1000 resultados para Phosphate sensor


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The full-length cDNA sequence (3219 base pairs) of the trehalose-6-phosphate synthase gene of Porphyra yezoensis (PyTPS) was isolated by RACE-PCR and deposited in GenBank (NCBI) with the accession number AY729671. PyTPS encodes a protein of 908 amino acids before a stop codon, and has a calculated molecular mass of 101,591 Daltons. The PyTPS protein consists of a TPS domain in the N-terminus and a putative TPP domain at the C-terminus. Homology alignment for PyTPS and the TPS proteins from bacteria, yeast and higher plants indicated that the most closely related sequences to PyTPS were those from higher plants (OsTPS and AtTPS5), whereas the most distant sequence to PyTPS was from bacteria (EcOtsAB). Based on the identified sequence of the PyTPS gene, PCR primers were designed and used to amplify the TPS genes from nine other seaweed species. Sequences of the nine obtained TPS genes were deposited in GenBank (NCBI). All 10 TPS genes encoded peptides of 908 amino acids and the sequences were highly conserved both in nucleotide composition (>94%) and in amino acid composition (>96%). Unlike the TPS genes from some other plants, there was no intron in any of the 10 isolated seaweed TPS genes.

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An electrochemical DNA biosensor was fabricated by immobilizing DNA probe on aluminum ion films that were electrodeposited on the surface of the stearic acid-modified carbon paste electrode (CPE). DNA immobilization and hybridization were characterized with cyclic voltammetry (CV) by using methylene blue (MB) as indicator. MB has a couple of well-defined voltammetric redox peaks at the CPE. The currents of redox peaks of MB decreased after depositing aluminum ion films on the CPE (Al(III)/CPE) and increased dramatically after immobilizing DNA probe (ssDNA/Al(III)/CPE). Hybridization of DNA probe led to a marked decrease of the peak currents of MB, which can be used to detect the target single-stranded DNA. The conditions for the preparation of Al(III)/CPE, and DNA immobilization and hybridization were optimized. The specific sequences related to bar transgene in the transgenic corn and the PCR amplification of CP4 epsps gene from the sample of transgenic roundup ready soybean were detected by differential pulse voltammetry (DPV) with this new electrochemical DNA biosensor. The difference between the peak currents of MB at ssDNA/Al(III)/CPE and that at hybridization DNA modified electrode (dsDNA/Al(III)/CPE) was applied to determine the Specific sequence related to the target bar gene with the dynamic range comprised between 1.0 X 10(-7) mol/L to 1.0 x 10(-4) mol/L. A detection limit of 2.25 x.10(-8) mol/L. of oligonucleotides can be estimated.

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Previously we suggested that four proteins including aldolase and triose phosphate isomerase (TPI) evolved with approximately constant rates over long periods covering the whole animal phyla. The constant rates of aldolase and TPI evolution were reexamined based on three different models for estimating evolutionary distances, It was shown that the evolutionary rates remain essentially unchanged in comparisons not only between different classes of vertebrates but also between vertebrates and arthropods and even between animals and plants, irrespective of the models used, Thus these enzymes might be useful molecular clocks for inferring divergence times of animal phyla, To know the divergence time of Parazoa and Eumetazoa and that of Cephalochordata and Vertebrata, the aldolase cDNAs from Ephydatia fluviatilis, a freshwater sponge, and the TPI cDNAs from Ephydatia fluviatilis and Branchiostoma belcheri an amphioxus, have been cloned and sequenced, Comparisons of the deduced amino acid sequences of aldolase and TPI from the freshwater sponge with known sequences revealed that the Parazoa-Eumetazoa split occurred about 940 million years ago (Ma) as determined by the average of two proteins and three models, Similarly, the aldolase and TPI clocks suggest that vertebrates and amphioxus last shared a common ancestor around 700 Ma and they possibly diverged shortly after the divergence of deuterostomes and protostomes.

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To explore typhoon effects on dissolved organic carbon (DOC) dynamics, field investigations (tributary and dam site) and laboratory experiments (bioassay and DOC consumption) were conducted in a subtropical reservoir. A tributary survey indicated that after typhoon disruption, upstream areas were the sources of phosphate (P) but not DOC for the dam site located downstream. Bioassay experiments verified P-limitation on bacteria and phytoplankton during summer stratification, and bacteria showed a faster response than algae to added P. Experiments indicated that DOC consumption was determined by the availability of P. The 4 yr typhoon period (June-September) data of the dam site denoted that DOC concentration (27 to 270 mu M C) and its rate of change (-13 to 24 mu M C d(-1)) varied more dramatically in the weak (2006 and 2007) than in the strong (2004 and 2005) typhoon years. The negative correlation of DOC with the ratio of bacterial production (BP) to primary production (PP) in the euphotic zone (0 to 10 m) signified the interactive effects of auto- and heterotrophic processes on DOC variation. In the aphotic zone, the variation of DOC could be ascribed to the change of BP, which showed a positive correlation with P concentrations. This study documents that DOC concentration in the studied system varied at multiple time scales. Such variation can be explained by the decoupling between BP and PP, which is believed to be a function of the limiting nutrient's availability. More importantly, this study suggests that the P supply introduced by strong typhoons might have substantiated a tighter coupling between BP and PP, so that the amplitude of DOC oscillation during the summer period was effectively reduced.

