Multiple Mobile Robots Coordination in Shared Workspace for Task Makespan Minimization

In this paper we consider a system of multiple mobile robots (MMRS) and the process of their concurrent motion in a shared two-dimensional workspace. The goal is to plan the robot movement along given fixed paths so as to minimize the completion time of all the robots while ensuring that they never collide. Thus, the considered problem combines the problems of robot schedule optimization with collision and deadlock avoidance. The problem formulation is presented and its equivalent reformulation that does not depend explicitly on the geometry of the robot paths is proposed. An event-based solution representation is proposed, allowing for a discrete optimization approach. Two types of possible deadlocks are identified and deadlock avoidance procedures are discussed. We proposed two types of solving methods. First, we implemented two metaheuristics: the local-search-based taboo search as well as the population-based artificial bee colony. Next, we implemented 14 simple constructive algorithms, employing dispatch rules such as first-in first-out, shortest distance remaining first, and longest distance remaining first, among others. A set of problem instances for different numbers of robots is created and provided as a benchmark. The effectiveness of the solving methods is then evaluated by simulation using the generated instances. Both deterministic and lognormal-distributed uncertain robot travel times are considered. The results prove that the taboo search metaheuristic obtained the best results for both deterministic and uncertain cases, with only artificial bee colony and a few constructive algorithms managing to remain competitive. Detailed results as well as ideas to further improve proposed methods are discussed

Data from: Linking the respiration of fungal sporocarps with their nitrogen concentration: variation among species, tissues, and guilds

Tissue nitrogen (N) concentration has been correlated with respiration (RS) across plants of different life forms, functional and phylogenetic groups, plant organs and ectomycorrhizae of different fungal species. Nothing is known, however, if a similar relationship exists in other organisms like fungi. Here, we explored the N-RS relationship across sporocarps of 93 fungal species that varied in their guilds (mutualistic, saprotrophic, and parasitic) as well as “tissue” types (caps and stipes). We hypothesized that RS, N and protein concentrations were higher for saprotrophic fungi than either mutualistic and parasitic fungi and were higher for caps than for stipes. We also hypothesized that respiration of fungal guild could be predicted by the N concentration. Lastly we predicted N and RS were phylogenetically conserved and that by subtracting metabolically inactive N in chitin, we could improve the N-RS relationship. Sporocarp N concentration only explained 26% of the variation in RS across species. We found a significant difference in the N-RS relationship among the three fungal guilds, but no difference between the two tissue types. Saprotrophic species had higher N concentration and respiration than mutualistic and parasitic fungal species. Sporocarp components differed with caps showing both higher respiration and higher N and protein concentrations than stipes. Overall, our results show that fungal sporocarp nitrogen concentration is phylogenetically conserved among fungal families and may prove to be a strong predictor of fungal guild. The positive N-RS relationships existed for all fungal species (similar to plants), within fungal guilds (similar to plant functional groups), and fungal “tissue” types (like plants’ organs). The clear linkage of fungal sporocarp respiration to total N concentration could help improve C and N cycling models in forest ecosystems by including estimates of fungal respiration based on fungal N concentration

Trocha_Data_FE2015-00294

The file contains data on respiration (RS) (nmol O2 g-1 s-1) and nitrogen concentration (%N) of 93 species of fungal sporocarps of different fungal guilds (ECM-ectomycorrhizal, SAP-saprotrophic, and PAR-parasitic); the file contains also information on RS and %N in fungal "tissues" (cap, stipe, and as 'sporocarp' for those species do not form cap-and-stipe fruiting bodies); the number of each RS and %N measurement and sporocarp repeat is also included

Clinical implementation of RNA sequencing for Mendelian disease diagnostics

Background Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics. Methods We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage. Results We detected on average 12,500 genes per sample including around 60% of all disease genes-a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than 1 week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. Conclusion Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics