Conceal an entrance by means of superscatterer

By using the novel property of the rectangular superscatterer, we propose a design which can conceal an entrance from electromagnetic wave detection. Such a superscatterer is realized by coating a negative index material shell on a perfect electrical conductor rectangle cylinder. The results are numerically confirmed by full-wave simulations both in the far-field and near-field.Comment: 10 pages, 4 figure

MMFL-Net: Multi-scale and Multi-granularity Feature Learning for Cross-domain Fashion Retrieval

Instance-level image retrieval in fashion is a challenging issue owing to its increasing importance in real-scenario visual fashion search. Cross-domain fashion retrieval aims to match the unconstrained customer images as queries for photographs provided by retailers; however, it is a difficult task due to a wide range of consumer-to-shop (C2S) domain discrepancies and also considering that clothing image is vulnerable to various non-rigid deformations. To this end, we propose a novel multi-scale and multi-granularity feature learning network (MMFL-Net), which can jointly learn global-local aggregation feature representations of clothing images in a unified framework, aiming to train a cross-domain model for C2S fashion visual similarity. First, a new semantic-spatial feature fusion part is designed to bridge the semantic-spatial gap by applying top-down and bottom-up bidirectional multi-scale feature fusion. Next, a multi-branch deep network architecture is introduced to capture global salient, part-informed, and local detailed information, and extracting robust and discrimination feature embedding by integrating the similarity learning of coarse-to-fine embedding with the multiple granularities. Finally, the improved trihard loss, center loss, and multi-task classification loss are adopted for our MMFL-Net, which can jointly optimize intra-class and inter-class distance and thus explicitly improve intra-class compactness and inter-class discriminability between its visual representations for feature learning. Furthermore, our proposed model also combines the multi-task attribute recognition and classification module with multi-label semantic attributes and product ID labels. Experimental results demonstrate that our proposed MMFL-Net achieves significant improvement over the state-of-the-art methods on the two datasets, DeepFashion-C2S and Street2Shop.Comment: 27 pages, 12 figures, Published by <Multimedia Tools and Applications

Cost-Based Droop Schemes for Economic Dispatch in Islanded Microgrids

In this paper, cost-based droop schemes are proposed, to minimize the total active power generation cost in an islanded microgrid (MG), while the simplicity and decentralized nature of the droop control are retained. In cost-based droop schemes, the incremental costs of distributed generators (DGs) are embedded into the droop schemes, where the incremental cost is a derivative of the DG cost function with respect to output power. In the steady state, DGs share a single common frequency, and cost-based droop schemes equate incremental costs of DGs, thus minimizing the total active power generation cost, in terms of the equal incremental cost principle. Finally, simulation results in an islanded MG with high a penetration of intermittent renewable energy sources are presented, to demonstrate the effectiveness, as well as plug and play capability of the cost-based droop schemes.Feixiong Chen, Minyou Chen, Qiang Li, Kaikai Meng, Yongwei Zheng, Josep M. Guerrero, Derek Abbot

Direct rosiglitazone action on steroidogenesis and proinflammatory factor production in human granulosa-lutein cells

<p>Abstract</p> <p>Background</p> <p>Ovarian granulosa cells are the predominant source of estradiol and progesterone biosynthesis in vivo. Rosiglitazone, a synthetic agonist of the peroxisome proliferator-activated receptor gamma (PPAR gamma), is applied as the treatment of insulin resistance including women with PCOS. The aim of the study was to investigate the direct effects of rosiglitazone on steroidogenesis and proinflammatory factor production in human granulosa-lutein cells (GLCs).</p> <p>Methods</p> <p>Primary human GLCs were separated during in vitro fertilization and cultured in the presence of rosiglitazone, GW9662 (an antagonist of PPAR gamma) and hCG. The mRNA expression of key steroidogenic factors including 3beta- hydroxysteriod dehydrogenase (3beta-HSD), cytochrome P-450 scc (CYP11A1), cytochrome P-450 aromatase (CYP19A1), and steroidogenic acute regulatory protein (StAR) were detected by quantitative real-time PCR. Estradiol and progesterone levels in GLCs cultures were measured by chemiluminescence immunoassay, and the proinflammtory factors (TNFalpha and IL-6) in conditioned culture media were measured by ELISA.</p> <p>Results</p> <p>PPAR gamma mRNA levels increased up to 3.24 fold by rosiglitazone at the concentration of 30 microM compared to control (P < 0.05). hCG alone or hCG with rosiglitazone had no significant effects on PPAR gamma mRNA levels. The CYP19A1 mRNA level at exposure to rosiglitazone alone showed a drop, but was not significantly reduced comparing to control. The expression levels of enzymes 3beta-HSD and CYP11A1 in all treatments did not alter significantly. The StAR mRNA expression at exposure to rosiglitazone was significantly increased comparing to control (P < 0.05). The media concentrations of E2 and progesterone by rosiglitazone treatment showed a declining trend comparing to control or cotreatment with hCG, which did not reach significance. Most importantly, treatment with rosiglitazone decreased TNFalpha secretion in a statistically significant manner compared with control (P < 0.05). The concentration of IL-6 following rosiglitazone exposure did not significantly decrease comparing to control.</p> <p>Conclusion</p> <p>In cultured GLCs, rosiglitazone stimulated StAR expression, but did not significantly affect steroidogenic enzymes, as well as E2 and progesterone production. Moreover, rosiglitazone significantly decreased the production of TNFalpha in human GLCs, suggesting that PPAR gamma may play a role in the regulation of GLCs functions through inhibiting proinflammatory factors.</p

