Energy Efficiency Maximization Under Delay-Outage Probability Constraints Using Fluid Antenna Systems

Fluid antenna system (FAS) is a new wireless technology that enables reconfigurable antenna position to enhance communication performance. In wireless networks, spectral efficiency, delay and energy efficiency are some of the most important performance indicators. To jointly optimize these indicators for FAS-assisted point-to-point communication systems, we adopt the energy efficiency (EE) metric which is defined as the delivered data rate divided by the total power consumption. The optimal power allocation strategy is obtained to maximize the EE subject to a delay-outage probability constraint. We then study the effects of delay bounds and the number of FAS's ports on the maximum EE. Simulation results are presented to show the effectiveness of the proposed delay-aware FAS-assisted system

Lattice-Boltzmann model for axisymmetric thermal flows

In this brief report, a thermal lattice-Boltzmann (LB) model is presented for axisymmetric thermal flows in the incompressible limit. The model is based on the double-distribution-function LB method, which has attracted much attention since its emergence for its excellent numerical stability. Compared with the existing axisymmetric thermal LB models, the present model is simpler and retains the inherent features of the standard LB method. Numerical simulations are carried out for the thermally developing laminar flows in circular ducts and the natural convection in an annulus between two coaxial vertical cylinders. The Nusselt number obtained from the simulations agrees well with the analytical solutions and/or the results reported in previous studies.Comment: 11 pages, 4 figure

Elastic net hypergraph learning for image clustering and semi-supervised classification

© 1992-2012 IEEE. Graph model is emerging as a very effective tool for learning the complex structures and relationships hidden in data. In general, the critical purpose of graph-oriented learning algorithms is to construct an informative graph for image clustering and classification tasks. In addition to the classical K -nearest-neighbor and r-neighborhood methods for graph construction, l1-graph and its variants are emerging methods for finding the neighboring samples of a center datum, where the corresponding ingoing edge weights are simultaneously derived by the sparse reconstruction coefficients of the remaining samples. However, the pairwise links of l1-graph are not capable of capturing the high-order relationships between the center datum and its prominent data in sparse reconstruction. Meanwhile, from the perspective of variable selection, the l1 norm sparse constraint, regarded as a LASSO model, tends to select only one datum from a group of data that are highly correlated and ignore the others. To simultaneously cope with these drawbacks, we propose a new elastic net hypergraph learning model, which consists of two steps. In the first step, the robust matrix elastic net model is constructed to find the canonically related samples in a somewhat greedy way, achieving the grouping effect by adding the l2 penalty to the l1 constraint. In the second step, hypergraph is used to represent the high order relationships between each datum and its prominent samples by regarding them as a hyperedge. Subsequently, hypergraph Laplacian matrix is constructed for further analysis. New hypergraph learning algorithms, including unsupervised clustering and multi-class semi-supervised classification, are then derived. Extensive experiments on face and handwriting databases demonstrate the effectiveness of the proposed method

Exact solution of gyration radius of individual's trajectory for a simplified human mobility model

Gyration radius of individual's trajectory plays a key role in quantifying human mobility patterns. Of particular interests, empirical analyses suggest that the growth of gyration radius is slow versus time except the very early stage and may eventually arrive to a steady value. However, up to now, the underlying mechanism leading to such a possibly steady value has not been well understood. In this Letter, we propose a simplified human mobility model to simulate individual's daily travel with three sequential activities: commuting to workplace, going to do leisure activities and returning home. With the assumption that individual has constant travel speed and inferior limit of time at home and work, we prove that the daily moving area of an individual is an ellipse, and finally get an exact solution of the gyration radius. The analytical solution well captures the empirical observation reported in [M. C. Gonz`alez et al., Nature, 453 (2008) 779]. We also find that, in spite of the heterogeneous displacement distribution in the population level, individuals in our model have characteristic displacements, indicating a completely different mechanism to the one proposed by Song et al. [Nat. Phys. 6 (2010) 818].Comment: 4 pages, 4 figure

Signature of high temperature superconductivity in electron doped Sr2IrO4

Sr2IrO4 was predicted to be a high temperature superconductor upon electron doping since it highly resembles the cuprates in crystal structure, electronic structure and magnetic coupling constants. Here we report a scanning tunneling microscopy/spectroscopy (STM/STS) study of Sr2IrO4 with surface electron doping by depositing potassium (K) atoms. At the 0.5-0.7 monolayer (ML) K coverage, we observed a sharp, V-shaped gap with about 95% loss of density of state (DOS) at EFand visible coherence peaks. The gap magnitude is 25-30 meV for 0.5-0.6 ML K coverage and it closes around 50 K. These behaviors exhibit clear signature of superconductivity. Furthermore, we found that with increased electron doping, the system gradually evolves from an insulating state to a normal metallic state, via a pseudogap-like state and possible superconducting state. Our data suggest possible high temperature superconductivity in electron doped Sr2IrO4, and its remarkable analogy to the cuprates.Comment: 11 pages, 5 figure

Floating Microparticulate Oral Diltiazem Hydrochloride Delivery System for Improved Delivery to Heart

Purpose: To formulate and evaluate floating microparticulate oral diltiazem delivery system for possible delivery to the heart.Method: Floating microspheres were prepared using cellulose acetate and Eudragit RS100 polymers by emulsion solvent evaporation technique. The dried floating microspheres were evaluated for micromeritic properties (flow properties, density, particle size determination) scanning as well as by electron microscopy, and in vitro floatability and drug release studies.Results: The microspheres showed good buoyancy, good flow properties (angle of repose ranging from 24.29 to 29.02 º), particle size (262.09 to 409.60 μm) and good drug loading (74.29 to 92.09 %). The microspheres were porous, hollow and spherical. All the formulations showed good in vitro controlled drug release in the range of 77.62 ± 2.12 to 97.50 ± 1.04 % at the end of 12 h. Drug release was diffusion-controlled and followed zero order kinetics.Conclusion: Microparticulate floating (gastroretentive) oral drug delivery system of diltiazem prepared using cellulose acetate and Eudragit R5100 may be an effective alternative to conventional oral tablets for cardiac drug delivery.Keywords: Cardiac, Microparticulate, Drug release, Gastroretentive, Floating microspheres, Diltiazem hydrochlorid