Feature fusion based deep spatiotemporal model for violence detection in videos

© Springer Nature Switzerland AG 2019. It is essential for public monitoring and security to detect violent behavior in surveillance videos. However, it requires constant human observation and attention, which is a challenging task. Autonomous detection of violent activities is essential for continuous, uninterrupted video surveillance systems. This paper proposed a novel method to detect violent activities in videos, using fused spatial feature maps, based on Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) units. The spatial features are extracted through CNN, and multi-level spatial features fusion method is used to combine the spatial features maps from two equally spaced sequential input video frames to incorporate motion characteristics. The additional residual layer blocks are used to further learn these fused spatial features to increase the classification accuracy of the network. The combined spatial features of input frames are then fed to LSTM units to learn the global temporal information. The output of this network classifies the violent or non-violent category present in the input video frame. Experimental results on three different standard benchmark datasets: Hockey Fight, Crowd Violence and BEHAVE show that the proposed algorithm provides better ability to recognize violent actions in different scenarios and results in improved performance compared to the state-of-the-art methods

Contrasting views on the role of mesenchymal stromal/stem cells in tumour growth : a systematic review of experimental design

The effect of mesenchymal stromal/stem cells (MSCs) on tumour growth remains controversial. Experimental evidence supports both an inhibitory and a stimulatory effect. We have assessed factors responsible for the contrasting effects of MSCs on tumour growth by doing a meta-analysis of existing literature between 2000 and May 2017. We assessed 183 original research articles comprising 338 experiments. We considered (a) in vivo and in vitro experiments, (b) whether in vivo studies were syngeneic or xenogeneic, and (c) if animals were immune competent or deficient. Furthermore, the sources and types of cancer cells and MSCs were considered together with modes of cancer induction and MSC administration. 56% of all 338 experiments reported that MSCs promote tumour growth. 78% and 79% of all experiments sourced human MSCs and cancer cells, respectively. MSCs were used in their naïve and engineered form in 86% and 14% of experiments, respectively, the latter to produce factors that could alter either their activity or that of the tumour. 53% of all experiments were conducted in vitro with 60% exposing cancer cells to MSCs via coculture. Of all in vivo experiments, 79% were xenogeneic and 63% were conducted in immune-competent animals. Tumour growth was inhibited in 80% of experiments that used umbilical cord-derived MSCs, whereas tumour growth was promoted in 64% and 57% of experiments that used bone marrow- and adipose tissue-derived MSCs, respectively. This contrasting effect of MSCs on tumour growth observed under different experimental conditions may reflect differences in experimental design. This analysis calls for careful consideration of experimental design given the large number of MSC clinical trials currently underway.The South African Medical Research Council in terms of the SAMRC’s Flagship Award Project SAMRC-RFA-UFSP-01-2013/STEM CELLS, the SAMRC Extramural Stem Cell Research and Therapy Unit, the National Research Foundation of South Africa (grant no. 86942), the National Health Laboratory Services Research Trust (grant no. 94453), the University of Pretoria Research Development Programme (A0Z778), the University of Pretoria Vice Chancellor’s Postdoctoral Fellowship and the Institute for Cellular and Molecular Medicine of the University of Pretoria.http://www.springer.comseries/5584hj2019ImmunologyOral Pathology and Oral Biolog

Differential expression of parental alleles of BRCA1 in human preimplantation embryos

Gene expression from both parental genomes is required for completion of embryogenesis. Differential methylation of each parental genome has been observed in mouse and human preimplantation embryos. It is possible that these differences in methylation affect the level of gene transcripts from each parental genome in early developing embryos. The aim of this study was to investigate if there is a parent-specific pattern of BRCA1 expression in human embryos and to examine if this affects embryo development when the embryo carries a BRCA1 or BRCA2 pathogenic mutation. Differential parental expression of ACTB, SNRPN, H19 and BRCA1 was semi-quantitatively analysed by minisequencing in 95 human preimplantation embryos obtained from 15 couples undergoing preimplantation genetic diagnosis. BRCA1 was shown to be differentially expressed favouring the paternal transcript in early developing embryos. Methylation-specific PCR showed a variable methylation profile of BRCA1 promoter region at different stages of embryonic development. Embryos carrying paternally inherited BRCA1 or 2 pathogenic variants were shown to develop more slowly compared with the embryos with maternally inherited BRCA1 or 2 pathogenic mutations. This study suggests that differential demethylation of the parental genomes can influence the early development of preimplantation embryos. Expression of maternal and paternal genes is required for the completion of embryogenesis

UA-DETRAC 2018: report of AVSS2018 IWT4S challenge on advanced traffic monitoring

A desirable smart traffic-monitoring and street-safety system can elicit and support the intervention of law enforcement agencies or medical staff. Recently, there has been a dramatically higher demand for such smart systems. To this end, the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S) was organized in conjunction with the 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS 2018). Our goal is to advance the state-of-the-art detection and tracking algorithms and provide a comprehensive performance evaluation for them. We evaluate 5 submitted detection and 7 submitted tracking methods on the large-scale UA-DETRAC benchmark, and the results are shared publicly on the website http://detrac-db. rit.albany.edu. We expect this challenge to advance the research and development of new detection and tracking methods for transportation applications