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In this paper, we design a new virtual queue-based back-pressure scheduling algorithm (VBR) for achieving significant delay reduction in wireless sensor networks (WSN). Our algorithm design comes from an observation that classical back-pressure scheduling algorithm usually needs a long period of time to form a queue backlog-based gradient in a network, which decreases towards the sink in the network, before achieving stable packet delivery performance. To address this issue, VBR is designed to pre-build proper virtual queue-based gradient at nodes in a WSN, which is chosen to be a function of traffic arrival rate, link rate, and distance to sink, in order to be adaptive to different network and application environments while achieving high network performance. Moreover, the queue backlog differential between each pair of neighbor nodes is decided by their actual queue lengths and also their virtual queue lengths (gradient values). We prove that VBR can maintain back-pressure scheduling’s throughput optimality. Simulation result shows that VBR can obtain significant performance improvement in terms of packet delivery ratio, average end-to-end delay, and average queue length as compared with existing work.

Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work.

Positioning technique has become an indispensable part of our daily lives. Compared with the well-solved positioning issue in outdoor areas, indoor positioning is still far from being well explored, and existing techniques in this area are still far from being sufficiently mature to be widely used in practice. Recently, visible light communication based indoor positioning, also referred to as visible light based positioning, has attracted great attention and much work has been carried out, which reveals remarkable positioning accuracy. In this article, we provide a comprehensive survey of visible light based positioning. We first introduce some fundamental issues in visible light based positioning and further categorize existing systems in this field according to different design criteria. We then give a comprehensive survey of state-of-the-art systems, and introduce how each of the systems works and discuss their merits and deficiencies. Finally, we discuss challenging issues in this area and also point out future directions.

Epidemiologic studies have provided solid evidence for the neurotoxic effect of lead for decades of years. In view of the fact that children are more vulnerable to the neurotoxicity of lead, lead exposure has been an urgent public health concern for decades of years. The modes of action of lead neurotoxic effects include disturbance of neurotransmitter storage and release, damage of mitochondria, as well as induction of apoptosis in cerebrovascular endothelial cells, astroglia and oligodendroglia. Our studies here, from a novel point of view, demonstrates that lead specifically caused induction of COX-2, a well known inflammatory mediator in neurons and glia cells. Furthermore, we revealed that COX-2 was induced by lead in a transcription-dependent manner, which relayed on transcription factor NFAT, rather than AP-1 and NFκB, in glial cells. Considering the important functions of COX-2 in mediation of inflammation reaction and oxidative stress, our studies here provide a mechanistic insight into the understanding of lead-associated inflammatory neurotoxicity effect via activation of pro-inflammatory NFAT3/COX-2 axis.

In this paper, we propose a location-based friend-assisted coding-aware routing protocol (LFCR) for wireless multihop networks. To achieve improved network throughout, LFCR performs inter-flow network coding based routing with the assistance of location information. Specifically, LFCR combines friend-assisted path discovery and coding-aware routing. Further, when making decision on next hop selection, LFCR takes into account both coding opportunities and forwarding progress in next hop selection and attempts to make a good tradeoff between them. Simulation results show that LFCR significantly outperforms existing work in terms of network throughput, packet delivery ratio, and coding frequency.

Recently, much effort has been made for implementation of back-pressure scheduling in wireless networks. In this paper, we explore the implementation of back-pressure-based forwarding in wireless sensor networks. For this purpose, we propose Gradient-pressure, a practical Gradient-assisted anycast-based back-pressure framework for wireless sensor networks. Gradient-pressure introduces gradient information to assist transmission scheduling and realizes distributed anycast-based back-pressure scheduling on top of IEEE 802.11. Simulation results demonstrate that Gradient-pressure has high performance in terms of energy-use efficiency and goodput.

In this paper, we propose an efficient network coding based back-pressure algorithm (NBP). NBP introduces the interflow network coding to improve the performance of the backpressure algorithm (a famous throughput-optimal cross-layer scheduling algorithm) for scheduling the transmissions of packets and also higher transmission efficiency. We theoretically prove that NBP can stabilize such networks. Simulation results demonstrate that NBP significantly outperforms traditional back-pressure algorithm in terms of packet delivery delay and average forwarding queue length.

Summary Back-pressure scheduling has been considered as a promising strategy for resource allocation in wireless multi-hop networks. However, there still exist some problems preventing its wide deployment in practice. One of the problems is its poor end-to-end (E2E) delay performance. In this paper, we study how to effectively use inter-flow network coding to improve E2E delay and also throughput performance of back-pressure scheduling. For this purpose, we propose an efficient network coding based back-pressure algorithm (NBP), and accordingly design detailed procedure regarding how to consider coding gain in back-pressure based weight calculation and how to integrate it into next hop decision making in the NBP algorithm. We theoretically prove that NBP can stabilize the networks. Simulation results demonstrate that NBP can not only improve the delay performance of back-pressure algorithm, but also achieve higher network throughput. Copyright © 2016 John Wiley & Sons, Ltd.

TNFα is one of the initial and important mediators to activate downstream signaling pathways by binding to trimerized TNFα receptors (TNFR), and thus is an ideal drug target for cancer therapy. Taking advantage of intrinsic homotimerization of the globular domain of adiponectin (gAD), we have developed a novel TNFα antagonist, the trimerized fusion protein named sTNFRII-gAD. However, our previously-used CHO expression system yielded less than 10 mg/L of sTNFRII-gAD. To produce large quantities of sTNFRII-gAD efficiently, we used a modified CHO-S cell expression system, which is based on a pMH3 vector with non-coding GC-rich DNA fragments for high-level gene expression. We obtained stable clones that produced 75 mg/L of sTNFRII-gAD in the 96-well plate, adapted the clones to 40 ml suspension serum-free batch culture, then optimized the culturing conditions to scale up the fed-batch culture in a 3 L shake-flask and finally in a 5 L AP30 bioreactor. We achieved a final yield of 52 mg/L of sTNFRII-gAD. The trimerized sTNFRII-gAD exhibited the higher affinity to TNFα with a dissociation constant (Kd) of 5.63 nM than the dimerized sTNFRII-Fc with a Kd of 13.4 nM, and further displayed the higher TNFα-neutralizing activity than sTNFRII-Fc (p