A Social Distance Estimation and Crowd Monitoring System for Surveillance Cameras

Social distancing is crucial to restrain the spread of diseases such as COVID-19, but complete adherence to safety guidelines is not guaranteed. Monitoring social distancing through mass surveillance is paramount to develop appropriate mitigation plans and exit strategies. Nevertheless, it is a labor-intensive task that is prone to human error and tainted with plausible breaches of privacy. This paper presents a privacy-preserving adaptive social distance estimation and crowd monitoring solution for camera surveillance systems. We develop a novel person localization strategy through pose estimation, build a privacy-preserving adaptive smoothing and tracking model to mitigate occlusions and noisy/missing measurements, compute inter-personal distances in the real-world coordinates, detect social distance infractions, and identify overcrowded regions in a scene. Performance evaluation is carried out by testing the system's ability in person detection, localization, density estimation, anomaly recognition, and high-risk areas identification. We compare the proposed system to the latest techniques and examine the performance gain delivered by the localization and smoothing/tracking algorithms. Experimental results indicate a considerable improvement, across different metrics, when utilizing the developed system. In addition, they show its potential and functionality for applications other than social distancing.Peer reviewe

Iron Age and Anglo-Saxon genomes from East England reveal British migration history

British population history has been shaped by a series of immigrations, including the early Anglo-Saxon migrations after 400 CE. It remains an open question how these events affected the genetic composition of the current British population. Here, we present whole-genome sequences from 10 individuals excavated close to Cambridge in the East of England, ranging from the late Iron Age to the middle Anglo-Saxon period. By analysing shared rare variants with hundreds of modern samples from Britain and Europe, we estimate that on average the contemporary East English population derives 38% of its ancestry from Anglo-Saxon migrations. We gain further insight with a new method, rarecoal, which infers population history and identifies fine-scale genetic ancestry from rare variants. Using rarecoal we find that the Anglo-Saxon samples are closely related to modern Dutch and Danish populations, while the Iron Age samples share ancestors with multiple Northern European populations including Britain

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi

Mutations in the Beta Propeller WDR72 Cause Autosomal-Recessive Hypomaturation Amelogenesis Imperfecta

Healthy dental enamel is the hardest and most highly mineralized human tissue. Though acellular, nonvital, and without capacity for turnover or repair, it can nevertheless last a lifetime. Amelogenesis imperfecta (AI) is a collective term for failure of normal enamel development, covering diverse clinical phenotypes that typically show Mendelian inheritance patterns. One subset, known as hypomaturation AI, is characterised by near-normal volumes of organic enamel matrix but with weak, creamy-brown opaque enamel that fails prematurely after tooth eruption. Mutations in genes critical to enamel matrix formation have been documented, but current understanding of other key events in enamel biomineralization is limited. We investigated autosomal-recessive hypomaturation AI in a consanguineous Pakistani family. A whole-genome SNP autozygosity screen identified a locus on chromosome 15q21.3. Sequencing candidate genes revealed a point mutation in the poorly characterized WDR72 gene. Screening of WDR72 in a panel of nine additional hypomaturation AI families revealed the same mutation in a second, apparently unrelated, Pakistani family and two further nonsense mutations in Omani families. Immunohistochemistry confirmed intracellular localization in maturation-stage ameloblasts. WDR72 function is unknown, but as a putative β propeller is expected to be a scaffold for protein-protein interactions. The nearest homolog, WDR7, is involved in vesicle mobilization and Ca2+-dependent exocytosis at synapses. Vesicle trafficking is important in maturation-stage ameloblasts with respect to secretion into immature enamel and removal of cleaved enamel matrix proteins via endocytosis. This raises the intriguing possibility that WDR72 is critical to ameloblast vesicle turnover during enamel maturation

Risk Mapping of Groundwater-Drawdown-Induced Land Subsidence in Heterogeneous Soils on Large Areas

Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large-scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics-based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low-risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk-reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm