142 research outputs found
The effect of the tailbiting restriction on feedback encoders
It is shown that, for short and moderate relative tailbiting lengths and high signal-to-noise ratios, systematic feedback encoders have better bit error performance than nonsystematic feedforward encoders. Conditions for when tailbiting will fail are given and it is described how the encoder starting state can be obtained for feedback encoders in both controller and observer canonical for
New tailbiting encoders
In B tailbiting trellis encoder, the starting state of the encoder is set to the state at which the machine will be at the end of the encoded frame. By this means the probability of decoding error at the end of the frame can be kept low without the addition of termination bits and the consequent rate loss. We report on an extensive search for short and moderatelength convoluticinal encoders for tailbiting trellis representations of bllock codes at rates 1/4, 1/3, 1/2, and 2/3. The short tailbiting representations found are typically as good as the best known block codes
Searching for tailbiting codes with large minimum distances
Tailbiting trellis representations of linear block codes with an arbitrary sectionalization of the time axis are studied. A new lower bound on the maximal state complexity of an arbitrary tailbiting code is derived. The asymptotic behavior of the derived bound is investigated. Some new tailbiting representations for linear block codes of rates R=1/c, c=2,3,4 are presente
A web tool for finding gene candidates associated with experimentally induced arthritis in the rat
Rat models are frequently used for finding genes contributing to the arthritis phenotype. In most studies, however, limitations in the number of animals result in a low resolution. As a result, the linkage between the autoimmune experimental arthritis phenotype and the genomic region, that is, the quantitative trait locus, can cover several hundred genes. The purpose of this work was to facilitate the search for candidate genes in such regions by introducing a web tool called Candidate Gene Capture (CGC) that takes advantage of free text data on gene function. The CGC tool was developed by combining genomic regions in the rat, associated with the autoimmune experimental arthritis phenotype, with rat/human gene homology data, and with descriptions of phenotypic gene effects and selected keywords. Each keyword was assigned a value, which was used for ranking genes based on their description of phenotypic gene effects. The application was implemented as a web-based tool and made public at . The CGC application ranks gene candidates for 37 rat genomic regions associated with autoimmune experimental arthritis phenotypes. To evaluate the CGC tool, the gene ranking in four regions was compared with an independent manual evaluation. In these sample tests, there was a full agreement between the manual ranking and the CGC ranking for the four highest-ranked genes in each test, except for one single gene. This indicates that the CGC tool creates a ranking very similar to that made by human inspection. The exceptional gene, which was ranked as a gene candidate by the CGC tool but not in the manual evaluation, was found to be closely associated with rheumatoid arthritis in additional literature studies. Genes ranked by the CGC tools as less likely gene candidates, as well as genes ranked low, were generally rated in a similar manner to those done manually. Thus, to find genes contributing to experimentally induced arthritis, we consider the CGC application to be a helpful tool in facilitating the evaluation of large amounts of textual information
An upper bound on decoding bit-error probability with linear coding on extremely noisy channels
When concatenated coding schemes operate near channel capacity their component encoders may operate above capacity. The decoding bit-error performance of binary convolutional codes near and above capacity is investigate
Estimating density from presence/absence data in clustered populations
Inventories of plant populations are fundamental in ecological research and monitoring, but such surveys are often prone to field assessment errors. Presence/absence (P/A) sampling may have advantages over plant cover assessments for reducing such errors. However, the linking between P/A data and plant density depends on model assumptions for plant spatial distributions. Previous studies have shown, for example, how that plant density can be estimated under Poisson model assumptions on the plant locations. In this study, new methods are developed and evaluated for linking P/A data with plant density assuming that plants occur in clustered spatial patterns.New theory was derived for estimating plant density under Neyman-Scott-type cluster models such as the Matern and Thomas cluster processes. Suggested estimators, corresponding confidence intervals and a proposed goodness-of-fit test were evaluated in a Monte Carlo simulation study assuming a Matern cluster process. Furthermore, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empirical application.The simulation study showed that our methods work well for large enough sample sizes. The judgment of what is' large enough' is often difficult, but simulations indicate that a sample size is large enough when the sampling distributions of the parameter estimators are symmetric or mildly skewed. Bootstrap may be used to check whether this is true. The empirical results suggest that the derived methodology may be useful for estimating density of plants such as Leucanthemum vulgare and Scorzonera humilis.By developing estimators of plant density from P/A data under realistic model assumptions about plants' spatial distributions, P/A sampling will become a more useful tool for inventories of plant populations. Our new theory is an important step in this direction
FĂ€ltinstruktion för nationell inventering av landskapet i Sverige, NILS, MOTH, LillNILS och Ă&B : Ă„r 2012
Temporal and Spatial Positioning of Service Crops in Cereals Affects Yield and Weed Control
Leguminous service crops (SCs) can provide multiple services to cropping systems, reducing the reliance on external resources if sufficient biomass is produced. However, rapid light and temperature reductions limit post-harvest cultivation of SCs in Northern Europe. A novel practice of intercropping SCs in two consecutive crops (spring-winter cereal) to extend the period of SCs growth, and hence improve yield and reduce weeds, was tested. Three spatial and temporal arrangements of SCs and cash crops were investigated, as well as three SC mixtures, characterized by their longevity and frost sensitivity. Compared to no SC, the best performing mixture, frost-tolerant annuals, increased grain and N yield of winter wheat by 10% and 19%, respectively, and reduced weed biomass by 15% and 26% in oats and winter wheat, respectively. These effects were attributed to high biomass production and winter survival. However, this SC reduced oat yields by 15% compared to no SC. Furthermore, SC growth and service provision varied largely between experiments, driven by the weather conditions. Extending the SC's growth period by intercropping in two consecutive cereal crops has potential, but locally adapted species choices and establishment strategies are needed to ensure SC vitality until termination
Multiple drivers of large-scale lichen decline in boreal forest canopies
Thin, hair-like lichens (Alectoria, Bryoria, Usnea) form conspicuous epiphyte communities across the boreal biome. These poikilohydric organisms provide important ecosystem functions and are useful indicators of global change. We analyse how environmental drivers influence changes in occurrence and length of these lichens on Norway spruce (Picea abies) over 10 years in managed forests in Sweden using data from >6000 trees. Alectoria and Usnea showed strong declines in southern-central regions, whereas Bryoria declined in northern regions. Overall, relative loss rates across the country ranged from 1.7% per year in Alectoria to 0.5% in Bryoria. These losses contrasted with increased length of Bryoria and Usnea in some regions. Occurrence trajectories (extinction, colonization, presence, absence) on remeasured trees correlated best with temperature, rain, nitrogen deposition, and stand age in multinomial logistic regression models. Our analysis strongly suggests that industrial forestry, in combination with nitrogen, is the main driver of lichen declines. Logging of forests with long continuity of tree cover, short rotation cycles, substrate limitation and low light in dense forests are harmful for lichens. Nitrogen deposition has decreased but is apparently still sufficiently high to prevent recovery. Warming correlated with occurrence trajectories of Alectoria and Bryoria, likely by altering hydration regimes and increasing respiration during autumn/winter. The large-scale lichen decline on an important host has cascading effects on biodiversity and function of boreal forest canopies. Forest management must apply a broad spectrum of methods, including uneven-aged continuous cover forestry and retention of large patches, to secure the ecosystem functions of these important canopy components under future climates. Our findings highlight interactions among drivers of lichen decline (forestry, nitrogen, climate), functional traits (dispersal, lichen colour, sensitivity to nitrogen, water storage), and population processes (extinction/colonization)
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