Data-driven SIRMs-connected FIS for prediction of external tendon stress

This paper presents a novel harmony search (HS)-based data-driven single input rule modules (SIRMs)- connected fuzzy inference system (FIS) for the prediction of stress in externally prestressed tendon. The proposed method attempts to extract causal relationship of a system from an input-output pairs of data even without knowing the complete physical knowledge of the system. The monotonicity property is then exploited as an additional qualitative information to obtain a meaningful SIRMs-connected FIS model. This method is then validated using results from test data from the literature. Several parameters, such as initial tendon depth to beam ratio; deviators spacing to the initial tendon depth ratio; and distance of a concentrated load from the nearest support to the effective beam span are considered. A computer simulation for estimating the bond reduction coefficient u is then reported. The contributions of this paper is two folds; (1) it contributes towards a new monotonicity-preserving data-driven FIS model in fuzzy modeling and (2) it provides a novel solution for estimating the u even without a complete physical knowledge of unbonded tendons

School Closure and Mitigation of Pandemic (H1N1) 2009, Hong Kong

In Hong Kong, kindergartens and primary schools were closed when local transmission of pandemic (H1N1) 2009 was identified. Secondary schools closed for summer vacation shortly afterwards. By fitting a model of reporting and transmission to case data, we estimated that transmission was reduced ≈25% when secondary schools closed

MicroRNA clusters integrate evolutionary constraints on expression and target affinities : the miR-6/5/4/286/3/309 cluster in Drosophila

This research was supported by the Hong Kong Research Grant Council GRF Grant (14103516), The Chinese University of Hong Kong Direct Grant (4053248), and TUYF Charitable Trust (6903957) (JHLH).A striking feature of microRNAs is that they are often clustered in the genomes of animals. The functional and evolutionary consequences of this clustering remain obscure. Here, we investigated a microRNA cluster miR-6/5/4/286/3/309 that is conserved across drosophilid lineages. Small RNA sequencing revealed expression of this microRNA cluster in Drosophila melanogaster leg discs, and conditional overexpression of the whole cluster resulted in leg appendage shortening. Transgenic overexpression lines expressing different combinations of microRNA cluster members were also constructed. Expression of individual microRNAs from the cluster resulted in a normal wild-type phenotype, but either the expression of several ancient microRNAs together (miR-5/4/286/3/309) or more recently evolved clustered microRNAs (miR-6-1/2/3) can recapitulate the phenotypes generated by the whole-cluster overexpression. Screening of transgenic fly lines revealed down-regulation of leg patterning gene cassettes in generation of the leg-shortening phenotype. Furthermore, cell transfection with different combinations of microRNA cluster members revealed a suite of downstream genes targeted by all cluster members, as well as complements of targets that are unique for distinct microRNAs. Considered together, the microRNA targets and the evolutionary ages of each microRNA in the cluster demonstrates the importance of microRNA clustering, where new members can reinforce and modify the selection forces on both the cluster regulation and the gene regulatory network of existing microRNAs.PostprintPeer reviewe

Large enhancement of deuteron polarization with frequency modulated microwaves

We report a large enhancement of 1.7 in deuteron polarization up to values of 0.6 due to frequency modulation of the polarizing microwaves in a two liters polarized target using the method of dynamic nuclear polarization. This target was used during a deep inelastic polarized muon-deuteron scattering experiment at CERN. Measurements of the electron paramagnetic resonance absorption spectra show that frequency modulation gives rise to additional microwave absorption in the spectral wings. Although these results are not understood theoretically, they may provide a useful testing ground for the deeper understanding of dynamic nuclear polarization.Comment: 10 pages, including the figures coming in uuencoded compressed tar files in poltar.uu, which also brings cernart.sty and crna12.sty files neede

Search for the Flavor-Changing Neutral Current Decay D0→μ+μ−D^0 \to \mu^+\mu^- with the HERA-B Detector

We report on a search for the flavor-changing neutral current decay $D^0 \to \mu^+\mu^-$ using $50 \times 10^6$ events recorded with a dimuon trigger in interactions of 920 GeV protons with nuclei by the HERA-B experiment. We find no evidence for such decays and set a 90% confidence level upper limit on the branching fraction $Br(D^0 \to \mu^+\mu^-) <2.0 \times 10^{-6}$.Comment: 17 pages, 4 figures (of which 1 double), paper to be submitted to Physics Letters

Measurement of the J/Psi Production Cross Section in 920 GeV/c Fixed-Target Proton-Nucleus Interactions

The mid-rapidity (dsigma_(pN)/dy at y=0) and total sigma_(pN) production cross sections of J/Psi mesons are measured in proton-nucleus interactions. Data collected by the HERA-B experiment in interactions of 920 GeV/c protons with carbon, titanium and tungsten targets are used for this analysis. The J/Psi mesons are reconstructed by their decay into lepton pairs. The total production cross section obtained is sigma_(pN)(J/Psi) = 663 +- 74 +- 46 nb/nucleon. In addition, our result is compared with previous measurements

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types