Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

Digital surveillance systems are ubiquitous and continuously generate massive amounts of data,and manual monitoring is required in order to recognise human activities in public areas.Intelligent surveillance systems that can automatically identify normal and abnormal activities are highly desirable,as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring.This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system.The proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step framework.In the first step,the salient frames are selected from the online video stream using a frame differencing method.A lightweight 3D convolutional neural network(3DCNN)architecture is applied to extract spatio-temporal features from the salient frames in the second step.Finally,the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the camera.The proposed system performs well compared to state-of-theart violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance networks.Comprehensive experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98%with an F1-score of 0.97 on the Hockey Fight dataset,and an accuracy of 99%with an F1-score of 0.98 on the Violent Crowd dataset.

China antimicrobial resistance surveillance network for pets(CARPet),2018 to 2021

China Antimicrobial Resistance Surveillance Network for Pets(CARPet)was established in 2021 to monitor the resist-ance profiles of clinical bacterial pathogens from companion animals.From 2018 to 2021,we recovered and tested 4,541 isolates from dogs and cats across 25 Chinese provinces,with Escherichia coli(18.5%)and Staphylococcus pseudintermedius(17.8%)being the most predominant bacterial species.The Enterobacterales were highly susceptible to tigecycline,meropenem,colistin,and amikacin(70.3%-100.0%),but showed moderate resistance to ampicillin,ceftriaxone,doxycycline,florfenicol,levofloxacin,enrofloxacin,and trimethoprim-sulfamethoxazole(29.3%-56.7%).About 66.3%of Acinetobacter spp.were resistant to florfenicol,with relatively low resistance to another 11 antibiot-ics(1.2%-23.3%).The Pseudomonas spp.showed high susceptibility to colistin(91.7%)and meropenem(88.3%).The coagulase-positive Staphylococcus spp.showed higher resistance rates to most antimicrobial agents than coagulase-negative Staphylococcus isolates.However,over 90.0%of Staphylococcus spp.were susceptible to linezolid,dapto-mycin and rifampin,and no vancomycin-resistant isolates were detected.E.faecium isolates demonstrated higher resistance rates to most antimicrobial agents than E.faecalis isolates.Streptococcus spp.isolates showed low resistance to most antimicrobial agents except for doxycycline(78.2%)and azithromycin(68.8%).Overall,the tested clinical isolates showed high rates of resistance to commonly used antimicrobial agents in companion animals.Therefore,it is crucial to strengthen the monitoring of bacterial resistance in pets.By timely and effectively collecting,analyzing,and reporting antimicrobial resistance dynamics in pets,the CARPet network will become a powerful platform to provide scientific guidance for both pet medical care and public health.

CASCIRE surveillance network and work on avian influenza viruses

Studies on influenza virus by Chinese Academy of Sciences(CAS)could be traced back as early as 2005 by the CAS Key Laboratory of Pathogenic Microbiology and Immunology(CASPMI),who discovered that Qinghai-like Clade 2.2H5N1 subtype highly pathogenic avian influenza virus(HPAIV)first caused severe outbreak in wild birds in Qinghai Lake(Liu et al.,2005).

Global antimicrobial resistance:a system-wide comprehensive investigation using the Global One Health Index

Background:Antimicrobial resistance(AMR)is one of the top ten global public health challenges.However,given the lack of a comprehensive assessment of worldwide AMR status,our objective is to develop a One Health-based system-wide evaluation tool on global AMR.Methods:We have further developed the three-hierarchical Global One Health Index(GOHI)-AMR indicator scheme,which consists of five key indicators,17 indicators,and 49 sub-indicators,by incorporating 146 countries'data from diverse authoritative databases,including WHO's Global Antimicrobial Resistance and Use Surveillance System(GLASS)and the European CDC.We investigated the overall-or sub-rankings of GOHI-AMR at the international/regional/national levels for data preprocessing and score calculation utilizing the existing GOHI methodology.Additionally,a correlation analysis was conducted between the GOHI-AMR and other socioeconomic factors.Results:The average GOHI-AMR score for 146 countries is 38.45.As expected,high-income countries(HICs)outperform the other three income groups on overall rankings and all five key indicators of GOHI-AMR,whereas lowincome countries unexpectedly outperform upper-middle-income countries and lower-middle-income countries on the antibiotics-resistant key indicator(ARR)and ARR-subordinate indicators,including carbapenem-,β-lactam-,and quinolone resistance,and even HICs on aminoglycoside resistance.There were no significant differences among the four groups on the environmental-monitoring indicator(P>0.05).GOHI-AMR was positively correlated with gross domestic product,life expectancy,and AMR-related publications,but negatively with natural growth rate and chronic respiratory disease.In contrast to Cyprus,the remarkably lower prevalence of"ESKAPE pathogens"in high-scoring Sweden and Denmark highlights Europe's huge gaps.China and Russia outperformed the other three BRICS countries on all key indicators,particularly India's ARR and Brazil's AMR laboratory network and coordination capacity.Furthermore,significant internal disparities in carbapenem-resistant Klebsiella pneumoniae(CRKP)and methicillin-resistant Staphylococcus aureus(MRSA)prevalence were observed between China and the USA,with MRSA prevalence both gradually declining,whereas CRKP prevalence has been declining in the USA but increasing in China,consistent with higher carbapenems-related indicator'performance in USA.Conclusions:GOHI-AMR is the most comprehensive tool currently available for the assessment of AMR status worldwide.We discovered unique features impacting AMR in each country and offered precise recommendations to improve the capacity to tackle AMR in low-ranking countries.