Recent advances in unmanned aerial vehicles real-time trajectory planning

The growing interest in Unmanned Aerial Vehicles (UAV) can be attributed to many factors, particularly the potential for them to operate beyond visual line of sight and at increasingly higher level of autonomy. Trajectory planning defines the extent to which a vehicle is ‘autonomous’. Therefore, to operate at high levels of autonomy, UAV will require real-time embedded trajectory planning that respects a minimum of flyability. This paper presents a review of recent advances in UAV trajectory planning and seeks to clarify the flyability, the real-time and the embedded aspects, which are not adequately considered by previous survey papers. This work, which specifically focuses on Class II (≥ 150 kg and ≤ 600 kg) and Class III (> 600 kg) fixed wing UAV, analyses 60 papers from this last decade that mention some real-time achievement with respect to UAV trajectory planning. From this analysis, we highlight some challenges and some suggested orientations for future works.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Environment and host species shape the skin microbiome of captive neotropical bats

Background A wide range of microorganisms inhabit animal skin. This microbial community (microbiome) plays an important role in host defense against pathogens and disease. Bats (Chiroptera: Mammalia) are an ecologically and evolutionarily diversified group with a relatively unexplored skin microbiome. The bat skin microbiome could play a role in disease resistance, for example, to white nose syndrome (WNS), an infection which has been devastating North American bat populations. However, fundamental knowledge of the bat skin microbiome is needed before understanding its role in health and disease resistance. Captive neotropical frugivorous bats Artibeus jamaicensis and Carollia perspicillataprovide a simple controlled system in which to characterize the factors shaping the bat microbiome. Here, we aimed to determine the relative importance of habitat and host species on the bat skin microbiome. Methods We performed high-throughput 16S rRNA gene sequencing of the skin microbiome of two different bat species living in captivity in two different habitats. In the first habitat, A. jamaicensis and C. perspicillata lived together, while the second habitat contained only A. jamaicensis. Results We found that both habitat and host species shape the composition and diversity of the skin microbiome, with habitat having the strongest influence. Cohabitating A. jamaicensis and C. perspicillata shared more similar skin microbiomes than members of the same species (A. jamaicensis) across two habitats. Discussion These results suggest that in captivity, the skin microbial community is homogenised by the shared environments and individual proximities of bats living together in the same habitat, at the expense of the innate host species factors. The predominant influence of habitat suggests that environmental microorganisms or pathogens might colonize bat skin. We also propose that bat populations could differ in pathogen susceptibility depending on their immediate environment and habitat

Enrichment of beneficial bacteria in the skin microbiota of bats persisting with white-nose syndrome

Background Infectious diseases of wildlife are increasing worldwide with implications for conservation and human public health. The microbiota (i.e. microbial community living on or in a host) could influence wildlife disease resistance or tolerance. White-nose syndrome (WNS), caused by the fungus Pseudogymnoascus destructans (Pd), has killed millions of hibernating North American bats since 2007. We characterized the skin microbiota of naïve, pre-WNS little brown bats (Myotis lucifugus) from three WNS-negative hibernation sites and persisting, previously exposed bats from three WNS-positive sites to test the hypothesis that the skin microbiota of bats shifts following WNS invasion. Results Using high-throughput 16S rRNA gene sequencing on 66 bats and 11 environmental samples, we found that hibernation site strongly influenced the composition and diversity of the skin microbiota. Bats from WNS-positive and WNS-negative sites differed in alpha and beta diversity, as well as in microbiota composition. Alpha diversity was reduced in persisting, WNS-positive bats, and the microbiota profile was enriched with particular taxa such Janthinobacterium, Micrococcaceae, Pseudomonas, Ralstonia, and Rhodococcus. Some of these taxa are recognized for their antifungal activity, and specific strains of Rhodococcus and Pseudomonas are known to inhibit Pd growth. Composition of the microbial community in the hibernaculum environment and the community on bat skin was superficially similar but differed in relative abundance of some bacterial taxa. Conclusions Our results are consistent with the hypothesis that Pd invasion leads to a shift in the skin microbiota of surviving bats and suggest the possibility that the microbiota plays a protective role for bats facing WNS. The detection of what appears to be enrichment of beneficial bacteria in the skin microbiota of persisting bats is a promising discovery for species re-establishment. Our findings highlight not only the potential value of management actions that might encourage transmission, growth, and establishment of beneficial bacteria on bats, and within hibernacula, but also the potential risks of such management actions

Additional file 7: of Enrichment of beneficial bacteria in the skin microbiota of bats persisting with white-nose syndrome

Major bacterial taxa identified in bat skin microbiota samples. The 16 more abundant taxa across all hibernacula are provided. Stars represent significant indicator taxa. *IndVal < 0.50, **IndVal ≥ 0.50, ***IndVal ≥ 0.89

Bat skin microbiome: metadata

<b>mapping_bats.txt</b> is the sampled bats mapping file<br><br><b>Bat_OTUs_table_TAX.biom</b> is the taxonomy assigned OTU by library matrix with of only non-chimeric sequences<br><br><b>unique.dbOTU.nonchimera.fasta</b> is a fasta file of only non-chimeric OTU representatives<br><br><b>BatTree</b> is the phylogenetic tree built with FastTree 2.1.8<strong><br><br>Summarize_OTUs_Table_bat_only </strong>is a summary file of the information in the biom table<strong>  <br><br><br></strong><br><br>  <sup> <br> <br> </sup

Bat skin microbiome: metadata

<b>mapping_bats.txt</b> is the sampled bats mapping file<br><br><b>Bat_OTUs_table_TAX.biom</b> is the taxonomy assigned OTU by library matrix with of only non-chimeric sequences<br><br><b>unique.dbOTU.nonchimera.fasta</b> is a fasta file of only non-chimeric OTU representatives<br><br><b>BatTree</b> is the phylogenetic tree built with FastTree 2.1.8<strong><br><br>Summarize_OTUs_Table_bat_only </strong>is a summary file of the information in the biom table<strong>  <br><br><br></strong><br><br>  <sup> <br> <br> </sup

Bat skin microbiome: raw sequencing data

Raw sequencing data. This experiment was carried out in two sequencing runs (Run1 and Run2). <br