8,814 research outputs found
University of Washington football player, Vernon "Bull" Bellman, between 1923 and 1926
No full textWritten on photo: "Bull" Me Ra.
PH Coll 115.35
Towards distributed adaptive control for road traffic junction signals using learning classifier systems
No full textThis chapter considers an approach to distributed traffic responsive signal controlusing Learning Classifier Systems (Holland, 1976). The intention is to accommodaterealistic kinds of detector data and wide ranges of candidate performance criteria fortraffic management in a fully flexible manner. The approach to achieving this is to useevolutionary computing (eg Holland, 1975) and reinforcement learning (eg Sutton andBarto, 1998) with performance fed back from microscopic traffic simulations: thisapproach has the advantage that it is not specific to any particular objective or form ofprimary data. The purpose of this work is to develop an approach to distributedoptimisation that can achieve good traffic performance flexibly according to any on arange of possible criteria using data from existing traffic detectors. Here each junctionin a road network is controlled by a Learning Classifier System using only locallyavailable input and performance data; a multi-agent approach is proposed.Learning Classifier Systems (LCS) can be used for optimisation in a way thatoffers substantial promise for application in traffic-responsive signal control systemswhere the way in which the control responds to variations in traffic flows can beadapted according to measured conditions. This is important in order to achieve trafficcontrol that is sufficiently flexible to respond rapidly when traffic conditions change ina fundamental way, as occurs at the start of a peak period, without being undulysensitive to short-term variations in flow. The expectation is that this will be possibleby their use of both reinforcement learning and evolutionary computing techniques.Furthermore, they offer the automated rule development of neural networks togetherwith the transparency of production system rules.The importance of this approach for traffic control is that it offers a means bywhich signal control strategies can be developed directly according to theirperformance, evaluated using detailed microscopic simulation as opposed to thatestimated from formulae that have been adopted on grounds of analytical convenience.This closed-loop approach to development of control strategies offers severaladvantages over the use of traditional explicit optimisation formulations. Theseinclude flexibility in respect of objectives so that multiple and varying needs can beaccommodated, ability to use various different kinds of detector data according to theiravailability, and freedom from dependence on a single explicit evaluation formula thatis intended to embody the whole of a traffic model. This final point has been found tobe especially important in recent research work where certain fine details of themodels used have been found to have an unexpectedly strong influence onperformance
The influence of toughening-particles in CFRPs on low velocity impact damage resistance performance
Get PDFThe role of particle-toughening for increasing impact damage resistance in carbon fibre reinforced polymer (CFRP) composites was investigated. Five carbon fibre reinforced systems consisting of four particle-toughened matrices and one system containing no toughening particles were subjected to low velocity impacts ranging from 25 J to 50 J to establish the impact damage resistance of each material system. Synchrotron radiation computed tomography (SRCT) enabled a novel approach for damage assessment and quantification. Toughening mechanisms were detected in the particle-toughened systems consisting of particle–resin debonding, crack-deflection and crack-bridging. Quantification of the bridging behaviour, increase in crack path length and roughness was undertaken. Out of the three toughening mechanisms measured, particle systems exhibited a larger extent of bridging suggesting a significant contribution of this toughening mechanism compared to the system with no particle
Rayleigh number dependence of the Archimedes number dependent large-scale flow structure formation in mixed convection
No full textWe report on experimental investigations of large-scale flow structure formation in mixed convection. We characterize the flow field by measuring the velocity fields within a rectangular model room using 2D2C PIV. The control parameters are the Reynolds number Re, the Rayleigh number Ra and the Prandtl number Pr. All parameters are linked through the Archimedes number Ar. In 6.4x10-2 ≤ Ar ≤ 1.39x101, 4.2x103 ≤ Re ≤ 6.35x104 and Ra = 3.1x107, Ra = 1.8x108 and Pr = 0.713 we found flow 3 different flow structures. While keeping Ra and Pr constant and varying Ar through Re variations, we found an Ar dependence of the largescale flow structure formation within 6.4x10-2 ≤ Ar ≤ 1.39x101. Furthermore, we found a Ra dependence of the structure formation, which shifts the transition points between the structures to higher Archimedes numbers and reduces the mean velocities within the investigated domain
Reynolds numbers near the ultimate state of turbulent Rayleigh-Bénard convection
No full textWe report on measurements of the mean-flow Reynolds number ReU and the rms fluctuation Reynolds number ReV in turbulent Rayleigh-Bénard convection as a function of the Rayleigh number Ra for 4 x 1011 < Ra < 2 1014 and Pr ' 0:8. Both can be described by the same power law with an effective exponent = 0:44, in agreement with predictions for ReU but in disagreement with predictions for ReV
Logarithmic variance profiles and the corresponding f-1 spectra of temperature fluctuations in turbulent Rayleigh-Bénard convection
No full textWe report experimental results for the temperature variance 2(z) and the corresponding frequency spectra P(f) in turbulent Rayleigh-Bénard convection (RBC) in a cylindrical sample of aspect ratioT= D/L = 1:00 (D = 1:12 m is the diameter and L = 1:12 m the height). The measurements were conducted in the Rayleigh-number range 1011 < Ra < 1:35 1014 and Pr ' 0:8. For Ra = 1:35x1014, 2(z) could be described well by a logarithmic dependence on the vertical position z in a range of z 1 < z < z 2 with z 1 ' 70 and z 2 = 0:1L. Here L=(2Nu) is the thickness of a thin thermal sublayer adjacent to the horizontal plate where the heat flux (denoted by the Nusselt number Nu) is carried mostly by thermal diffusion. In the log layer, we found that the temperature spectra had a significant frequency range over which P(f) f with close to 1. As Ra decreased, increased so that the log layer became thinner. At Ra = 2:05 1011, z 2 < z 1 and therefore there was no range for a log layer. Correspondingly, the temperature spectrum near the horizontal plate did not have the f1 scaling form either
