Yield predictions of timothy (Phleum pratense L.) in Norway under future climate scenarios

The perennial forage grass timothy (Phleum pratense L.) is the most important forage crop in Norway. Future changesin the climate will affect growing conditions and hence the yield output. We used data from the Norwegian Value for Cultivation and Use testing to find a statistical prediction model for total dry matter yield (DMY) based on agro-climatic variables. The statistical model selection found that the predictors with the highest predictive power were growing degree days (GDD) in July and the number of days with rain (>1mm) in June–July. These predictors together explained 43% of the variability in total DMY. Further, the prediction model was combined with a range of climate ensembles (RCP4.5) to project DMY of timothy for the decades 2050–2059 and 2090–2099 at 8 locations in Norway. Our projections forecast that DMY of today’s timothy varieties may decrease substantially in South-Eastern Norway, but increase in Northern Norway, by the middle of the century, due to increased temperatures and changing precipitation patterns

Non-smooth optimization methods for computation of the conditional value-at-risk and portfolio optimization

We examine numerical performance of various methods of calculation of the Conditional Value-at-risk (CVaR), and portfolio optimization with respect to this risk measure. We concentrate on the method proposed by Rockafellar and Uryasev in (Rockafellar, R.T. and Uryasev, S., 2000, Optimization of conditional value-at-risk. Journal of Risk, 2, 21-41), which converts this problem to that of convex optimization. We compare the use of linear programming techniques against a non-smooth optimization method of the discrete gradient, and establish the supremacy of the latter. We show that non-smooth optimization can be used efficiently for large portfolio optimization, and also examine parallel execution of this method on computer clusters.<br /

Yield predictions of timothy (Phleum pratense L.) in Norway under future climate scenarios

The perennial forage grass timothy (Phleum pratense L.) is the most important forage crop in Norway. Future changes in the climate will affect growing conditions and hence the yield output. We used data from the Norwegian Value for Cultivation and Use testing to find a statistical prediction model for total dry matter yield (DMY) based on agro-climatic variables. The statistical model selection found that the predictors with the highest predictive power were growing degree days (GDD) in July and the number of days with rain (>1mm) in June–July. These predictors together explained 43% of the variability in total DMY. Further, the prediction model was combined with a range of climate ensembles (RCP4.5) to project DMY of timothy for the decades 2050–2059 and 2090–2099 at 8 locations in Norway. Our projections forecast that DMY of today’s timothy varieties may decrease substantially in South-Eastern Norway, but increase in Northern Norway, by the middle of the century, due to increased temperatures and changing precipitation patterns

Staphylococcal protein Ecb impairs complement receptor-1 mediated recognition of opsonized bacteria

Staphyloccus aureus is a major human pathogen leading frequently to sepsis and soft tissue infections with abscesses. Multiple virulence factors including several immune modulating molecules contribute to its survival in the host. When S. aureus invades the human body, one of the first line defenses is the complement system, which opsonizes the bacteria with C3b and attract neutrophils by release of chemotactic peptides. Neutrophils express Complement receptor-1 [CR1, CD35) that interacts with the C3b-opsonized particles and thereby plays an important role in pathogen recognition by phagocytic cells. In this study we observed that a fraction of S. aureus culture supernatant prevented binding of C3b to neutrophils. This fraction consisted of S. aureus leukocidins and Efb. The C-terminus of Efb is known to bind C3b and shares significant sequence homology to the extracellular complement binding protein [Ecb). Here we show that S. aureus Ecb displays various mechanisms to block bacterial recognition by neutrophils. The presence of Ecb blocked direct interaction between soluble CR1 and C3b and reduced the cofactor activity of CR1 in proteolytic inactivation of C3b. Furthermore, Ecb could dose-dependently prevent recognition of C3b by cell-bound CR1 that lead to impaired phagocytosis of NHS-opsonized S. aureus. Phagocytosis was furthermore reduced in the presence of soluble CR1 [sCR1). These data indicate that the staphylococcal protein Ecb prevents recognition of C3b opsonized bacteria by neutrophil CR1 leading to impaired killing by phagocytosis and thereby contribute to immune evasion of S. aureus.Peer reviewe

