2,615 research outputs found

    Exploiting Radio Fingerprints for Simultaneous Localization and Mapping

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    Simultaneous localization and mapping (SLAM) is paramount for unmanned systems to achieve self-localization and navigation. It is challenging to perform SLAM in large environments, due to sensor limitations, complexity of the environment, and computational resources. We propose a novel approach for localization and mapping of autonomous vehicles using radio fingerprints, for example WiFi (Wireless Fidelity) or LTE (Long Term Evolution) radio features, which are widely available in the existing infrastructure. In particular, we present two solutions to exploit the radio fingerprints for SLAM. In the first solution-namely Radio SLAM, the output is a radio fingerprint map generated using SLAM technique. In the second solution-namely Radio+LiDAR SLAM, we use radio fingerprint to assist conventional LiDAR-based SLAM to improve accuracy and speed, while generating the occupancy map. We demonstrate the effectiveness of our system in three different environments, namely outdoor, indoor building, and semi-indoor environment.Comment: This paper has been accepted by IEEE Pervasive Computing with DOI: 10.1109/MPRV.2023.327477

    The impact of job contact networks on wages of rural–urban migrants in China: a switching regression approach

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    In nationally representative household data from the 2008 Chinese Rural to Urban Migration Survey, nearly two thirds of rural–urban migrants found their employment through family members, relatives, friends or acquaintances. This paper investigates why the use of social network to find jobs is so prevalent among rural–urban migrants in China, and whether migrants face a wage penalty as a result of adopting this job search method. Using a switch regression approach, we find evidence of positive selection effects of the use of networks on wages. Users of networks tend to be older, to have migrated longer ago and to be less educated. In addition, married workers and those from villages with more out-migrant are more likely to use networks, while those without local residential registration status are less likely. Controlling for selectivity, we find a large negative impact of network use on wages. Using job contacts brings access to urban employment, but at the cost of markedly lower wages

    Chemical adsorption of NiO nanostructures on nickel foam-graphene for supercapacitor applications

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    Few-layer graphene was synthesized on a nickel foam template by chemical vapor deposition. The resulting three-dimensional (3D) graphene was loaded with nickel oxide nanostructures using the successive ionic layer adsorption and reaction technique. The composites were characterized and investigated as electrode material for supercapacitors. Raman spectroscopy measurements on the sample revealed that the 3D graphene consisted of mostly few layers, while X-ray diffractometry and scanning electron microscopy revealed the presence of nickel oxide. The electrochemical properties were investigated using cyclic voltammetry, electrochemical impedance spectroscopy, and potentiostatic charge–discharge in aqueous KOH electrolyte. The novelty of this study is the use of the 3D porous cell structure of the nickel foam which allows for the growth of highly conductive graphene and subsequently provides support for uniform adsorption of the NiO onto the graphene. The NF-G/NiO electrode material showed excellent properties as a pseudocapacitive device with a high-specific capacitance value of 783 F g-1 at a scan rate of 2 mV s-1. The device also exhibited excellent cycle stability, with 84 % retention of the initial capacitance after 1000 cycles. The results demonstrate that composites made using 3D graphene are versatile and show considerable promise as electrode materials for supercapacitor applications.South African Research Chairs Initiative of the Department of Science and Technology (SARChI-DST) and the National Research Foundation (NRF). University of Pretoria.http://link.springer.com/journal/11665hb201

    A direct physical interaction between Nanog and Sox2 regulates embryonic stem cell self-renewal

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    Embryonic stem (ES) cell self-renewal efficiency is determined by the Nanog protein level. However, the protein partners of Nanog that function to direct self-renewal are unclear. Here, we identify a Nanog interactome of over 130 proteins including transcription factors, chromatin modifying complexes, phosphorylation and ubiquitination enzymes, basal transcriptional machinery members, and RNA processing factors. Sox2 was identified as a robust interacting partner of Nanog. The purified Nanog–Sox2 complex identified a DNA recognition sequence present in multiple overlapping Nanog/Sox2 ChIP-Seq data sets. The Nanog tryptophan repeat region is necessary and sufficient for interaction with Sox2, with tryptophan residues required. In Sox2, tyrosine to alanine mutations within a triple-repeat motif (S X T/S Y) abrogates the Nanog–Sox2 interaction, alters expression of genes associated with the Nanog-Sox2 cognate sequence, and reduces the ability of Sox2 to rescue ES cell differentiation induced by endogenous Sox2 deletion. Substitution of the tyrosines with phenylalanine rescues both the Sox2–Nanog interaction and efficient self-renewal. These results suggest that aromatic stacking of Nanog tryptophans and Sox2 tyrosines mediates an interaction central to ES cell self-renewal

