The turbulent single-phase forced convection heat transfer and pressure drop characteristics of circular ducts containing swirl-row inducers or pall rings

The heat transfer and pressure drop characteristics of tubes containing either Pall rings, or helical (180°) strips of metal, were studied experimentally. Tests were performed with water in the Reynolds number range of 11000 to 104000, approximately. Rotameters were used to measure the volumetric flowrate of the water. The effect of fluid temperature on this measurement was determined. The insertion of a continuous length of Pall rings into a tube increases the Nusselt number and pressure drop by factors of 1.5 and 15. (These factors are relative to the empty tube over the same flow range). Smaller increases were obtained while using rings that were equidistantly spaced along the tube. [Continues.

Open-Ended Evolutionary Robotics: an Information Theoretic Approach

This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller. This entropy is computed using unsupervised learning; its maximization, achieved by an on-board evolutionary algorithm, implements a "curiosity instinct", favouring controllers visiting many diverse sensori-motor states (sms). Further, the set of sms discovered by an individual can be transmitted to its offspring, making a cultural evolution mode possible. Cumulative entropy (computed from ancestors and current individual visits to the sms) defines another self-driven fitness; its optimization implements a "discovery instinct", as it favours controllers visiting new or rare sensori-motor states. Empirical results on the benchmark problems proposed by Lehman and Stanley (2008) comparatively demonstrate the merits of the approach

Assessment of processes and operating conditions in UK pork abattoirs

In order to determine typical and atypical operations in the slaughtering and dressing of pigs for pork and bacon practices and operations were recorded at eight pig abattoirs. Data included physical parameters such as temperatures and durations. The results indicate that plants are reasonably similar if processing pigs mainly for pork, but those processing mainly for bacon had more aggressive singeing and polishing (black scraper) arrangements. The plants visited used either hot water (tank) or vertical (sprayed hot water) scalding systems prior to dehairing

HLA-class I markers and multiple sclerosis susceptibility in the Italian population

Previous studies reported an association with multiple sclerosis (MS) of distinct HLA-class I markers, namely HLA-A*02, HLA-Cw*05 and MOG-142L. In this work, we tested the association with MS of A*02 and Cw*05 in 1273 Italian MS patients and 1075 matched controls, which were previously analyzed for MOG-142, and explored the relationship among these three markers in modulating MS risk. HLA-A*02 conferred a statistically robust MS protection (odds ratio, OR=0.61; 95% confidence intervals, CI=0.51–0.72, P<10−9), which was independent of DRB1*15 and of any other DRB1* allele and remained similar after accounting for the other two analyzed class I markers. Conversely, the protective effect we previously observed for MOG-142L was secondary to its linkage disequilibrium with A*02. Cw*05 was not associated considering the whole sample, but its presence significantly enhanced the protection in the HLA-A*02-positive group, independently of DRB1: the OR conferred by A*02 in Cw*05-positive individuals (0.22, 95% CI=0.13–0.38) was significantly lower than in Cw*05-negative individuals (0.69, 95% CI=0.58–0.83) with a significant (P=4.94 × 10−5) multiplicative interaction between the two markers. In the absence of A*02, Cw*05 behaved as a risk factor, particularly in combination with DRB1*03 (OR=3.89, P=0.0006), indicating that Cw*05 might be a marker of protective or risk haplotypes, respectively

Population-based study of genetic variation in individuals with autism spectrum disorders from Croatia

<p>Abstract</p> <p>Background</p> <p>Genome-wide studies on autism spectrum disorders (ASDs) have mostly focused on large-scale population samples, but examination of rare variations in isolated populations may provide additional insights into the disease pathogenesis.</p> <p>Methods</p> <p>As a first step in the genetic analysis of ASD in Croatia, we characterized genetic variation in a sample of 103 subjects with ASD and 203 control individuals, who were genotyped using the Illumina HumanHap550 BeadChip. We analyzed the genetic diversity of the Croatian population and its relationship to other populations, the degree of relatedness via Runs of Homozygosity (ROHs), and the distribution of large (>500 Kb) copy number variations.</p> <p>Results</p> <p>Combining the Croatian cohort with several previously published populations in the FastME analysis (an alternative to Neighbor Joining) revealed that Croatian subjects cluster, as expected, with Southern Europeans; in addition, individuals from the same geographic region within Europe cluster together. Whereas Croatian subjects could be separated from a sample of healthy control subjects of European origin from North America, Croatian ASD cases and controls are well mixed. A comparison of runs of homozygosity indicated that the number and the median length of regions of homozygosity are higher for ASD subjects than for controls (p = 6 × 10^-3). Furthermore, analysis of copy number variants found a higher frequency of large chromosomal rearrangements (>2 Mb) in ASD cases (5/103) than in ethnically matched control subjects (1/197, p = 0.019).</p> <p>Conclusions</p> <p>Our findings illustrate the remarkable utility of high-density genotype data for subjects from a limited geographic area in dissecting genetic heterogeneity with respect to population and disease related variation.</p

A Polymorphism in the HLA-DPB1 Gene Is Associated with Susceptibility to Multiple Sclerosis

We conducted an association study across the human leukocyte antigen (HLA) complex to identify loci associated with multiple sclerosis (MS). Comparing 1927 SNPs in 1618 MS cases and 3413 controls of European ancestry, we identified seven SNPs that were independently associated with MS conditional on the others (each ). All associations were significant in an independent replication cohort of 2212 cases and 2251 controls () and were highly significant in the combined dataset (). The associated SNPs included proxies for HLA-DRB1*15:01 and HLA-DRB1*03:01, and SNPs in moderate linkage disequilibrium (LD) with HLA-A*02:01, HLA-DRB1*04:01 and HLA-DRB1*13:03. We also found a strong association with rs9277535 in the class II gene HLA-DPB1 (discovery set , replication set , combined ). HLA-DPB1 is located centromeric of the more commonly typed class II genes HLA-DRB1, -DQA1 and -DQB1. It is separated from these genes by a recombination hotspot, and the association is not affected by conditioning on genotypes at DRB1, DQA1 and DQB1. Hence rs9277535 represents an independent MS-susceptibility locus of genome-wide significance. It is correlated with the HLA-DPB1*03:01 allele, which has been implicated previously in MS in smaller studies. Further genotyping in large datasets is required to confirm and resolve this association

The turbulent single phase forced convection heat transfer and pressure drop characteristics of circular ducts containing swirl flow inducers or pall rings

SIGLELD:D45171/83 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Toward a theory of embodied statistical learning

The purpose of this paper is to outline a new formulation of statistical learning that will be more useful and relevant to the field of robotics. The primary motivation for this new perspective is the mismatch between the form of data assumed by current statistical learning algorithms, and the form of data that is actually generated by robotic systems. Specifically, robotic systems generate a vast unlabeled data stream, while most current algorithms are designed to handle limited numbers of discrete, labeled, independent and identically distributed samples. We argue that there is only one meaningful unsupervised learning process that can be applied to a vast data stream: adaptive compression. The compression rate can be used to compare different techniques, and statistical models obtained through adaptive compression should also be useful for other tasks