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This paper examines the use of digital video in public safety and surveillance systems. Traditionally video recordings are used by law enforcement to review events retrospectively and for evidential purposes in the pursuance of criminal prosecution. We also examine how, due to the proliferation of cameras around cities, human operators are challenged to monitor these data feeds in real-time and how the emergence of AI and computer vision solutions can process this data. Computer vision can enable the move from a purely reactive to a predictive, real-time analysis platform. As camera numbers and the resolution and framerate of cameras grow, existing network infrastructure frequently causes challenges provisioning low latency, high bandwidth networking to private or public cloud infrastructure for evidential storage. These technical challenges can provide issues for law enforcement providing a data chain of custody to ensure its admissibility during court proceedings. Emerging technologies offer solutions to overcome these challenges: the use of emerging edge compute capabilities, including the use of on-camera and mobile edge compute nodes providing compute capabilities closer to the data source and new software paradigms, including CI/CD methodologies, and the use of micro-services and containerization to manage and deliver applications across the portfolio of devices, at the edge of the network. Using Amazon Web Services as an example, we review how cloud providers are now overcoming challenges in delivering real time video analytics solutions in the classical cloud model, and how they are enabling services and platforms closer to the edge, while delivering the cloud computing experience of scalability and manageability across different edges of the network. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2005.09.007 Byline: Daniel J.F. Toal, Colin Flanagan, William B. Lyons, Sean Nolan, Elfed Lewis Keywords: Autonomous underwater vehicles; Optical fibre sensor; Obstacle avoidance; Behaviour-based control Abstract: This paper describes short range and tactile optical fibre sensors for marine applications. The sensors are designed for obstacle avoidance on unmanned underwater vehicles (UUVs) operating in confined spaces, but have other possible applications. The fibre sensors augment the sensory abilities derived from ultrasonic and other sensors employed for marine proximity measurement. Of particular interest is proximity detection in the 'near' (less than 1m) and tactile areas. The paper describes the basic principle of operation and alternative sensor configurations. Results are given based on laboratory tests and deployment on a mini autonomous submersible in a test pool. Author Affiliation: Department of Electronics and Computer Engineering, University of Limerick, Limerick, Ireland Article History: Received 28 November 2003; Revised 28 August 2005; Accepted 13 September 2005

One of the most abundant proteins in human saliva, mucin-7, is encoded by the MUC7 gene, which harbors copy number variable subexonic repeats (PTS-repeats) that affect the size and glycosylation potential of this protein. We recently documented the adaptive evolution of MUC7 subexonic copy number variation among primates. Yet, the evolution of MUC7 genetic variation in humans remained unexplored. Here, we found that PTS-repeat copy number variation has evolved recurrently in the human lineage, thereby generating multiple haplotypic backgrounds carrying five or six PTSrepeat copy number alleles. Contrary to previous studies, we found no associations between the copy number of PTSrepeats and protection against asthma. Instead, we revealed a significant association of MUC7 haplotypic variation with the composition of the oral microbiome. Furthermore, based on in-depth simulations, we conclude that a divergent MUC7 haplotype likely originated in an unknown African hominin population and introgressed into ancestors ofmodern Africans. [ABSTRACT FROM AUTHOR]

Human skin has evolved rapidly, leaving evolutionary signatures in the genome. The filaggrin (FLG) gene is widely studied for its skin-barrier function in humans. The extensive genetic variation in this gene, especially common loss-of-function (LoF) mutations, has been established as primary risk factors for atopic dermatitis. To investigate the evolution of this gene, we analyzed 2,504 human genomes and genotyped the copy number variation of filaggrin repeats within FLG in 126 individuals from diverse ancestral backgrounds. We were unable to replicate a recent study claiming that LoF of FLG is adaptive in northern latitudes with lower ultraviolet light exposure. Instead, we present multiple lines of evidence suggesting that FLG genetic variation, including LoF variants, have little or no effect on fitness in modern humans. Haplotype-level scrutinization of the locus revealed signatures of a recent selective sweep in Asia, which increased the allele frequency of a haplotype group (Huxian haplogroup) in Asian populations. Functionally, we found that the Huxian haplogroup carries dozens of functional variants in FLG and hornerin (HRNR) genes, including those that are associated with atopic dermatitis susceptibility, HRNR expression levels and microbiome diversity on the skin. Our results suggest that the target of the adaptive sweep is HRNR gene function, and the functional FLG variants that involve susceptibility to atopic dermatitis, seem to hitchhike the selective sweep on HRNR. Our study presents a novel case of a locus that harbors clinically relevant common genetic variation with complex evolutionary trajectories. [ABSTRACT FROM AUTHOR]