978 research outputs found

    Evaluation of codon biology in citrus and poncirus trifoliata based on genomic features and frame corrected expressed sequence tags

    Get PDF
    Citrus, as one of the globally important fruit trees, has been an object of interest for understanding genetics and evolutionary process in fruit crops. Meta-analyses of 19 Citrus species, including 4 globally and economically important Citrus sinensis, Citrus clementina, Citrus reticulata, and 1 Citrus relative Poncirus trifoliata, were performed. We observed that codons ending with A- or T- at the wobble position were preferred in contrast to C- or G- ending codons, indicating a close association with AT richness of Citrus species and P. trifoliata. The present study postulates a large repertoire of a set of optimal codons for the Citrus genus and P. trifoliata and demonstrates that GCT and GGT are evolutionary conserved optimal codons. Our observation suggested that mutational bias is the dominating force in shaping the codon usage bias (CUB) in Citrus and P. trifoliata. Correspondence analysis (COA) revealed that the principal axis [axis 1; COA/relative synonymous codon usage (RSCU)] contributes only a minor portion (~10.96%) of the recorded variance. In all analysed species, except P. trifoliata, Gravy and aromaticity played minor roles in resolving CUB. Compositional constraints were found to be strongly associated with the amino acid signatures in Citrus species and P. trifoliata. Our present analysis postulates compositional constraints in Citrus species and P. trifoliata and plausible role of the stress with GC3 and coevolution pattern of amino acid. © The Author 2012

    Effect of influenza on cardiorespiratory and all-cause mortality in Hong Kong, Singapore and Guangzhou.

    Get PDF
    1. Using a common modelling approach, mortality attributable to influenza was higher in the two subtropical cities Guangzhou and Hong Kong than in the tropical city Singapore. 2. The virus activity appeared more synchronised in subtropical cities, whereas seasonality of influenza tended to be less marked in the tropical city. 3. High temperature was associated with increased mortality after influenza infection in Hong Kong, whereas relative humidity was an effect modifier for influenza in Guangzhou. No effect modification was found for Singapore. 4. Seasonal and environmental factors probably play a more important role than socioeconomic factors in regulating seasonality and disease burden of influenza. Further studies are needed in identifying the mechanism behind the regulatory role of environmental factors.published_or_final_versio

    Tailoring force sensitivity and selectivity by microstructure engineering of multidirectional electronic skins

    Get PDF
    Electronic skins (e-skins) with high sensitivity to multidirectional mechanical stimuli are crucial for healthcare monitoring devices, robotics, and wearable sensors. In this study, we present piezoresistive e-skins with tunable force sensitivity and selectivity to multidirectional forces through the engineered microstructure geometries (i.e., dome, pyramid, and pillar). Depending on the microstructure geometry, distinct variations in contact area and localized stress distribution are observed under different mechanical forces (i.e., normal, shear, stretching, and bending), which critically affect the force sensitivity, selectivity, response/relaxation time, and mechanical stability of e-skins. Microdome structures present the best force sensitivities for normal, tensile, and bending stresses. In particular, microdome structures exhibit extremely high pressure sensitivities over broad pressure ranges (47,062 kPa(-1) in the range of < 1 kPa, 90,657 kPa(-1) in the range of 1-10 kPa, and 30,214 kPa(-1) in the range of 10-26 kPa). On the other hand, for shear stress, micropillar structures exhibit the highest sensitivity. As proof-of-concept applications in healthcare monitoring devices, we show that our e-skins can precisely monitor acoustic waves, breathing, and human artery/carotid pulse pressures. Unveiling the relationship between the microstructure geometry of e-skins and their sensing capability would provide a platform for future development of high-performance microstructured e-skins

    A multi-biometric iris recognition system based on a deep learning approach

    Get PDF
    YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person

    A homologue of the Parkinson's disease-associated protein LRRK2 undergoes a monomer-dimer transition during GTP turnover.

    Get PDF
    Mutations in LRRK2 are a common cause of genetic Parkinson's disease (PD). LRRK2 is a multi-domain Roco protein, harbouring kinase and GTPase activity. In analogy with a bacterial homologue, LRRK2 was proposed to act as a GTPase activated by dimerization (GAD), while recent reports suggest LRRK2 to exist under a monomeric and dimeric form in vivo. It is however unknown how LRRK2 oligomerization is regulated. Here, we show that oligomerization of a homologous bacterial Roco protein depends on the nucleotide load. The protein is mainly dimeric in the nucleotide-free and GDP-bound states, while it forms monomers upon GTP binding, leading to a monomer-dimer cycle during GTP hydrolysis. An analogue of a PD-associated mutation stabilizes the dimer and decreases the GTPase activity. This work thus provides insights into the conformational cycle of Roco proteins and suggests a link between oligomerization and disease-associated mutations in LRRK2

    The muon system of the Daya Bay Reactor antineutrino experiment

    Get PDF
    postprin

    Search for a Light Sterile Neutrino at Daya Bay

    Get PDF
    published_or_final_versio

    Azimuthal anisotropy and correlations in the hard scattering regime at RHIC

    Get PDF
    Azimuthal anisotropy (v(2)) and two-particle angular correlations of high p(T) charged hadrons have been measured in Au+Au collisions at roots(NN) = 130 GeV for transverse momenta up to 6 GeV/c, where hard processes are expected to contribute significantly. The two-particle angular correlations exhibit elliptic flow and a structure suggestive of fragmentation of high p(T) partons. The monotonic rise of v(2)(p(T)) for p(T) 3 GeV/c, a saturation of v(2) is observed which persists up to p(T) = 6 GeV/c
    corecore