Lipopolysaccharide preconditioning enhances the efficacy of mesenchymal stem cells transplantation in a rat model of acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Mesenchymal stem cells (MSCs)-based regenerative therapy is currently regarded as an alternative approach to salvage the acute myocardial infarcted hearts. However, the efficiency of MSCs transplantation is limited by lower survival rate of engrafted MSCs. In previous study, we found that 1.0 μg/ml Lipopolysaccharide (LPS) could protect MSCs against apoptosis induced by oxidative stress and meanwhile enhance the proliferation of MSCs. Therefore, in the present study, we firstly preconditioned MSCs with 1.0 μg/ml LPS, then transplanted MSCs into ischemic myocardium, and observed the survival and cardiac protective capacity of MSCs in a rat model of acute myocardial infarction. Furthermore, we tried to explore the underlying mechanisms and the role of Toll-like receptor-4 (TLR4) in the signal pathway of LPS-induced cardiac protection.</p> <p>Methods and results</p> <p>Acute myocardial infarction model was developed by left anterior descending coronary artery ligation. 60 rats were divided into 4 groups randomly and given an intramyocardial injection of one of the following treatments: 30 μl PBS (control group), 3 × 10⁶wild MSCs/30 μl (wMSCs group), 3 × 10⁶LPS-preconditioned wild MSCs/30 μl (LPS-wMSCs group), or 3 × 10⁶LPS-preconditioned TLR4 gene deleted MSCs/30 μl (LPS-tMSCs group). After 3 weeks, LPS-preconditioned wild MSCs transplantation ameliorated cardiac function and reduced fibrosis of infarcted myocardium. Vascular density was markedly increased in LPS-wMSCs group compared with other three groups. Survival rate of engrafted MSCs was elevated and apoptosis of myocardium was reduced in infarcted heart. Expression of vascular endothelial growth factor (VEGF) and phospho-Akt was increased in the infarcted myocardium after transplantation of LPS-preconditioned MSCs.</p> <p>Conclusion</p> <p>LPS preconditioning enhanced survival of engrafted MSCs, stimulated expression of VEGF and activated PI3K/Akt pathway. LPS preconditioning before MSCs transplantation resulted in superior therapeutic neovascularization and recovery of cardiac function. LPS preconditioning provided a novel strategy in maximizing biologic and functional properties of MSCs.</p

Bidding for Highly Available Services with Low Price in Spot Instance Market

ABSTRACT Amazon EC2 has built the Spot Instance Marketplace and offers a new type of virtual machine instances called as spot instances. These instances are less expensive but considered failure-prone. Despite the underlying hardware status, if the bidding price is lower than the market price, such an instance will be terminated. Distributed systems can be built from the spot instances to reduce the cost while still tolerating instance failures. For example, embarrassingly parallel jobs can use the spot instances by re-executing failed tasks. The bidding framework for such jobs simply selects the spot price as the bid. However, highly available services like lock service or storage service cannot use the similar techniques for availability consideration. The spot instance failure model is different to that of normal instances (fixed failure probability in traditional distributed model). This makes the bidding strategy more complex to keep service availability for such systems. We formalize this problem and propose an availability and cost aware bidding framework. Experiment results show that our bidding framework can reduce the costs of a distributed lock service and a distributed storage service by 81.23% and 85.32% respectively while still keeping availability level the same as it is by using on-demand instances