Gene- and pathway-based genomics of breast cancer and type 2 diabetes in African American women

Women of African ancestry (AA) experience a greater burden from breast cancer and type 2 diabetes compared to women of European ancestry. Some of the racial disparities observed for these diseases may be explained by AA-specific genetic risk variants. The projects conducted here sought to discover risk variants in AA women for overall and subtype-specific breast cancer and for type 2 diabetes using pathway- and gene-based analytic approaches. Project 1 evaluated 170,812 mostly rare variants across the exome in 3629 breast cancer cases (1093 estrogen receptor negative (ER-), 1968 ER+, 568 ER unknown) and 4658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. Gene-based analyses found ER- associations with PDE4D (previously identified in GWAS) and FBXL22 (novel), based on very small counts at extremely rare SNPs. Project 2 evaluated common SNPs in 308 genes in hormone pathways using 3663 breast cancer cases (1098 ER-, 1983 ER+, 582 ER unknown) and 4687 controls from AMBER. Gene-based and single SNP analyses identified eight genes (CALM2, CETP, NR0B1, IGF2R, CYP1B1, PGR, MAPK3, and MAP3K1) that contained common variants associated with overall or subtype-specific breast cancer after gene-level correction for multiple testing. Project 3 evaluated common SNPs in 69 genes involved in the Wnt pathway using 2632 type 2 diabetes cases and 2596 controls from the Black Women’s Health Study. Gene-based and single SNP analyses were run, and an association was observed between the PSMD2 gene region and type 2 diabetes. Association data on a subset of the top PSMD2 SNPs were available from a large, independent AA sample; associations were in the same direction, but weak and not statistically significant. We also identified a TCF7L2 SNP that may represent a novel, independent association signal seen only in AA populations. Many of the SNPs identified in the present research are more common in AA populations, possibly explaining their lack of discovery by European ancestry genome-wide association studies. Replication of the associations we observed using independent AA samples is necessary. Future studies should consider the entire gene regions identified in our research rather than focusing solely on the specific variants highlighted

Integrated control-system design via generalized LQG (GLQG) theory

Thirty years of control systems research has produced an enormous body of theoretical results in feedback synthesis. Yet such results see relatively little practical application, and there remains an unsettling gap between classical single-loop techniques (Nyquist, Bode, root locus, pole placement) and modern multivariable approaches (LQG and H infinity theory). Large scale, complex systems, such as high performance aircraft and flexible space structures, now demand efficient, reliable design of multivariable feedback controllers which optimally tradeoff performance against modeling accuracy, bandwidth, sensor noise, actuator power, and control law complexity. A methodology is described which encompasses numerous practical design constraints within a single unified formulation. The approach, which is based upon coupled systems or modified Riccati and Lyapunov equations, encompasses time-domain linear-quadratic-Gaussian theory and frequency-domain H theory, as well as classical objectives such as gain and phase margin via the Nyquist circle criterion. In addition, this approach encompasses the optimal projection approach to reduced-order controller design. The current status of the overall theory will be reviewed including both continuous-time and discrete-time (sampled-data) formulations

A new methodology for network scale simulation of emerging power line communication standards

This paper presents the development of a new methodology for the simulation of Power Line Communication (PLC) within the popular Electromagnetic Transients Programme-Alternative Transients Programme (EMTP-ATP). As a first application, the comparative performance of the emerging Orthogonal Frequency Division Multiplexing (OFDM) based Prime and G3-PLC narrowband standards is investigated. Models of both standards have been created within the EMTP-ATP and simulations performed using frequency dependent line models and realistic transformer models as terminations. It is observed that both standards are severely affected by the highly frequency selective nature of the MV power line channel and a more considered choice of OFDM parameters may be necessary for optimal performance on MV networks

Texture measures for segmentation

Includes bibliographical references (p. 67-72).Texture is an important visual cue in both human and computer vision. Segmenting images into regions of constant texture is used in many applications. This work surveys a wide range of texture descriptors and segmentation methods to determine the state of the art in texture segmentation. Two types of texture descriptors are investigated: filter bank based methods and local descriptors. Filter banks deconstruct an image into several bands, each of which emphasises areas of the image with different properties. Textons are an adaptive histogram method which describes the distribution of typical feature vectors. Local descriptors calculate features from smaller neighbourhoods than filter banks. Some local descriptors calculate a scale for their local neighbourhood to achieve scale invariance. Both local and global segmentation methods are investigated. Local segmentation methods consider each pixel in isolation. Global segmentation methods penalise jagged borders or fragmented regions in the segmentation. Pixel labelling and border detection methods are investigated. Methods for measuring the accuracy of segmentation are discussed. Two data sets are used to test the texture segmentation algorithms. The Brodatz Album mosaics are composed of grayscale texture images from the Brodatz Album. The Berkeley Natural Images data set has 300 colour images of natural scenes. The tests show that, of the descriptors tested, filter bank based textons are the best texture descriptors for grayscale images. Local image patch textons are best for colour images. Graph cut segmentation is best for pixel labelling problems and edge detection with regular borders. Non-maxima suppression is best for edge detection with irregular borders. Factors affecting the performance of the algorithms are investigated

