Pairing interactions and the vanishing pairing correlations in hot nuclei

Finite temperature Hartree-Fock-Bogoliubov calculations are performed in Sn isotopes using Skyrme and zero-range, density-dependent pairing interactions. For both stable and very neutron-rich nuclei the critical temperature at which pairing correlations vanish is independent of the volume/surface nature of the pairing interaction. The value of the critical temperature follows approximatively the empirical rule T$_c$ $\simeq$ 0.5 $\Delta_{T=0}$ for all the calculated isotopes, showing that the critical temperature could be deduced from the pairing gap at zero temperature. On the other hand, the pairing gap at temperatures just below T$_c$ is strongly sensitive to the volume/surface nature of the pairing interaction.Comment: 6 pages, 7 figures revised versio

Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks

© 2019 IEEE. In this paper, we propose a novel approach to jointly address energy management and network throughput maximization problems for heterogeneous IoT low-power wireless communication networks. In particular, we consider a low-power communication network in which the IoT devices can harvest energy from a dedicated RF energy source to support their transmissions or backscatter the signals of the RF energy source to transmit information to the gateway. Different IoT devices may have dissimilar hardware configurations, and thus they may have various communications types and energy requirements. In addition, the RF energy source may have a limited energy supply source which needs to be minimized. Thus, to maximize the network throughput, we need to jointly optimize energy usage and operation time for the IoT devices under different energy demands and communication constraints. However, this optimization problem is non-convex due to the strong relation between energy supplied by the RF energy source and the IoT communication time, and thus obtaining the optimal solution is intractable. To address this problem, we study the relation between energy supply and communication time, and then transform the non-convex optimization problem to an equivalent convex-optimization problem which can achieve the optimal solution. Through simulation results, we show that our solution can achieve greater network throughputs (up to five times) than those of other conventional methods, e.g., TDMA. In addition, the simulation results also reveal some important information in controlling energy supply and managing low-power IoT devices in heterogeneous wireless communication networks

Collective excitations in the inner crust of neutron stars : supergiant resonances

We investigate the nuclear collective excitations of Wigner-Seitz cells containing nuclear clusters immersed in a gas of neutrons. This baryonic non-uniform system is specific to the structure of inner crust matter of neutron stars. The collective excitations are studied in the framework of a spherical Hartree-Fock-Bogoliubov + Quasiparticle Random Phase Approximation, formulated in coordinate representation. The calculations are done for two representative Wigner-Seitz cells with baryonic density equal to 0.02 fm$^{-3}$ and 0.08 fm$^{-3}$. It is shown that the excitations with low multipolarities are concentrated almost entirely in one strongly collective mode which exhausts a very large fraction of the energy-weighted sum rule. Since these collective modes are located at very low energies compared to the giant resonances in standard nuclei, they may affect significantly the specific heat of baryonic inner crust matter of neutron stars.Comment: 6 pages, 4 figure

Quasiparticle RPA with finite rank approximation for Skyrme interactions

A finite rank separable approximation for the particle-hole RPA calculations with Skyrme interactions is extended to take into account the pairing. As an illustration of the method energies and transition probabilities for the quadrupole and octupole excitations in some O, Ar, Sn and Pb isotopes are calculated. The values obtained within our approach are very close to those that were calculated within QRPA with the full Skyrme interaction. They are in reasonable agreement with experimental data.Comment: 20 pages, 1 figure, submitted to Phys.Rev.

