A novel infrared video surveillance system using deep learning based techniques

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.This paper presents a new, practical infrared video based surveillance system, consisting of a resolution-enhanced, automatic target detection/recognition (ATD/R) system that is widely applicable in civilian and military applications. To deal with the issue of small numbers of pixel on target in the developed ATD/R system, as are encountered in long range imagery, a super-resolution method is employed to increase target signature resolution and optimise the baseline quality of inputs for object recognition. To tackle the challenge of detecting extremely low-resolution targets, we train a sophisticated and powerful convolutional neural network (CNN) based faster-RCNN using long wave infrared imagery datasets that were prepared and marked in-house. The system was tested under different weather conditions, using two datasets featuring target types comprising pedestrians and 6 different types of ground vehicles. The developed ATD/R system can detect extremely low-resolution targets with superior performance by effectively addressing the low small number of pixels on target, encountered in long range applications. A comparison with traditional methods confirms this superiority both qualitatively and quantitativelyThis work was funded by Thales UK, the Centre of Excellence for Sensor and Imaging System (CENSIS), and the Scottish Funding Council under the project “AALART. Thales-Challenge Low-pixel Automatic Target Detection and Recognition (ATD/ATR)”, ref. CAF-0036. Thanks are also given to the Digital Health and Care Institute (DHI, project Smartcough-MacMasters), which partially supported Mr. Monge-Alvarez’s contribution, and to the Royal Society of Edinburgh and National Science Foundation of China for the funding associated to the project “Flood Detection and Monitoring using Hyperspectral Remote Sensing from Unmanned Aerial Vehicles”, which partially covered Dr. Casaseca-de-la-Higuera’s, Dr. Luo’s, and Prof. Wang’s contribution. Dr. Casaseca-de-la-Higuera would also like to acknowledge the Royal Society of Edinburgh for the funding associated to project “HIVE”

Governing Antimicrobial Resistance (AMR) in a Changing Climate: A Participatory Scenario Planning Approach Applied to Sweden in 2050

Background: Antimicrobial resistance (AMR) is a growing global crisis with long-term and unpredictable health, social and economic impacts, with which climate change is likely to interact. Understanding how to govern AMR amidst evolving climatic changes is critical. Scenario planning offers a suitable approach. By envisioning alternative futures, stakeholders more effectively can identify consequences, anticipate problems, and better determine how to intervene. This study explored future worlds and actions that may successfully address AMR in a changing climate in a high-income country, using Sweden as the case.Methods: We conducted online scenario-building workshops and interviews with eight experts who explored: (1) how promising interventions (taxation of antimicrobials at point of sale, and infection prevention measures) could each combat AMR in 2050 in Sweden given our changing climate; and (2) actions to take starting in 2030 to ensure success in 2050. Transcripts were thematically analyzed to produce a narrative of participant validated alternative futures.Results: Recognizing AMR to be a global problem requiring global solutions, participants looked beyond Sweden to construct three alternative futures: (1) “Tax Burn Out” revealed taxation of antimicrobials as a low-impact intervention that creates inequities and thus would fail to address AMR without other interventions, such as infection prevention measures. (2) “Addressing the Basics” identified infection prevention measures as highly impactful at containing AMR in 2050 because they would contribute to achieving the Sustainable Development Goals (SDGs), which would be essential to tackling inequities underpinning AMR and climate change, and help to stabilize climate-induced mass migration and conflicts; and (3) ”Siloed Nations” described a movement toward nationalism and protectionism that would derail the “Addressing the Basics” scenario, threatening health and wellbeing of all. Several urgent actions were identified to combat AMR long-term regardless which future un-folds, such as global collaboration, and a holistic approach where AMR and climate change are addressed as interlinked issues.Conclusion: Our participatory scenario planning approach enabled participants from different sectors to create shared future visions and identify urgent actions to take that hinge on global collaboration, addressing AMR and climate change together, and achieving the SDGs to combat AMR under a changing climate

Factors influencing antimicrobial resistance in the European food system and potential leverage points for intervention: A participatory, One Health study

Introduction Antimicrobial resistance (AMR) is a global crisis that evolves from a complex system of factors. Understanding what factors interact is key to finding solutions. Our objective was to identify the factors influencing AMR in the European food system and places to intervene. Materials and methods We conducted two workshops involving participants with diverse perspectives to identify the factors influencing AMR and leverage points (places) to target interventions. Transcripts were open coded for factors and connections, then transcribed into Vensim 8.0.4 to develop a causal loop diagram (CLD) and compute the number of feedback loops. Thematic analysis followed to describe AMR dynamics in Europe’s food system and places for intervention. The CLD and themes were confirmed via participant feedback. Results Seventeen participants representing human, animal and agricultural sectors identified 91 CLD factors and 331 connections. Seven themes (e.g., social and economic conditions) describing AMR dynamics in Europe’s food system, five ‘overarching factors’ that impact the entire CLD system (e.g., leadership) and fourteen places for intervention (e.g., consumer demand) emerged from workshop discussions. Most leverage points fell on highly networked feedback loops suggesting that intervening at these places may create unpredictable consequences. Conclusions Our study produced a CLD of factors influencing AMR in Europe’s food system that implicates sectors across the One Health spectrum. The high connectivity between the CLD factors described by participants and our finding that factors are connected with many feedback mechanisms underscores the complexity of the AMR problem and the challenge with finding long-term solutions. Identifying factors and feedbacks helped identify relevant leverage points in the system. Some actions, such as government’s setting AMU standards may be easier to implement. These actions in turn can support multi-pronged actions that can help redefine the vision, values and goals of the system to sustainably tackle AMR

Extensive Geographic Mosaicism in Avian Influenza Viruses from Gulls in the Northern Hemisphere

Due to limited interaction of migratory birds between Eurasia and America, two independent avian influenza virus (AIV) gene pools have evolved. There is evidence of low frequency reassortment between these regions, which has major implications in global AIV dynamics. Indeed, all currently circulating lineages of the PB1 and PA segments in North America are of Eurasian origin. Large-scale analyses of intercontinental reassortment have shown that viruses isolated from Charadriiformes (gulls, terns, and shorebirds) are the major contributor of these outsider events. To clarify the role of gulls in AIV dynamics, specifically in movement of genes between geographic regions, we have sequenced six gull AIV isolated in Alaska and analyzed these along with 142 other available gull virus sequences. Basic investigations of host species and the locations and times of isolation reveal biases in the available sequence information. Despite these biases, our analyses reveal a high frequency of geographic reassortment in gull viruses isolated in America. This intercontinental gene mixing is not found in the viruses isolated from gulls in Eurasia. This study demonstrates that gulls are important as vectors for geographically reassorted viruses, particularly in America, and that more surveillance effort should be placed on this group of birds

Characterizing monoclonal antibody epitopes by filtered gene fragment phage display

In the present paper, we describe a novel approach to map monoclonal antibody epitopes, using three new monoclonal antibodies that recognize h-TG2 (human transglutaminase 2) as an example. The target gene was fragmented and cloned upstream of an antibiotic-resistance gene, in the vector pPAO2, to select for in-frame polypeptides. After removal of the antibiotic-resistance gene by Cre/Lox recombination, an antigen fragment phage display library was created and selected against specific monoclonal antibodies. Using the h-TG2 fragment library, we were able to identify epitopes. This technique can also be broadly applied to the study of protein–protein interactions