3,146 research outputs found

    Dynamics of automorphisms on compact Kähler manifolds

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    AbstractWe study holomorphic automorphisms on compact Kähler manifolds having simple actions on the Hodge cohomology ring. We show for such automorphisms that the main dynamical Green currents admit complex laminar structures (woven currents) and the Green measure is the unique invariant probability measure of maximal entropy

    Factors influencing engagement in premarital sex among Vietnamese young adults: a qualitative study.

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    Background With the rising trend of sexual engagement among Vietnamese young adults in recent years, concerns were raised over the issue of premarital sex and its potential health consequences. In order to prevent such consequences and further promote health, an in-depth understanding of factors influencing young people to have premarital sex would be valuable. Objective To generate a grounded theory explaining factors influencing engagement in premarital sex among Vietnamese young adults. Subjects Vietnamese adults aged 18-24 who have voluntarily engaged in premarital sex (n = 18). Method The study was conducted using the grounded theory approach by Glaser. Purposive and theoretical sampling was used. Ten in-depth interviews and three additional focus group discussions were carried out. The interviews were audio-recorded and transcribed verbatim. Data analysis involved using the constant comparative method and open and theoretical coding. Sampling, data collection and data analysis happened simultaneously until theoretical saturation was achieved. Results The grounded theory is constructed around six emergent themes: (a) desire as the 'direct cause'; (b) the facilitators; (c) social changes; (d) media; (e) peer and (f) absence of family. The latter four themes are 'indirect causes' that influence through desire and the facilitators. Conclusion The study has contributed a grounded theory that identified the factors and described their relationships in a comprehensive way. It suggested a need for a reliable source of information to be tailor-designed to suit young people. Additionally, the stigma of talking about sex needs to be reduced to allow for more open discussions on sex and sexual health

    Disturbance decoupled observers for systems with unknown inputs

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    This note deals with the design of reduced-order disturbance decoupled scalar functional observers for linear systems with unknown inputs. Based on a parametric approach, existence conditions are derived and a design procedure for finding reduced-order scalar functional observers is given. The derived existence conditions are relaxed and the procedure can find first-order disturbance decoupled scalar functional observers for some cases where the number of unknown inputs is more than the number of outputs. Also, the observer matching condition, which is the necessary requirement for the design of state observers for linear systems with unknown inputs, is not required. Numerical examples are given to illustrate the attractiveness of the proposed design method.<br /

    Calculation of the hyperfine structure of the superheavy elements Z=119 and Z=120+

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    The hyperfine structure constants of the lowest ss and p1/2p_{1/2} states of superheavy elements Z=119 and Z= 120+^+ are calculated using {\em ab initio} approach. Core polarization and dominating correlation effects are included to all orders. Breit and quantum electrodynamic effects are also considered. Similar calculations for Cs, Fr, Ba+^+ and Ra+^+ are used to control the accuracy. The dependence of the hyperfine structure constants on nuclear radius is discussed.Comment: 4 pages, 3 tables, no figure

    Parametric attosecond pulse amplification far from the ionization threshold from high order harmonic generation in He+^+

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    Parametric amplification of attosecond coherent pulses around 100 eV at the single-atom level is demonstrated for the first time by using the 3D time-dependent Schr{\"o}dinger equation in high-harmonic generation processes from excited states of He+^+. We present the attosecond dynamics of the amplification process far from the ionization threshold and resolve the physics behind it. The amplification of a particular central photon energy requires the seed XUV pulses to be perfectly synchronized in time with the driving laser field for stimulated recombination to the He+^+ ground state and is only produced in a few specific laser cycles in agreement with the experimental measurements. Our simulations show that the amplified photon energy region can be controlled by varying the peak intensity of the laser field. Our results pave the way to the realization of compact attosecond pulse intense XUV lasers with broad applications

    Unsupervised deep learning-based reconfigurable intelligent surface aided broadcasting communications in industrial IoTs

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    This paper presents a general system framework which lays the foundation for Reconfigurable Intelligent Surface (RIS)-enhanced broadcast communications in Industrial Internet of Things (IIoTs). In our system model, we consider multiple sensor clusters co-existing in a smart factory where the direct links between these clusters and a central base station (BS) is blocked completely. In this context, an RIS is utilized to reflect signals broadcast from BS toward cluster heads (CHs) which act as a representative of clusters, where BS only has access to the statistical distribution of the channel state information (CSI). An analytical upper bound of the total ergodic spectral efficiency and an approximation of outage probability are derived. Based on these analytical results, two algorithms are introduced to control the phase shifts at RIS, which are the Riemannian conjugate gradient (RCG) method and the deep neural network (DNN) method. While the RCG algorithm operates based on the conventional iterative method, the DNN technique relies on unsupervised deep learning. Our numerical results show that the both algorithms achieve satisfactory performance based on only statistical CSI. In addition, compared to the RCG scheme, using deep learning reduces the computational latency by more than 10 times with an almost identical total ergodic spectral efficiency achieved. These numerical results reveal that while using conventional RCG method may provide unsatisfactory latency, DNN technique shows much promise for enabling RIS in ultra reliable and low latency communications (URLLC) in the context of IIoTs

    <Advanced Energy Utilization Division> Biofunctional Chemistry Research Section

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    3-1. Research Activities in 202
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