Low-Lying 2+ states in neutron-rich oxygen isotopes in quasiparticle random phase approximation

The properties of the low-lying, collective 2+ states in neutron-rich oxygen isotopes are investigated in the framework of self-consistent microscopic models with effective Skyrme interactions. In RPA the excitation energies E2+ can be well described but the transition probabilities are much too small as compared to experiment. Pairing correlations are then accounted for by performing quasiparticle RPA calculations. This improves considerably the predictions of B(E2) values and it enables one to calculate more reliably the ratios Mn/Mp of neutron-to-proton transition amplitudes. A satisfactory agreement with the existing experimental values of Mn/Mp is obtained.Comment: 8 pages, 3 figure

Ion-implantation induced anomalous surface amorphization in silicon

Spectroscopic ellipsometry (SE), high-depth-resolution Rutherford backscattering (RBS) and channeling have been used to examine the surface damage formed by room temperature N and B implantation into silicon. For the analysis of the SE data we used the conventional method of assuming appropriate optical models and fitting the model parameters (layer thicknesses and volume fraction of the amorphous silicon component in the layers) by linear regression. The dependence of the thickness of the surface-damaged silicon layer (beneath the native oxide layer) on the implantation parameters was determined: the higher the dose, the thicker the disordered layer at the surface. The mechanism of the surface amorphization process is explained in relation to the ion beam induced layer-by-layer amorphization. The results demonstrate the applicability of Spectroscopic ellipsometry with a proper optical model. RBS, as an independent cross-checking method supported the constructed optical model

Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach

© 2019 IEEE. Practical and efficient network slicing often faces real-time dynamics of network resources and uncertain customer demands. This work provides an optimal and fast resource slicing solution under such dynamics by leveraging the latest advances in deep learning. Specifically, we first introduce a novel system model which allows the network provider to effectively allocate its combinatorial resources, i.e., spectrum, computing, and storage, to various classes of users. To allocate resources to users while taking into account the dynamic demands of users and resources constraints of the network provider, we employ a semi-Markov decision process framework. To obtain the optimal resource allocation policy for the network provider without requiring environment parameters, e.g., uncertain service time and resource demands, a Q-learning algorithm is adopted. Although this algorithm can maximize the revenue of the network provider, its convergence to the optimal policy is particularly slow, especially for problems with large state/action spaces. To overcome this challenge, we propose a novel approach using an advanced deep Q-learning technique, called deep dueling that can achieve the optimal policy at few thousand times faster than that of the conventional Q-learning algorithm. Simulation results show that our proposed framework can improve the long-term average return of the network provider up to 40% compared with other current approaches

Temporal fluctuation of multidrug resistant salmonella typhi haplotypes in the mekong river delta region of Vietnam.

BACKGROUND: typhoid fever remains a public health problem in Vietnam, with a significant burden in the Mekong River delta region. Typhoid fever is caused by the bacterial pathogen Salmonella enterica serovar Typhi (S. Typhi), which is frequently multidrug resistant with reduced susceptibility to fluoroquinolone-based drugs, the first choice for the treatment of typhoid fever. We used a GoldenGate (Illumina) assay to type 1,500 single nucleotide polymorphisms (SNPs) and analyse the genetic variation of S. Typhi isolated from 267 typhoid fever patients in the Mekong delta region participating in a randomized trial conducted between 2004 and 2005. PRINCIPAL FINDINGS: the population of S. Typhi circulating during the study was highly clonal, with 91% of isolates belonging to a single clonal complex of the S. Typhi H58 haplogroup. The patterns of disease were consistent with the presence of an endemic haplotype H58-C and a localised outbreak of S. Typhi haplotype H58-E2 in 2004. H58-E2-associated typhoid fever cases exhibited evidence of significant geo-spatial clustering along the Sông H u branch of the Mekong River. Multidrug resistance was common in the established clone H58-C but not in the outbreak clone H58-E2, however all H58 S. Typhi were nalidixic acid resistant and carried a Ser83Phe amino acid substitution in the gyrA gene. SIGNIFICANCE: the H58 haplogroup dominates S. Typhi populations in other endemic areas, but the population described here was more homogeneous than previously examined populations, and the dominant clonal complex (H58-C, -E1, -E2) observed in this study has not been detected outside Vietnam. IncHI1 plasmid-bearing S. Typhi H58-C was endemic during the study period whilst H58-E2, which rarely carried the plasmid, was only transient, suggesting a selective advantage for the plasmid. These data add insight into the outbreak dynamics and local molecular epidemiology of S. Typhi in southern Vietnam