Formation Mechanism of Guided Resonances and Bound States in the Continuum in Photonic Crystal Slabs

We develop a formalism, based on the mode expansion method, to describe the guided resonances and bound states in the continuum (BICs) in photonic crystal slabs with one-dimensional periodicity. This approach provides analytic insights to the formation mechanisms of these states: the guided resonances arise from the transverse Fabry-P\'erot condition, and the divergence of the resonance lifetimes at the BICs is explained by a destructive interference of radiation from different propagating components inside the slab. We show BICs at the center and on the edge of the Brillouin zone protected by symmetry, as well as BICs at generic wave vectors not protected by symmetry.Comment: 12 pages, 3 figure

Flower ontogenesis and fruit development of Synsepalum dulcificum

Synsepalum dulcificum from the family Sapotaceae is known as miracle fruit and is a valuable horticultural species. All plant parts are of medicinal importance whereas the fruit known as magic berry, miracle berry, or sweet berry is consumed fresh. Surprisingly, very little is known on the species in terms of flower morphology and flower development. In this study, an observation on the flower morphology and flower development of miracle fruit has been made with the aid of microscopic techniques. Miracle fruit flower requires 100 days to develop from reproductive meristem to full anthesis. The flower development can be divided into six stages based on the size and appearance of the flower bud. The fruit with persistent style developed and ripened 90 days after anthesis. Heavy fruit drop was observed at 40–60 days after anthesis which contributed to the final fruit set of average of 5.06% per plant. Through this study, miracle fruit is strongly insect pollinated and prevents self-fertilization. A study on pollination ecology is needed to identify the pollinator for miracle fruit, as this is important in manipulating fruit loading in the future

QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms

Copyright @ Elsevier Ltd. All rights reserved.In this paper, two bio-inspired Quality of Service (QoS) multicast algorithms are proposed in IP over dense wavelength division multiplexing (DWDM) optical Internet. Given a QoS multicast request and the delay interval required by the application, both algorithms are able to find a flexible QoS-based cost suboptimal routing tree. They first construct the multicast trees based on ant colony optimization and artificial immune algorithm, respectively. Then a dedicated wavelength assignment algorithm is proposed to assign wavelengths to the trees aiming to minimize the delay of the wavelength conversion. In both algorithms, multicast routing and wavelength assignment are integrated into a single process. Therefore, they can find the multicast trees on which the least wavelength conversion delay is achieved. Load balance is also considered in both algorithms. Simulation results show that these two bio-inspired algorithms can construct high performance QoS routing trees for multicast applications in IP/DWDM optical Internet.This work was supported in part ny the Program for New Century Excellent Talents in University, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1, the National Natural Science Foundation of China under Grant no. 60673159 and 70671020, the National High-Tech Reasearch and Development Plan of China under Grant no. 2007AA041201, and the Specialized Research Fund for the Doctoral Program of Higher Education under Grant no. 20070145017

Daily Runoff Simulation of a Coastal Watershed of Southeast China Based on SWAT Model

Integrated Modeling of Hydro-System

Prevalence and determinants of resistant hypertension among hypertensive patients attending a cardiology clinic in China: a prospective cross-sectional study

Purpose: To determine occurrence and determinants of resistant hypertension (RHT) among patients attending cardiology clinic of the affiliated hospital of Hangzhou Normal University, China.Methods: An observational prospective cross-sectional study was conducted among patients with hypertension attending the cardiology clinic over a period of 6 months. After identification of patients with RHT, various independent co-variants were tested by logistic regression in order to evaluate the determinants of RHT.Results: Out of 556 patients, 104 (18.7 %) patients had RHT while 67 (12.1 %) patients had uncontrolled blood pressure (BP) in spite of treatment with three antihypertensive drugs including a diuretic; 37 (6.6 %) patients had controlled BP with > three drugs. Obesity (OR: 2.7, p = 0.002], duration of hypertension (OR: 1.8, p = 0.015], presence of diabetes mellitus (OR: 3.6, p < 0.001) and ischemic heart disease (OR: 3.2, p = 0.001) were significant determinants of resistant hypertension in the study cohort.Conclusion: The prevalence of RHT found in this study is significantly high, thus indicating a need for greater attention of clinicians to this highly morbid condition. Obese patients and those suffering from diabetes mellitus, ischemic heart disease and chronic diseases should be evaluated for the presence of RHT. Early identification of such patients will provide sufficient time for clinicians to refer patients, as well as modify and/or intensify therapy.Keywords: Resistant hypertension, Risk factors, Hypertension, Stroke, Diabetes mellitus, Ischemic heart diseas

Adaptive compressive sensing and data recovery for periodical monitoring wireless sensor networks

The development of compressive sensing (CS) technology has inspired data gathering in wireless sensor networks to move from traditional raw data gathering towards compression based gathering using data correlations. While extensive efforts have been made to improve the data gathering efficiency, little has been done for data that is gathered and recovered data with unknown and dynamic sparsity. In this work, we present an adaptive compressive sensing data gathering scheme to capture the dynamic nature of signal sparsity. By only re-sampling a few measurements, the current sparsity as well as the new sampling rate can be accurately determined, thus guaranteeing recovery performance and saving energy. In order to recover a signal with unknown sparsity, we further propose an adaptive step size variation integrated with a sparsity adaptive matching pursuit algorithm to improve the recovery performance and convergence speed. Our simulation results show that the proposed algorithm can capture the variation in the sparsities of the original signal and obtain a much longer network lifetime than traditional raw data gathering algorithms.</p

Optimal Resource Block Assignment and Power Allocation for D2D-Enabled NOMA Communication

A novel joint optimization framework for device-To-device (D2D)-enabled non-orthogonal multiple access (NOMA) networks is proposed. Our objective is to maximize the performance of the D2D communication by jointly optimizing the resource block (RB) assignment and the power allocation, by considering the SIC decoding order of the NOMA-based cellular user equipments (CUEs). We invoke the distributed decision making (DDM) framework to decouple the formulated problem into two sub-problems. For the RB assignment sub-problem with integer variables, we propose a differential evolution (DE) algorithm to obtain the optimal NOMA CUE group and RB assignment for D2D pairs. For power allocation sub-problem with continuous variables and decoding order variables, we first use a heuristic algorithm to optimize the power allocation for NOMA-based CUEs with given D2D power allocation. We prove that the power allocation for the NOMA-based CUEs is the optimal solution. We then invoke the successive convex approximation (SCA) and DE to find the sub-optimal power allocation of the D2D pairs. The numerical results validate the feasibility, fast convergence, and flexibility of the proposed algorithm, and the performance with our algorithm outperforms the conventional OMA technology in terms of energy efficiency and sum rate.</p