RF Energy Harvesting in WSNs

As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article reviews existing energy harvesting technology applied in WSNs, and analyzes advantages of harvesting radio frequency (RF) energy in WSNs.

Energy saving in intelligent buildings - via energy harvesting in wireless sensor networks

Wireless sensor networks (WSNs) have been widely used in pervasive systems such as intelligent buildings. As a vital factor of product cost, energy consuming in WSN has been focused upon, but only via energy harvesting can the problem be overcome radically. This article presents a new approach to harvesting electromagnetic energy for WSN from useless radio frequency (RF) signals transmitted in WSN, with a quantitative analysis showing its feasibility.

Radio frequency energy harvesting in wireless sensor networks

As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article presents a new approach to making use of electromagnetic energy from useless radio frequency (RF) signals transmitted in WSNs, with a quantitative analysis showing its feasibility. A mechanism to harvest the energy either passively or actively is proposed.

Energy-efficient hybrid system for Wireless Body Area Network Applications

Wireless Body Area Networks (WBANs) consist of a number of miniaturized wearable or implanted sensor nodes that are employed to monitor vital parameters of a patient over long duration of time. These sensors capture physiological data and wirelessly transfer the collected data to a local base station in order to be further processed. Almost all of these body sensors are expected to have low data-rate and to run on a battery. Since recharging or replacing the battery is not a simple task specifically in the case of implanted devices such as pacemakers, extending the lifetime of sensor nodes in WBANs is one of the greatest challenges. To achieve this goal, WBAN systems employ low-power communication transceivers and low duty cycle Medium Access Control (MAC) protocols. Although, currently used MAC protocols are able to reduce the energy consumption of devices for transmission and reception, yet they are still unable to offer an ultimate energy self-sustaining solution for low-power MAC protocols. This paper proposes to utilize energy harvesting technologies in low-power MAC protocols. This novel approach can further reduce energy consumption of devices in WBAN systems.

A comparison between bond graphs switching modelling techniques implemented on a boost dc-dc converter

A Bond Graph is a graphical modelling technique that allows the representation of energy flow between the components of a system. When used to model power electronic systems, it is necessary to incorporate bond graph elements to represent a switch. In this paper, three different methods of modelling switching devices are compared and contrasted: the Modulated Transformer with a binary modulation ratio (MTF), the ideal switch element, and the Switched Power Junction (SPJ) method. These three methods are used to model a dc-dc Boost converter and then run simulations in MATLAB/SIMULINK. To provide a reference to compare results, the converter is also simulated using PSPICE. Both quantitative and qualitative comparisons are made to determine the suitability of each of the three Bond Graph switch models in specific power electronics applications

Toll-like receptor expression in murine DC subsets: lack of TLR7 expression by CD8α+ DC correlates with unresponsiveness to imidazoquinolines

Toll-like receptors (TLR) recognize microbial and viral patterns and activate dendritic cells (DC). TLR distribution among human DC subsets is heterogeneous: plasmacytoid DC (PDC) express TLR1, 7 and 9, while other DC types do not express TLR9 but express other TLR. Here, we report that mRNA for most TLR is expressed at similar levels by murine splenic DC sub-types, including PDC, but that TLR3 is preferentially expressed by CD8α+ DC while TLR5 and TLR7 are selectively absent from the same subset. Consistent with the latter, TLR7 ligand activates CD8α– DC and PDC, but not CD8α+ DC as measured by survival ex vivo, up-regulation of surface markers and production of IL-12p40. These data suggest that the dichotomy in TLR expression between plasmacytoid and non-plasmacytoid DC is not conserved between species. However, lack of TLR7 expression could restrict the involvement of CD8α+ DC in recognition of certain mouse pathogens.

Onset of germinability, desiccation tolerance and hardseededness in developing seeds of Peltophorum pterocarpum (DC) K. Heyne (Caesalpinioideae)

In the hot and dry conditions in which seeds of the tree legume Peltophorum pterocarpum develop and mature in Vietnam, seed moisture content declined rapidly on the mother plant from 87% at 42 d after flowering (DAF) to 15% at 70 DAF. Dry weight of the pods attained a maximum value at about 42 DAF, but seed mass maturity (i.e. the end of the seed-filling phase) occurred at about 62 DAF, at which time seed moisture content was about 45-48%. The onset of the ability of freshly collected seeds to germinate (in 63-d tests at 28-34degreesC) occurred at 42 DAF, i.e. about 20 d before mass maturity. Full germination (98%) was attained at 70 DAF, i.e. at about 8 d after mass maturity. Thereafter, germination of fresh seeds declined, due to the imposition of a hard seed coat. Tolerance of desiccation to 10% moisture content was first detected at 56 DAF and was complete within the seed population by 84 DAF, i.e. about 22 d after mass maturity. Hardseededness began to be induced when seeds were dried to about 15% moisture content and below, with a negative logarithmic relation between hardseededness and moisture content below this value.

