameters. © 2011 IEEE.

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At low mass flow rates, axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past---primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focused on the level of irregularity in the blade passing signature in the rotor tip region. In general, the irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of flow irregularity, but little effort has been made to characterize the irregularity itself, or to understand its underlying cause. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance size and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity that accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether the irregularity observed in the prestall flow field is due to random turbulence or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity would be difficult to implement in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. © 2013 American Society of Mechanical Engineers.

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Humans appear to be sensitive to relative small changes in their surroundings. These changes are often initially perceived as irrelevant, but they can cause significant changes in behavior. However, how exactly people's behavior changes is often hard to quantify. A reliable and valid tool is needed in order to address such a question, ideally measuring an important point of interaction, such as the hand. Wearable-body-sensor systems can be used to obtain valuable, behavioral information. These systems are particularly useful for assessing functional interactions that occur between the endpoints of the upper limbs and our surroundings. A new method is explored that consists of computing hand position using a wearable sensor system and validating it against a gold standard reference measurement (optical tracking device). Initial outcomes related well to the gold standard measurements (r = 0.81) showing an acceptable average root mean square error of 0.09 meters. Subsequently, the use of this approach was further investigated by measuring differences in motor behavior, in response to a changing environment. Three subjects were asked to perform a water pouring task with three slightly different containers. Wavelet analysis was introduced to assess how motor consistency was affected by these small environmental changes. Results showed that the behavioral motor adjustments to a variable environment could be assessed by applying wavelet coherence techniques. Applying these procedures in everyday life, combined with correct research methodologies, can assist in quantifying how environmental changes can cause alterations in our motor behavior.

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The development of infrastructure in major cities often involves tunnelling, which can cause damage to existing structures. Therefore, these projects require a careful prediction of the risk of settlement induced damage. The simplified approach of current methods cannot account for three-dimensional structural aspects of buildings, which can result in an inaccurate evaluation of damage. This paper investigates the effect of the building alignment with the tunnel axis on structural damage. A three-dimensional, phased, fully coupled finite element model with non-linear material properties is used as a tool to perform a parametric study. The model includes the simulation of the tunnel construction process, with the tunnel located adjacent to a masonry building. Three different type of settlements are included (sagging, hogging and a combination of them), with seven different increasing angles of the building with respect to the tunnel axis. The alignment parameter is assessed, based on the maximum occurring crack width, measured in the building. Results show a significant dependency of the final damage on the building and tunnel alignment.