Influence of ROV umbilical on power quality when supplying electrical loads

The paper investigates the effects of a 3 km electrical umbilical cable on power transmission for an "island" supply onboard an all/more electric 'work-class' remote operated vehicle (ROV). It is shown how the chosen transmission voltage and frequency influence efficiency and the selection of power transmission components. A key feature of the paper is a discussion on the use of matrix converters for the propulsion thruster drive system; thereby allowing the input displacement factor to be varied to maintain maximum power transmission efficiency, independent of the thruster power factor. The natural impedance characteristics of the umbilical cable are also considered as means of reducing the input filter requirements for such converter

Drive systems for operation on deep-sea ROVs

Power systems for thruster actuators and other auxiliaries employed on work-class deep-sea ROVs subject to 300bar ambient pressures, are considered. Emphasis on 3×3 matrix converters for thrusters and 3×2 matrix converters for system auxiliaries, is given, along with experimental results showing operation during pressure cycling consistent with typical operational duties

Sensorless control of deep-sea ROVs PMSMs excited by matrix converters

The paper reports the development of model-based sensorless control methodologies for driving PMSMs using matrix converters. In particular, experimental results show that observer-based state-estimation techniques normally employed for sensorless control of PMSMs using voltage source inverters (VSIs), can be readily exported to matrix converter counterparts with minimal additional computational overhead. Furthermore, zero speed start-up and speed reversal are experimentally demonstrated. Finally, the observer is designed to be fault tolerant such that upon detection of a broken terminal (phase fault), the PMSM remains operational and could be utilized to provide a limp-home capabilit

Qualitative assessment of the entry of capripoxviruses into Great Britain from the European Union through importation of ruminant hides, skins and wool

Sheep pox and goat pox (SPGP) virus and lumpy skin disease (LSD) virus belong to the genus Capripoxvirus and cause disease with economic impacts in sheep/goats and cattle respectively. In 2013/14, outbreaks of SPGP were reported in sheep in Greece and Bulgaria and LSD outbreaks were reported in cattle in Turkey, Egypt and some countries in the Middle East. Clinical signs for both diseases include pox lesions, papules and scabs on the skin which may contain virus. This, together with the fact that Great Britain (GB) currently imports cattle hides, sheep skins and wool from European Union (EU) countries without the requirement for treatment prior to export, raises concern that capripoxviruses could be introduced into GB. A qualitative assessment presented here concluded that the current risk of entry of SPGP virus into GB through the importation of one untreated sheep skin, hide or wool bale from an EU Member State (MS) with similar flock prevalence to that in sheep in Greece in 2013/14 is low. In terms of SPGP virus levels, those infected sheep skins/hides entering GB are more likely to be from infected animals with normal skin (i.e., not showing lesions) and hence carrying lower levels of virus than those from animals showing papules and scabs which contain very high virus levels and are easier to detect. The predicted risk of importation of LSD virus per cattle hide/skin is also low (assuming LSD were to emerge in an EU MS with similar herd prevalence to that reported for SPGP in Greece in 2013/14). The levels of LSD virus on an infected cow's hide, if imported, may be very low. It is recommended that the risks for entry of capripoxviruses are recalculated if outbreaks occur elsewhere within the EU

Pathways for entry of livestock arboviruses into Great Britain : assessing the strength of evidence

The emergence of bluetongue virus and Schmallenberg virus in Great Britain (GB) during the last decade has highlighted the need for understanding the relative importance of the various pathways of the entry of livestock arboviruses so as to help focus surveillance and mitigation. This study summarizes what is known for the main routes of entry and assesses the strength of the current evidence for and against. Entry through infected arthropod vectors is considered at the level of each life cycle stage for tick-, biting midge- and mosquito-borne viruses, and while there is evidence that this could happen through most tick and mosquito stages, strong evidence that only exists for entry through adult midges. There is also strong evidence that entry through immature midge stages could not happen. The weight of supporting evidence is strongest for importation of viraemic livestock including horses. While there is some indication of a common pathway for midge-borne viruses from sub-Saharan Africa to GB via Continental Europe, other factors such as maternal transmission in dogs and sheep need to be considered in the light of recent findings

Assessing the impact of climate change on vector-borne viruses in the EU through the elicitation of expert opinion

Expert opinion was elicited to undertake a qualitative risk assessment to estimate the current and future risks to the European Union (EU) from five vector-borne viruses listed by the World Organization for Animal Health. It was predicted that climate change will increase the risk of incursions of African horse sickness virus (AHSV), Crimean-Congo haemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV) into the EU from other parts of the world, with African swine fever virus (ASFV) and West Nile virus (WNV) being less affected. Currently the predicted risks of incursion were lowest for RVFV and highest for ASFV. Risks of incursion were considered for six routes of entry (namely vectors, livestock, meat products, wildlife, pets and people). Climate change was predicted to increase the risk of incursion from entry of vectors for all five viruses to some degree, the strongest effects being predicted for AHSV, CCHFV and WNV. This work will facilitate identification of appropriate risk management options in relation to adaptations to climate change

Q fever through consumption of unpasteurised milk and milk products – a risk profile and exposure assessment

