The CORSMAL benchmark for the prediction of the properties of containers

13 pages, 6 tables, 7 figures, Pre-print submitted to IEEE AccessAuthors' post-print accepted for publication in IEEE Access, see https://doi.org/10.1109/ACCESS.2022.3166906 . 14 pages, 6 tables, 7 figuresThe contactless estimation of the weight of a container and the amount of its content manipulated by a person are key pre-requisites for safe human-to-robot handovers. However, opaqueness and transparencies of the container and the content, and variability of materials, shapes, and sizes, make this estimation difficult. In this paper, we present a range of methods and an open framework to benchmark acoustic and visual perception for the estimation of the capacity of a container, and the type, mass, and amount of its content. The framework includes a dataset, specific tasks and performance measures. We conduct an in-depth comparative analysis of methods that used this framework and audio-only or vision-only baselines designed from related works. Based on this analysis, we can conclude that audio-only and audio-visual classifiers are suitable for the estimation of the type and amount of the content using different types of convolutional neural networks, combined with either recurrent neural networks or a majority voting strategy, whereas computer vision methods are suitable to determine the capacity of the container using regression and geometric approaches. Classifying the content type and level using only audio achieves a weighted average F1-score up to 81% and 97%, respectively. Estimating the container capacity with vision-only approaches and estimating the filling mass with audio-visual multi-stage approaches reach up to 65% weighted average capacity and mass scores. These results show that there is still room for improvement on the design of new methods. These new methods can be ranked and compared on the individual leaderboards provided by our open framework

Genome Fragmentation Is Not Confined to the Peridinin Plastid in Dinoflagellates

When plastids are transferred between eukaryote lineages through series of endosymbiosis, their environment changes dramatically. Comparison of dinoflagellate plastids that originated from different algal groups has revealed convergent evolution, suggesting that the host environment mainly influences the evolution of the newly acquired organelle. Recently the genome from the anomalously pigmented dinoflagellate Karlodinium veneficum plastid was uncovered as a conventional chromosome. To determine if this haptophyte-derived plastid contains additional chromosomal fragments that resemble the mini-circles of the peridin-containing plastids, we have investigated its genome by in-depth sequencing using 454 pyrosequencing technology, PCR and clone library analysis. Sequence analyses show several genes with significantly higher copy numbers than present in the chromosome. These genes are most likely extrachromosomal fragments, and the ones with highest copy numbers include genes encoding the chaperone DnaK(Hsp70), the rubisco large subunit (rbcL), and two tRNAs (trnE and trnM). In addition, some photosystem genes such as psaB, psaA, psbB and psbD are overrepresented. Most of the dnaK and rbcL sequences are found as shortened or fragmented gene sequences, typically missing the 3′-terminal portion. Both dnaK and rbcL are associated with a common sequence element consisting of about 120 bp of highly conserved AT-rich sequence followed by a trnE gene, possibly serving as a control region. Decatenation assays and Southern blot analysis indicate that the extrachromosomal plastid sequences do not have the same organization or lengths as the minicircles of the peridinin dinoflagellates. The fragmentation of the haptophyte-derived plastid genome K. veneficum suggests that it is likely a sign of a host-driven process shaping the plastid genomes of dinoflagellates