A modified broadcast strategy for distributed signal estimation in a wireless sensor network with a tree topology

We envisage a wireless sensor network (WSN) where each node is tasked with estimating a set of node-specific desired signals that has been corrupted by additive noise. The nodes accomplish this estimation by means of the distributed adaptive node-specific estimation (DANSE) algorithm in a tree topology (T-DANSE). In this paper, we consider a network where there is at least one node with a large (virtually infinite) energy budget, which we select as the root node. We propose a modification to the signal flow of the T-DANSE algorithm where instead of each node having two-way signal communication, there is a single signal flow toward the root node of the tree topology which then broadcasts a single signal to all other nodes. We demonstrate that the modified algorithm is equivalent to the original T-DANSE algorithm in terms of the signal estimation performance, shifts a large part of the communication burden toward the high-power root node to reduce the energy consumption in the low-power nodes and reduces the input-output delay

Efficient calculation of sensor utility and sensor removal in wireless sensor networks for adaptive signal estimation and beamforming

Wireless sensor networks are often deployed over a large area of interest and therefore the quality of the sensor signals may vary significantly across the different sensors. In this case, it is useful to have a measure for the importance or the so-called "utility" of each sensor, e.g., for sensor subset selection, resource allocation or topology selection. In this paper, we consider the efficient calculation of sensor utility measures for four different signal estimation or beamforming algorithms in an adaptive context. We use the definition of sensor utility as the increase in cost (e.g., mean-squared error) when the sensor is removed from the estimation procedure. Since each possible sensor removal corresponds to a new estimation problem (involving less sensors), calculating the sensor utilities would require a continuous updating of different signal estimators (where is the number of sensors), increasing computational complexity and memory usage by a factor. However, we derive formulas to efficiently calculate all sensor utilities with hardly any increase in memory usage and computational complexity compared to the signal estimation algorithm already in place. When applied in adaptive signal estimation algorithms, this allows for on-line tracking of all the sensor utilities at almost no additional cost. Furthermore, we derive efficient formulas for sensor removal, i.e., for updating the signal estimator coefficients when a sensor is removed, e.g., due to a failure in the wireless link or when its utility is too low. We provide a complexity evaluation of the derived formulas, and demonstrate the significant reduction in computational complexity compared to straightforward implementations

Sire by environment interactions for growth traits in beef cattle

The importance of region by sire, herd within region by sire and contemporary group within herd by sire interactions were evaluated for 68,271 birth weight, 247,943 weaning weight and 98,790 postweaning gain records supplied by the American Polled Hereford Association. Variance components for sire, region by sire, herd within region by sire, contemporary group within herd by sire and error were estimated using Henderson Method 3 estimation procedures. Sire by region, herd within region by sire and contemporary group within herd by sire variance estimates divided by the sire variance estimates were .57, .93 and 1.71, respectively, for weaning weight, -1.00, -.14 and 1.29, respectively, for birth weight, and -1.19, .14 and 1.22, respectively, for postweaning gain;The average genetic correlation estimates of weaning weight sire expected differences (EPDs) across regions was .64. This value expresses the correlation among progeny of the same sire after the sire evaluation model had accounted for the contemporary group within herd by sire and herd within region by sire interactions. The average genetic correlation estimates of weaning weight sire EPDs across contemporary groups within herds and across herds within regions were .37 and .27, respectively. The correlation estimates indicated that some rank changes were occurring between sire EPDs in different regions, and substantial rank changes of sire EPDs were occurring across herd and contemporary groups. Heritability of weaning weight was .11 across regions, .17 across herds within region, .28 within herd, and .46 within contemporary group;The average genetic correlation estimates among birth weight sire EPDs across regions were .24 and .35 using two different estimation methods. The average genetic correlation estimates among postweaning gain sire EPDs across regions were .21 and .32 using two different estimation methods. The correlation estimates for birth weight and postweaning gain may not fully reflect the true nature of the correlations due to insufficient number of progreny across regions;In general, contemporary group within herd by sire interaction appeared to be an important source of variation for all the traits and should continue to be included as a random effect in future national sire evaluations for the Polled Hereford breed. The data also indicated that performing sire evaluations across regions for birth weight, weaning weight and postweaning gain, while assuming that region by sire effects are negligible, may lead to severe errors in ranking sires in some regions. Separate sire evaluations for each region would yield sire estimates that better reflect the true future progeny performance of a sire in each region

Polynuclear complexes of first-row transition metal ions

Issued as Annual report, and Final technical report, Project no. G-33-619Reports have title: Polynuclear complexes of first-row transition metal ion

Complexes of B-dicarbonyl dianions

Issued as final repor

Microglial subtypes: diversity within the microglial community

Microglia are brain-resident macrophages forming the first active immune barrier in the central nervous system. They fulfill multiple functions across development and adulthood and under disease conditions. Current understanding revolves around microglia acquiring distinct phenotypes upon exposure to extrinsic cues in their environment. However, emerging evidence suggests that microglia display differences in their functions that are not exclusively driven by their milieu, rather by the unique properties these cells possess. This microglial intrinsic heterogeneity has been largely overlooked, favoring the prevailing view that microglia are a single-cell type endowed with spectacular plasticity, allowing them to acquire multiple phenotypes and thereby fulfill their numerous functions in health and disease. Here, we review the evidence that microglia might form a community of cells in which each member (or "subtype") displays intrinsic properties and performs unique functions. Distinctive features and functional implications of several microglial subtypes are considered, across contexts of health and disease. Finally, we suggest that microglial subtype categorization shall be based on function and we propose ways for studying them. Hence, we advocate that plasticity (reaction states) and diversity (subtypes) should both be considered when studying the multitasking microglia.España, Ministerio de Ciencia, Innovación y Universidades FEDER y UE RTI2018-098645-B-10

Using definite clause grammars to build a global system for analyzing collections of documents

International audienceCollections of documents are sets of heterogeneous documents, like a specific ancient book series, having proper structural and semantic properties linking them. A particular collection contains document images with specific physical layouts, like text pages or full-page illustrations, appearing in a specific order. Its contents, like journal articles, may be shared by several pages, not necessary following, producing strong dependencies between pages interpretations.In order to build an analysis system which can bring contextual information from the collection to the appropriate recognition modules for each page, we propose to express the structural and the semantic properties of a collection with a definite clause grammar. This is made possible by representing collections as streams of document descriptors, and by using extensions to the formalism we present here. We are then able to automatically generate a parser dedicated to a collection. Beside allowing structural variations and complex information flows, we also show that this approach enables the design of analysis stages, on a document or a set of documents. The interest of context usage is illustrated with several examples and their appropriate formalization in this framework