Microbes Bind Complement Inhibitor Factor H via a Common Site

To cause infections microbes need to evade host defense systems, one of these being the evolutionarily old and important arm of innate immunity, the alternative pathway of complement. It can attack all kinds of targets and is tightly controlled in plasma and on host cells by plasma complement regulator factor H (FH). FH binds simultaneously to host cell surface structures such as heparin or glycosaminoglycans via domain 20 and to the main complement opsonin C3b via domain 19. Many pathogenic microbes protect themselves from complement by recruiting host FH. We analyzed how and why different microbes bind FH via domains 19–20 (FH19-20). We used a selection of FH19-20 point mutants to reveal the binding sites of several microbial proteins and whole microbes (Haemophilus influenzae, Bordetella pertussis, Pseudomonas aeruginosa, Streptococcus pneumonia, Candida albicans, Borrelia burgdorferi, and Borrelia hermsii). We show that all studied microbes use the same binding region located on one side of domain 20. Binding of FH to the microbial proteins was inhibited with heparin showing that the common microbial binding site overlaps with the heparin site needed for efficient binding of FH to host cells. Surprisingly, the microbial proteins enhanced binding of FH19-20 to C3b and down-regulation of complement activation. We show that this is caused by formation of a tripartite complex between the microbial protein, FH, and C3b. In this study we reveal that seven microbes representing different phyla utilize a common binding site on the domain 20 of FH for complement evasion. Binding via this site not only mimics the glycosaminoglycans of the host cells, but also enhances function of FH on the microbial surfaces via the novel mechanism of tripartite complex formation. This is a unique example of convergent evolution resulting in enhanced immune evasion of important pathogens viautilization of a “superevasion site.

PLAST: parallel local alignment search tool for database comparison

Background: Sequence similarity searching is an important and challenging task in molecular biology and next-generation sequencing should further strengthen the need for faster algorithms to process such vast amounts of data. At the same time, the internal architecture of current microprocessors is tending towards more parallelism, leading to the use of chips with two, four and more cores integrated on the same die. The main purpose of this work was to design an effective algorithm to fit with the parallel capabilities of modern microprocessors. Results: A parallel algorithm for comparing large genomic banks and targeting middle-range computers has been developed and implemented in PLAST software. The algorithm exploits two key parallel features of existing and future microprocessors: the SIMD programming model (SSE instruction set) and the multithreading concept (multicore). Compared to multithreaded BLAST software, tests performed on an 8-processor server have shown speedup ranging from 3 to 6 with a similar level of accuracy. Conclusions: A parallel algorithmic approach driven by the knowledge of the internal microprocessor architecture allows significant speedup to be obtained while preserving standard sensitivity for similarity search problems.

Search reduction in hierarchical distributed problem solving

Knoblock and Korf have determined that abstraction can reduce search at a single agent from exponential to linear complexity (Knoblock 1991; Korf 1987). We extend their results by showing how concurrent problem solving among multiple agents using abstraction can further reduce search to logarithmic complexity. We empirically validate our formal analysis by showing that it correctly predicts performance for the Towers of Hanoi problem (which meets all of the assumptions of the analysis). Furthermore, a powerful form of abstraction for large multiagent systems is to group agents into teams, and teams of agents into larger teams, to form an organizational pyramid. We apply our analysis to such an organization of agents and demonstrate the results in a delivery task domain. Our predictions about abstraction's benefits can also be met in this more realistic domain, even though assumptions made in our analysis are violated. Our analytical results thus hold the promise for explaining in general terms many experimental observations made in specific distributed AI systems, and we demonstrate this ability with examples from prior research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42828/1/10726_2005_Article_BF01384251.pd

Accelerated large-scale multiple sequence alignment

<p>Abstract</p> <p>Background</p> <p>Multiple sequence alignment (MSA) is a fundamental analysis method used in bioinformatics and many comparative genomic applications. Prior MSA acceleration attempts with reconfigurable computing have only addressed the first stage of progressive alignment and consequently exhibit performance limitations according to Amdahl's Law. This work is the first known to accelerate the third stage of progressive alignment on reconfigurable hardware.</p> <p>Results</p> <p>We reduce subgroups of aligned sequences into discrete profiles before they are pairwise aligned on the accelerator. Using an FPGA accelerator, an overall speedup of up to 150 has been demonstrated on a large data set when compared to a 2.4 GHz Core2 processor.</p> <p>Conclusions</p> <p>Our parallel algorithm and architecture accelerates large-scale MSA with reconfigurable computing and allows researchers to solve the larger problems that confront biologists today. Program source is available from <url>http://dna.cs.byu.edu/msa/</url>.</p