Evaluation of NRC, UC Davis and ADAS approaches to estimate the metabolizable energy values of feeds at maintenance energy intake from equations utilizing chemical assays and in vitro determinations

Feed samples received by commercial analytical laboratories are often undefined or mixed varieties of forages, originate from various agronomic or geographical areas of the world, are mixtures (e.g., total mixed rations) and are often described incompletely or not at all. Six unified single equation approaches to predict the metabolizable energy (ME) value of feeds determined in sheep fed at maintenance ME intake were evaluated utilizing 78 individual feeds representing 17 different forages, grains, protein meals and by-product feedstuffs. The predictive approaches evaluated were two each from National Research Council [National Research Council (NRC), Nutrient Requirements of Dairy Cattle, seventh revised ed. National Academy Press, Washington, DC, USA, 2001], University of California at Davis (UC Davis) and ADAS (Stratford, UK). Slopes and intercepts for the two ADAS approaches that utilized in vitro digestibility of organic matter and either measured gross energy (GE), or a prediction of GE from component assays, and one UC Davis approach, based upon in vitro gas production and some component assays, differed from both unity and zero, respectively, while this was not the case for the two NRC and one UC Davis approach. However, within these latter three approaches, the goodness of fit (r(2)) increased from the NRC approach utilizing lignin (0.61) to the NRC approach utilizing 48 h in vitro digestion of neutral detergent fibre (NDF:0.72) and to the UC Davis approach utilizing a 30 h in vitro digestion of NDF (0.84). The reason for the difference between the precision of the NRC procedures was the failure of assayed lignin values to accurately predict 48 h in vitro digestion of NDF. However, differences among the six predictive approaches in the number of supporting assays, and their costs, as well as that the NRC approach is actually three related equations requiring categorical description of feeds (making them unsuitable for mixed feeds) while the ADAS and UC Davis approaches are single equations, suggests that the procedure of choice will vary dependent Upon local conditions, specific objectives and the feedstuffs to be evaluated. In contrast to the evaluation of the procedures among feedstuffs, no procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo, suggesting that the quest for an accurate and precise ME predictive approach among and within feeds, may remain to be identified. (C) 2004 Elsevier B.V. All rights reserved.

DC-SIGN increases the affinity of HIV-1 envelope glycoprotein interaction with CD4

Mannose-binding C-type lectin receptors, expressed on Langerhans cells and subepithelial dendritic cells (DCs) of cervico-vaginal tissues, play an important role in HIV-1 capture and subsequent dissemination to lymph nodes. DC-SIGN has been implicated in both productive infection of DCs and the DC-mediated trans infection of CD4(+) T cells that occurs in the absence of replication. However, the molecular events that underlie this efficient transmission have not been fully defined. In this study, we have examined the effect of the extracellular domains of DC-SIGN and Langerin on the stability of the interaction of the HIV-1 envelope glycoprotein with CD4 and also on replication in permissive cells. Surface plasmon resonance analysis showed that DC-SIGN increases the binding affinity of trimeric gp140 envelope glycoproteins to CD4. In contrast, Langerin had no effect on the stability of the gp140:CD4 complex. In vitro infection experiments to compare DC-SIGN enhancement of CD4-dependent and CD4-independent strains demonstrated significantly lower enhancement of the CD4-independent strain. In addition DC-SIGN increased the relative rate of infection of the CD4-dependent strain but had no effect on the CD4-independent strain. DC-SIGN binding to the HIV envelope protein effectively increases exposure of the CD4 binding site, which in turn contributes to enhancement of infection.

The statistical downscaling model-decision centric (SDSM-DC): conceptual basis and applications

Regional climate downscaling has arrived at an important juncture. Some in the research community favour continued refinement and evaluation of downscaling techniques within a broader framework of uncertainty characterisation and reduction. Others are calling for smarter use of downscaling tools, accepting that conventional, scenario-led strategies for adaptation planning have limited utility in practice. This paper sets out the rationale and new functionality of the Decision Centric (DC) version of the Statistical DownScaling Model (SDSM-DC). This tool enables synthesis of plausible daily weather series, exotic variables (such as tidal surge), and climate change scenarios guided, not determined, by climate model output. Two worked examples are presented. The first shows how SDSM-DC can be used to reconstruct and in-fill missing records based on calibrated predictor-predictand relationships. Daily temperature and precipitation series from sites in Africa, Asia and North America are deliberately degraded to show that SDSM-DC can reconstitute lost data. The second demonstrates the application of the new scenario generator for stress testing a specific adaptation decision. SDSM-DC is used to generate daily precipitation scenarios to simulate winter flooding in the Boyne catchment, Ireland. This sensitivity analysis reveals the conditions under which existing precautionary allowances for climate change might be insufficient. We conclude by discussing the wider implications of the proposed approach and research opportunities presented by the new tool.

Bond graph models of DC-DC converters operating in both CCM and DCM

In this paper, Bond Graphs are employed to develop a novel mathematical model of conventional switched-mode DC-DC converters valid for both continuous and discontinuous conduction modes. A unique causality bond graph model of hybrid models is suggested with the operation of the switch and the diode to be represented by a Modulated Transformer with a binary input and a resistor with fixed conductance causality. The operation of the diode is controlled using an if-then function within the model. The extracted hybrid model is implemented on a Boost and Buck converter with their operations to change from CCM to DCM and to return to CCM. The vector fields of the models show validity in a wide operation area and comparison with the simulation of the converters using PSPICE reveals high accuracy of the proposed model, with the Normalised Root Means Square Error and the Maximum Absolute Error remaining adequately low. The model is also experimentally tested on a Buck topology.