Robots can be used to mitigate risks in unsafe and austere settings. In recent years, explosive ordnance disposal robots have reduced the technician's time-on-target, and thus, reduce the direct risk of exposure. This article focuses on the study and development of innovative techniques as the foundational work for a new robot platform. The proposed system includes an organic electrochemical transistor device to detect the existence of explosive residues, and lead to decisions for safe-removal progress. Taurus' surgical gripper facilitates object tactile exploration, and manipulation with control precision to the millimeter range. The highly sensitive triboelectric tactile sensor could reduce intrusiveness during contact, and mitigate the risk of detonation. Haptic devices and visual displays are used to convey important signals, in order to improve the situational awareness of the teleoperator. A machine learning classifier can be used to assist the user to identify objects from tactile sampling. The integration of these methodologies allows for a sensitive approach to concealed objects that are only accessible through tactile sensing.

Visual querying is essential for interactively exploring massive trajectory data. However, the data uncertainty imposes profound challenges to fulfill advanced analytics requirements. On the one hand, many underlying data does not contain accurate geographic coordinates, e.g., positions of a mobile phone only refer to the regions (i.e., mobile cell stations) in which it resides, instead of accurate GPS coordinates. On the other hand, domain experts and general users prefer a natural way, such as using a natural language sentence, to access and analyze massive movement data. In this paper, we propose a visual analytics approach that can extract spatial-temporal constraints from a textual sentence and support an effective query method over uncertain mobile trajectory data. It is built up on encoding massive, spatially uncertain trajectories by the semantic information of the POls and regions covered by them, and then storing the trajectory documents in text database with an effective indexing scheme. The visual interface facilitates query condition specification, situation-aware visualization, and semantic exploration of large trajectory data. Usage scenarios on real-world human mobility datasets demonstrate the effectiveness of our approach.

UNLABELLED: Sodium bisulfite conversion followed by sequencing (BS-Seq, such as whole genome bisulfite sequencing or reduced representation bisulfite sequencing) has become popular for studying human epigenetic profiles. Identifying single nucleotide polymorphisms (SNPs) is important for quantification of methylation levels and for study of allele-specific epigenetic events such as imprinting. However, SNP calling in such data is complex and time consuming. Here, we present an ultrafast and memory-efficient package named BS-SNPer for the exploration of SNP sites from BS-Seq data. Compared with Bis-SNP, a popular BS-Seq specific SNP caller, BS-SNPer is over 100 times faster and uses less memory. BS-SNPer also offers higher sensitivity and specificity compared with existing methods. AVAILABILITY AND IMPLEMENTATION: BS-SNPer is written in C++ and Perl, and is freely available at https://github.com/hellbelly/BS-Snper.

BACKGROUND: The availability of 12 fully sequenced Drosophila species genomes provides an excellent opportunity to explore the evolutionary mechanism, structure and function of gene families in Drosophila. Currently, several important resources, such as FlyBase, FlyMine and DroSpeGe, have been devoted to integrating genetic, genomic, and functional data of Drosophila into a well-organized form. However, all of these resources are gene-centric and lack the information of the gene families in Drosophila. DESCRIPTION: FlyPhy is a comprehensive phylogenomic analysis platform devoted to analyzing the genes and gene families in Drosophila. Genes were classified into families using a graph-based Markov Clustering algorithm and extensively annotated by a number of bioinformatic tools, such as basic sequence features, functional category, gene ontology terms, domain organization and sequence homolog to other databases. FlyPhy provides a simple and user-friendly web interface to allow users to browse and retrieve the information at multiple levels. An outstanding feature of the FlyPhy is that all the retrieved results can be added to a workset for further data manipulation. For the data stored in the workset, multiple sequence alignment, phylogenetic tree construction and visualization can be easily performed to investigate the sequence variation of each given family and to explore its evolutionary mechanism. CONCLUSION: With the above functionalities, FlyPhy will be a useful resource and convenient platform for the Drosophila research community. The FlyPhy is available at http://bioinformatics.zj.cn/fly/ .