On a Service-Oriented Approach for an Engineering Knowledge Desktop

Increasingly, manufacturing companies are shifting their focus from selling products to providing services. As a result, when designing new products, engineers must increasingly consider the life cycle costs in addition to any design requirements. To identify possible areas of concern, designers are required to consult existing maintenance information from identical products. However, in a large engineering company, the amount of information available is significant and in wide range of formats. This paper presents a prototype knowledge desktop suitable for the design engineer. The Engineering Knowledge Desktop analyses and suggests relevant information from ontologically marked-up heterogeneous web resources. It is designed using a Service-Oriented Architecture, with an ontology to mediate between Web Services. It has been delivered to the user community for evaluation

A novel method of combining blood oxygenation and blood flow sensitive magnetic resonance imaging techniques to measure the cerebral blood flow and oxygen metabolism responses to an unknown neural stimulus.

Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO(2)) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged

Data Mining to Support Engineering Design Decision

The design and maintenance of an aero-engine generates a significant amount of documentation. When designing new engines, engineers must obtain knowledge gained from maintenance of existing engines to identify possible areas of concern. Firstly, this paper investigate the use of advanced business intelligence tenchniques to solve the problem of knowledge transfer from maintenance to design of aeroengines. Based on data availability and quality, various models were deployed. An association model was used to uncover hidden trends among parts involved in maintenance events. Classification techniques comprising of various algorithms was employed to determine severity of events. Causes of high severity events that lead to major financial loss was traced with the help of summarization techniques. Secondly this paper compares and evaluates the business intelligence approach to solve the problem of knowledge transfer with solutions available from the Semantic Web. The results obtained provide a compelling need to have data mining support on RDF/OWL-based warehoused data

Benefit of Apabetalone on Plasma Proteins in Renal Disease.

Introduction:Apabetalone, a small molecule inhibitor, targets epigenetic readers termed BET proteins that contribute to gene dysregulation in human disorders. Apabetalone has in vitro and in vivo anti-inflammatory and antiatherosclerotic properties. In phase 2 clinical trials, this drug reduced the incidence of major adverse cardiac events in patients with cardiovascular disease. Chronic kidney disease is associated with a progressive loss of renal function and a high risk of cardiovascular disease. We studied the impact of apabetalone on the plasma proteome in patients with impaired kidney function. Methods:Subjects with stage 4 or 5 chronic kidney disease and matched controls received a single dose of apabetalone. Plasma was collected for pharmacokinetic analysis and for proteomics profiling using the SOMAscan 1.3k platform. Proteomics data were analyzed with Ingenuity Pathway Analysis to identify dysregulated pathways in diseased patients, which were targeted by apabetalone. Results:At baseline, 169 plasma proteins (adjusted P value <0.05) were differentially enriched in renally impaired patients versus control subjects, including cystatin C and β2 microglobulin, which correlate with renal function. Bioinformatics analysis of the plasma proteome revealed a significant activation of 42 pathways that control immunity and inflammation, oxidative stress, endothelial dysfunction, vascular calcification, and coagulation. At 12 hours postdose, apabetalone countered the activation of pathways associated with renal disease and reduced the abundance of disease markers, including interleukin-6, plasminogen activator inhibitor-1, and osteopontin. Conclusion:These data demonstrated plasma proteome dysregulation in renally impaired patients and the beneficial impact of apabetalone on pathways linked to chronic kidney disease and its cardiovascular complications

PRIMUS: An observationally motivated model to connect the evolution of the AGN and galaxy populations out to z~1

We present an observationally motivated model to connect the AGN and galaxy populations at 0.2<z<1.0 and predict the AGN X-ray luminosity function (XLF). We start with measurements of the stellar mass function of galaxies (from the Prism Multi-object Survey) and populate galaxies with AGNs using models for the probability of a galaxy hosting an AGN as a function of specific accretion rate. Our model is based on measurements indicating that the specific accretion rate distribution is a universal function across a wide range of host stellar mass with slope gamma_1 = -0.65 and an overall normalization that evolves with redshift. We test several simple assumptions to extend this model to high specific accretion rates (beyond the measurements) and compare the predictions for the XLF with the observed data. We find good agreement with a model that allows for a break in the specific accretion rate distribution at a point corresponding to the Eddington limit, a steep power-law tail to super-Eddington ratios with slope gamma_2 = -2.1 +0.3 -0.5, and a scatter of 0.38 dex in the scaling between black hole and host stellar mass. Our results show that samples of low luminosity AGNs are dominated by moderately massive galaxies (M* ~ 10^{10-11} M_sun) growing with a wide range of accretion rates due to the shape of the galaxy stellar mass function rather than a preference for AGN activity at a particular stellar mass. Luminous AGNs may be a severely skewed population with elevated black hole masses relative to their host galaxies and in rare phases of rapid accretion.Comment: 11 pages, 5 figures, emulateapj format, updated to match version accepted for publication in Ap

PRIMUS + DEEP2: Clustering of X-ray, Radio and IR-AGN at z~0.7

We measure the clustering of X-ray, radio, and mid-IR-selected active galactic nuclei (AGN) at 0.2 < z < 1.2 using multi-wavelength imaging and spectroscopic redshifts from the PRIMUS and DEEP2 redshift surveys, covering 7 separate fields spanning ~10 square degrees. Using the cross-correlation of AGN with dense galaxy samples, we measure the clustering scale length and slope, as well as the bias, of AGN selected at different wavelengths. Similar to previous studies, we find that X-ray and radio AGN are more clustered than mid-IR-selected AGN. We further compare the clustering of each AGN sample with matched galaxy samples designed to have the same stellar mass, star formation rate, and redshift distributions as the AGN host galaxies and find no significant differences between their clustering properties. The observed differences in the clustering of AGN selected at different wavelengths can therefore be explained by the clustering differences of their host populations, which have different distributions in both stellar mass and star formation rate. Selection biases inherent in AGN selection, therefore, determine the clustering of observed AGN samples. We further find no significant difference between the clustering of obscured and unobscured AGN, using IRAC or WISE colors or X-ray hardness ratio.Comment: Accepted to ApJ. 23 emulateapj pages, 15 figures, 4 table

Geodesic Deviation in Kaluza-Klein Theories

We study in detail the equations of the geodesic deviation in multidimensional theories of Kaluza-Klein type. We show that their 4-dimensional space-time projections are identical with the equations obtained by direct variation of the usual geodesic equation in the presence of the Lorentz force, provided that the fifth component of the deviation vector satisfies an extra constraint derived here.Comment: 5 pages, Revtex, 1 figure. To appear in Phys. Rev. D (Brief Report