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The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSIITM =(TM3 -TM5)/(TM3 +TM5); for VGT data, NDSII is calculated as NDSIIVGT =(B2- MIR)/(B2 + MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSIIVGT.

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Affine transformations are often used in recognition systems, to approximate the effects of perspective projection. The underlying mathematics is for exact feature data, with no positional uncertainty. In practice, heuristics are added to handle uncertainty. We provide a precise analysis of affine point matching, obtaining an expression for the range of affine-invariant values consistent with bounded uncertainty. This analysis reveals that the range of affine-invariant values depends on the actual $x$-$y$-positions of the features, i.e. with uncertainty, affine representations are not invariant with respect to the Cartesian coordinate system. We analyze the effect of this on geometric hashing and alignment recognition methods.

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Hardy, N. W., Barnes, D. P., Lee, M. (1987). Declarative sensor knowledge in a robot monitoring system. In: Languages for Sensor-Based Control in Robotics, Ulrich Rembold and Klaus H?rmann (eds), Springer-Verlag, p. 169-188.

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Barnes, D. P., Lee, M. H., Hardy, N. W. (1983). A control and monitoring system for multiple-sensor industrial robots. In Proc. 3rd. Int. Conf. Robot Vision and Sensory Controls, Cambridge, MA. USA., 471-479.

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We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources-this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.

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Wireless sensor networks have recently emerged as enablers of important applications such as environmental, chemical and nuclear sensing systems. Such applications have sophisticated spatial-temporal semantics that set them aside from traditional wireless networks. For example, the computation of temperature averaged over the sensor field must take into account local densities. This is crucial since otherwise the estimated average temperature can be biased by over-sampling areas where a lot more sensors exist. Thus, we envision that a fundamental service that a wireless sensor network should provide is that of estimating local densities. In this paper, we propose a lightweight probabilistic density inference protocol, we call DIP, which allows each sensor node to implicitly estimate its neighborhood size without the explicit exchange of node identifiers as in existing density discovery schemes. The theoretical basis of DIP is a probabilistic analysis which gives the relationship between the number of sensor nodes contending in the neighborhood of a node and the level of contention measured by that node. Extensive simulations confirm the premise of DIP: it can provide statistically reliable and accurate estimates of local density at a very low energy cost and constant running time. We demonstrate how applications could be built on top of our DIP-based service by computing density-unbiased statistics from estimated local densities.

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Wireless sensor networks are characterized by limited energy resources. To conserve energy, application-specific aggregation (fusion) of data reports from multiple sensors can be beneficial in reducing the amount of data flowing over the network. Furthermore, controlling the topology by scheduling the activity of nodes between active and sleep modes has often been used to uniformly distribute the energy consumption among all nodes by de-synchronizing their activities. We present an integrated analytical model to study the joint performance of in-network aggregation and topology control. We define performance metrics that capture the tradeoffs among delay, energy, and fidelity of the aggregation. Our results indicate that to achieve high fidelity levels under medium to high event reporting load, shorter and fatter aggregation/routing trees (toward the sink) offer the best delay-energy tradeoff as long as topology control is well coordinated with routing.

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Routing protocols in wireless sensor networks (WSN) face two main challenges: first, the challenging environments in which WSNs are deployed negatively affect the quality of the routing process. Therefore, routing protocols for WSNs should recognize and react to node failures and packet losses. Second, sensor nodes are battery-powered, which makes power a scarce resource. Routing protocols should optimize power consumption to prolong the lifetime of the WSN. In this paper, we present a new adaptive routing protocol for WSNs, we call it M^2RC. M^2RC has two phases: mesh establishment phase and data forwarding phase. In the first phase, M^2RC establishes the routing state to enable multipath data forwarding. In the second phase, M^2RC forwards data packets from the source to the sink. Targeting hop-by-hop reliability, an M^2RC forwarding node waits for an acknowledgement (ACK) that its packets were correctly received at the next neighbor. Based on this feedback, an M^2RC node applies multiplicative-increase/additive-decrease (MIAD) to control the number of neighbors targeted by its packet broadcast. We simulated M^2RC in the ns-2 simulator and compared it to GRAB, Max-power, and Min-power routing schemes. Our simulations show that M^2RC achieves the highest throughput with at least 10-30% less consumed power per delivered report in scenarios where a certain number of nodes unexpectedly fail.

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Recent work in sensor databases has focused extensively on distributed query problems, notably distributed computation of aggregates. Existing methods for computing aggregates broadcast queries to all sensors and use in-network aggregation of responses to minimize messaging costs. In this work, we focus on uniform random sampling across nodes, which can serve both as an alternative building block for aggregation and as an integral component of many other useful randomized algorithms. Prior to our work, the best existing proposals for uniform random sampling of sensors involve contacting all nodes in the network. We propose a practical method which is only approximately uniform, but contacts a number of sensors proportional to the diameter of the network instead of its size. The approximation achieved is tunably close to exact uniform sampling, and only relies on well-known existing primitives, namely geographic routing, distributed computation of Voronoi regions and von Neumann's rejection method. Ultimately, our sampling algorithm has the same worst-case asymptotic cost as routing a point-to-point message, and thus it is asymptotically optimal among request/reply-based sampling methods. We provide experimental results demonstrating the effectiveness of our algorithm on both synthetic and real sensor topologies.