Genetic Relationship Between the United States and Canadian Holstein Bull Populations
Get PDFThe average additive genetic relationship and degree of connectedness between American and Canadian Holstein AI bull populations were estimated. This project was undertaken to determine the feasibility of a joint United States-Canadian sire evaluation to estimate genetic base differences between the two countries‘Holstein bull populations. Data were provided by USDA and Agriculture Canada for bulls evaluated in each country. Bulls were designated as American, Canadian, or dual national origin based on their country of registration and national origin of their parents. A total of 13,079 American, 1683 Canadian, and 256 dual origin bulls were included in the inverse relationship matrix. When both sire and maternal grandsire relationships were included in the matrix, there were 174 disconnected groups; however, 99% of the American bulls and 97% of the Canadian bulls were in a single group. The average aij between the American and Canadian population was 4.6×10−5. Despite the low average additive relationship between the two national populations, the high degree of connectedness in the inverse relationship matrix, when using both sire and maternal grandsire relationships, suggests sufficient genetic ties between the two populations to conduct a meaningful joint sire evaluation
Common genetic variants associated with disease from genome-wide association studies are mutually exclusive in prostate cancer and rheumatoid arthritis
Get PDFObjectives: To investigate if potential common pathways exist for the pathogenesis of autoimmune disease and prostate cancer (PrCa). To ascertain if the single nucleotide polymorphisms (SNPs) reported by genome-wide association studies (GWAS) as being associated with susceptibility to PrCa are also associated with susceptibility to the autoimmune disease rheumatoid arthritis (RA).
Materials and Methods: The original Wellcome Trust Case Control Consortium (WTCCC) UK RA GWAS study was expanded to include a total of 3221 cases and 5272 controls.
In all, 37 germline autosomal SNPs at genome-wide significance associated with PrCa risk were identified from a UK/Australian PrCa GWAS. Allele frequencies were compared for these 37 SNPs between RA cases and controls using a chi-squared trend test and corrected for multiple testing (Bonferroni).
Results: In all, 33 SNPs were able to be analysed in the RA dataset. Proxies could not be located for the SNPs in 3q26, 5p15 and for two SNPs in 17q12. After applying a Bonferroni correction for the number of SNPs tested, the SNP mapping to CCHCR1 (rs130067) retained statistically significant evidence for association (P = 6 × 10–4; odds ratio [OR] = 1.15, 95% CI: 1.06–1.24); this has also been associated with psoriasis.
However, further analyses showed that the association of this allele was due to confounding by RA-associated HLA-DRB1 alleles.
Conclusions: There is currently no evidence that SNPs associated with PrCa at genome-wide significance are associated with the development of RA. Studies like this are important in determining if common genetic risk profiles might predispose individuals to many diseases, which could have implications for public health in terms of screening and chemoprevention
Lagrangian Raylaigh-Bénard convection
No full textUsing passive tracers as sensors, we obtain Lagrangian measurements of tracers position, velocity and temperature in Rayleigh-Bénard convection at Ra=10^7-10^9. We report on statistics of temperature, velocity, and heat transport (Nusselt number). We observe that the Nusselt number is characterized by a largely intermittent behavior, likely due to the interaction of temperature with turbulent velocity fluctuations
Bayesian variable selection in modelling geographical heterogeneity in malaria transmission from sparse data : an application to Nouna Health and Demographic Surveillance System (HDSS) data, Burkina Faso
Get PDFQuantification of malaria heterogeneity is very challenging, partly because of the underlying characteristics of mosquitoes and also because malaria is an environmentally driven disease. Furthermore, in order to assess the spatial and seasonal variability in malaria transmission, vector data need to be collected repeatedly over time (at fixed geographical locations). Measurements collected at locations close to each other and over time tend to be correlated because of common exposures such as environmental or climatic conditions. Non- spatial statistical methods, when applied to analyze such data, may lead to biased estimates. We developed rigorous methods for analyzing sparse and spatially correlated data. We applied Bayesian variable selection to identify the most important predictors as well as the elapsing time between climate suitability and changes in entomological indices.; Bayesian geostatistical zero-inflated binomial and negative binomial models including harmonic seasonal terms, temporal trends and climatic remotely sensed proxies were applied to assess spatio-temporal variation of sporozoite rate and mosquito density in the study area. Bayesian variable selection was employed to determine the most important climatic predictors and elapsing (lag) time between climatic suitability and malaria transmission. Bayesian kriging was used to predict mosquito density and sporozoite rate at unsampled locations. These estimates were converted to covariate and season-adjusted maps of entomological inoculation rates. Models were fitted using Markov chain Monte Carlo simulation. The results show that Anophele. gambiae is the most predominant vector (79.29%) and is more rain-dependant than its sibling Anophele. funestus (20.71%). Variable selection suggests that the two species react differently to different climatic conditions. Prediction maps of entomological inoculation rate (EIR) depict a strong spatial and temporal heterogeneity in malaria transmission risk despite the relatively small geographical extend of the study area. CONCLUSION: Malaria transmission is very heterogeneous over the study area. The EIR maps clearly depict a strong spatial and temporal heterogeneity despite the relatively small geographical extend of the study area. Model based estimates of transmission can be used to identify high transmission areas in order to prioritise interventions and support research in malaria epidemiology
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