    Does accelerating universe indicates Brans-Dicke theory

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    The evolution of universe in Brans-Dicke (BD) theory is discussed in this paper. Considering a parameterized scenario for BD scalar field ϕ=ϕ0aα\phi=\phi_{0}a^{\alpha} which plays the role of gravitational "constant" GG, we apply the Markov Chain Monte Carlo method to investigate a global constraints on BD theory with a self-interacting potential according to the current observational data: Union2 dataset of type supernovae Ia (SNIa), high-redshift Gamma-Ray Bursts (GRBs) data, observational Hubble data (OHD), the cluster X-ray gas mass fraction, the baryon acoustic oscillation (BAO), and the cosmic microwave background (CMB) data. It is shown that an expanded universe from deceleration to acceleration is given in this theory, and the constraint results of dimensionless matter density Ω0m\Omega_{0m} and parameter α\alpha are, Ω0m=0.286−0.039−0.047+0.037+0.050\Omega_{0m}=0.286^{+0.037+0.050}_{-0.039-0.047} and α=0.0046−0.0171−0.0206+0.0149+0.0171\alpha=0.0046^{+0.0149+0.0171}_{-0.0171-0.0206} which is consistent with the result of current experiment exploration, ∣α∣≤0.132124\mid\alpha\mid \leq 0.132124. In addition, we use the geometrical diagnostic method, jerk parameter jj, to distinguish the BD theory and cosmological constant model in Einstein's theory of general relativity.Comment: 16 pages, 3 figure

    Cloning and Characterization of Genes Involved in Nostoxanthin Biosynthesis of Sphingomonas elodea ATCC 31461

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    Most Sphingomonas species synthesize the yellow carotenoid nostoxanthin. However, the carotenoid biosynthetic pathway of these species remains unclear. In this study, we cloned and characterized a carotenoid biosynthesis gene cluster containing four carotenogenic genes (crtG, crtY, crtI and crtB) and a β-carotene hydroxylase gene (crtZ) located outside the cluster, from the gellan-gum producing bacterium Sphingomonas elodea ATCC 31461. Each of these genes was inactivated, and the biochemical function of each gene was confirmed based on chromatographic and spectroscopic analysis of the intermediates accumulated in the knockout mutants. Moreover, the crtG gene encoding the 2,2′-β-hydroxylase and the crtZ gene encoding the β-carotene hydroxylase, both responsible for hydroxylation of β-carotene, were confirmed by complementation studies using Escherichia coli producing different carotenoids. Expression of crtG in zeaxanthin and β-carotene accumulating E. coli cells resulted in the formation of nostoxanthin and 2,2′-dihydroxy-β-carotene, respectively. Based on these results, a biochemical pathway for synthesis of nostoxanthin in S. elodea ATCC 31461 is proposed

    A mathematical and computational review of Hartree-Fock SCF methods in Quantum Chemistry

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    We present here a review of the fundamental topics of Hartree-Fock theory in Quantum Chemistry. From the molecular Hamiltonian, using and discussing the Born-Oppenheimer approximation, we arrive to the Hartree and Hartree-Fock equations for the electronic problem. Special emphasis is placed in the most relevant mathematical aspects of the theoretical derivation of the final equations, as well as in the results regarding the existence and uniqueness of their solutions. All Hartree-Fock versions with different spin restrictions are systematically extracted from the general case, thus providing a unifying framework. Then, the discretization of the one-electron orbitals space is reviewed and the Roothaan-Hall formalism introduced. This leads to a exposition of the basic underlying concepts related to the construction and selection of Gaussian basis sets, focusing in algorithmic efficiency issues. Finally, we close the review with a section in which the most relevant modern developments (specially those related to the design of linear-scaling methods) are commented and linked to the issues discussed. The whole work is intentionally introductory and rather self-contained, so that it may be useful for non experts that aim to use quantum chemical methods in interdisciplinary applications. Moreover, much material that is found scattered in the literature has been put together here to facilitate comprehension and to serve as a handy reference.Comment: 64 pages, 3 figures, tMPH2e.cls style file, doublesp, mathbbol and subeqn package

    Prediction of Ligand Binding Using an Approach Designed to Accommodate Diversity in Protein-Ligand Interactions

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    Computational determination of protein-ligand interaction potential is important for many biological applications including virtual screening for therapeutic drugs. The novel internal consensus scoring strategy is an empirical approach with an extended set of 9 binding terms combined with a neural network capable of analysis of diverse complexes. Like conventional consensus methods, internal consensus is capable of maintaining multiple distinct representations of protein-ligand interactions. In a typical use the method was trained using ligand classification data (binding/no binding) for a single receptor. The internal consensus analyses successfully distinguished protein-ligand complexes from decoys (r2, 0.895 for a series of typical proteins). Results are superior to other tested empirical methods. In virtual screening experiments, internal consensus analyses provide consistent enrichment as determined by ROC-AUC and pROC metrics
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