Non-contact measurement and analysis of trapped charge decay rates for cable line switching transients

During reclosure of 275 kV cable circuits used for voltage control, excessive overvoltages were observed on the network. Such events cause onerous and costly failures. Transient simulations have shown that the normal voltage on its own cannot generate such excessive switching overvoltages. Initial investigations by the network operator pointed towards trapped charge on the unearthed as the cause of the failures. Measurement of these trapped charge voltages and their slow decay without interfering with the charge has, to the author’s knowledge, not been done before in an operational substation. This work introduces a technique to measure trapped charge at a 275 kV substation using the Electrostatic Field Mill. Since the electric field is a proxy measurement of surface voltage, field mills can also be used to measure voltage. In this paper, an on-site substation measurement setup using an electrostatic field mill has been developed for the non-contact measurement of trapped charge voltage on a 275 kV underground cable circuit following switching operations at a National Grid substation. Results of field measurements within the substation and laboratory experimentation are discussed. It is demonstrated that with adequate calibration, achieved by using the known pre-switching power frequency steady state voltage, the slowly decaying DC voltage caused by the cable trapped charge can be measured using this non-contact technique. The correlation between the instantaneous time constant and the relative humidity is also analysed

Organic Evolution and the Capability Maturity of Business Intelligence

With the emergence of a new form of competition based on the extensive use of analytics, data, and subsequent decisionmaking, business intelligence (BI) has become a dominant platform for delivering solutions. The notion of gaining and sustaining competitive advantage through the use of complex analysis and data-intensive technologies has changed the way organizations manage themselves and compete in the marketplace. Initially, similar to other strategic technologies, BI will evolve or change depending on organizational needs and maturity. This suggests that process-oriented, descriptive, maturity models like the Capability Maturity Model apply. Despite the significance of BI, little attention has been given to examining the natural progression of business intelligence adoption and maturation within organizations. This is a concept paper presenting a model describing the relationship between evolution and the levels described by capability maturity. The proposed conceptual model is illustrated through the examination of a large, national, non-profit organization

A chirp spread spectrum modulation scheme for robust power line communication

This paper proposes the use of a LoRa like chirp spread spectrum physical layer as the basis for a new Power Line Communication modulation scheme suited for low-bandwidth communication. It is shown that robust communication can be established even in channels exhibiting extreme multipath interference, impulsive noise and low SNR (-40dB), with synchronisation requirements relaxed compared to conventional LoRa. ATP-EMTP simulations using frequency dependent line and transformer models, and simulations using artificial Rayleigh channels demonstrate the effectiveness of the new scheme in providing load data from LV feeders back to the MV primary substation. Our results demonstrate error-free communication at SNRs of -40dB, and can be further improved by trading-off data rate. We further present experimental results based on a Field Programmable Gate Array hardware implementation which match the simulated performance

A sub-μs accuracy GPS alternative using electrical transmission grids as precision timing networks

It is widely recognised that over-reliance on GNSS (e.g GPS) for time synchronisation represents an acute threat to modern society, and a diversity of alternatives are required to mitigate the threat of an outage. This paper proposes a GNSS alternative using time dissemination over national scale transmission or distribution networks. The method utilises the same frequency bandwidth and coupling technology as established power line carrier technology in conjunction with modern chirp Spread Spectrum modulation. The basis of the method is the transmission of a time synchronised chirp from a central substation, coupled into the aerial modes of the transmission line. During GNSS operation, all substations can estimate the time of flight by correlating the received chirp with a time-synchronised local copy. During GNSS outage, time sychronisation to the central substation is maintained by correcting for the precalculated time of flight. It is shown that recent advances in chirp spread spectrum allow for a computationally efficient algorithm with the capacity to compute hundreds of thousand of chirp correlations every second, facilitating timing accuracy which satisfies the majority of smart grid applications. ATP-EMTP simulations of the method on large transmission networks demonstrate sub-μs timing accuracy even in the presence of low SNR and impulsive noise. An FPGA prototype demonstrates experimentally sub-μs accuracy for time dissemination over a distance of 700 m. Averaging over time is shown to facilitate satisfactory performance down to -20dB, which could extend the range of the system to a national scale and a time dissemination network invulnerable to wireless spoofing and jamming attack vectors