Q fever is a zoonotic disease caused by the bacterium Coxiella burnetii which is endemic in cattle, sheep and goats in much of the world, including the United Kingdom (UK). There is some epidemiological evidence that a small proportion of cases in the developed world may arise from consumption of unpasteurised milk with less evidence for milk products such as cheese. Long maturation at low pH may give some inactivation in hard cheese, and viable C. burnetii are rarely detected in unpasteurised cheese compared to unpasteurised milk. Simulations presented here predict that the probability of exposure per person to one or more C. burnetii through the daily cumulative consumption of raw milk in the UK is 04203. For those positive exposures, the average level of exposure predicted is high at 1266 guinea pig intraperitoneal infectious dose 50% units (GP_IP_ID50) per person per day. However, in the absence of human dose–response data, the case is made that the GP_IP_ID50 unit represents a very low risk through the oral route. The available evidence suggests that the risks from C. burnetii through consumption of unpasteurised milk and milk products (including cheese) are not negligible but they are lower in comparison to transmission via inhalation of aerosols from parturient products and livestock contact

A transmission model for Salmonella in grower-finisher pigs

This paper presents a model describing the dynamic transmission of Salmonella Typhimurium between pigs on a typical, British pig grower-finisher farm. A modified Reed-Frost discrete-time model was used to estimate the probability of infection for susceptible pigs

A farm transmission model for Salmonella in pigs for individual EU Member States

The burden of Salmonella entering pig slaughterhouses across the European Union (EU) is considered to be of public health significance. Therefore, targets will be set for each EU Member State (MS) to reduce the prevalence of Salmonella in pigs at slaughter. As part of the evidence base for the development of National Control Plans (NCPs), a Quantitative Microbiological Risk Assessment (QMRA) was funded to support the scientific opinion required by the EC from the European Food Safety Authority, and subsequently adopted by the BIOHAZ panel

Editorial: Integrating Whole Genome Sequencing Into Source Attribution and Risk Assessment of Foodborne Bacterial Pathogens

Source attribution and microbial risk assessment have proved to be crucial to identify and prioritize food safety interventions as to effectively control the burden of human illnesses (Cassini et al., 2016; Mughini-Gras et al., 2018a, 2019). By comparing human cases and pathogen occurrences in selected animal, food, and environmental sources, microbial subtyping approaches were successfully applied to pinpoint the most important sources of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and Listeria monocytogenes (Hald et al., 2004; Mullner et al., 2009a,b; Barco et al., 2013; Nielsen et al., 2017; Mughini-Gras et al., 2018b; Cody et al., 2019). Microbial risk assessment has been applied to assess known or potential adverse health effects resulting from human exposure to food-borne hazards. Through a scientific structured approach (FAO and WHO, 2021), microbial risk assessment helps to identify and quantify the risk represented by specific foods and the critical points in these foods' production chains for microbial control (Cassini et al., 2016; FAO and WHO, 2021). For both source attribution and risk assessment, one key challenge has been to define the hazard in question: is the whole foodborne pathogen species a hazard, or only some of its subtypes? In this regard the choice of the subtyping method becomes crucial. In recent years, Whole Genome Sequencing (WGS) has represented a major benefit for more targeted approaches, no longer focused on the species/genus level but at the level of subtypes (Franz et al., 2016; Fritsch et al., 2018; EFSA Panel on Biological Hazards, 2019). Besides WGS, metagenomics showed potentialities in source attribution. In particular, this approach was useful in attributing the source of environmental contamination by comparing the abundances of source-specific genetic markers (i.e., resistome) in different reservoirs (Gupta et al., 2019). Therefore, this special issue focuses on traditional and novel source attribution approaches applied on molecular, WGS, and metagenomic data as well as on a fine-tuning genetic characterization of foodborne pathogens useful for hazard identification and characterization. In particular, one study compares the outputs of a modified Hald model, which was applied to different subtyping input data of S. enterica Typhimurium and its monophasic variant (Arnold et al.) whereas two studies proposed a novel network approach and a method based on the core-genome genetic distance to attribute human infections of S. enterica Typhimurium monophasic variant and S. enterica Derby using WGS as input data (Merlotti et al.; Sévellec et al.). Another study by Duarte et al. included the relative abundance of antimicrobial resistance (AMR) associated genes (resistome) as metagenomic input data in an AMR source attribution study. Finally, two studies were focused on the molecular and genomic characterization of human isolates of Campylobacter jejuni and C. coli from China and of Listeria monocytogenes isolates collected from ready-to-eat meat and processing environment from Poland (Zhang et al.; Kurpas et al.). Arnold et al. performed a source attribution study including the genomes of S. enterica Typhimurium and its monophasic variant of 596 human sources and 327 animal sources from England and Wales between 2014 and 2016. Data from Seven Loci Multi Locus Sequence Typing (7-loci MLST), core-genome MLST (cg-MLST), and SNP calling were compared as input data. By applying a modified Hald model, 60% of human genomes were attributed to pork. Comparing different input data, results highlighted MLST as the method with the lowest fit and the lowest discriminatory power. Merlotti et al. applied a network approach to 351 human and animal genomes of S. enterica Typhimurium and its monophasic variant collected from 2013 to 2014. Three datasets of whole-genome MLST (wgMLST), cgMLST, and SNPs were used as input data. Genomes were clustered based on their genetic similarities. Interestingly, a higher percentage of cluster coherence was reported for animal sources in comparison to country and year of isolation, suggesting animal sources as the major driver of cluster formation. The approach showed to be effective in attributing up to 97.2% of human genomes to animal sources represented in the dataset. Among these genomes, the majority (84%) was attributed to pigs/pork. No significant differences were highlighted by comparing the three different input datasets. Core genome analysis was the approach applied by Sévellec et al. to attribute human sporadic cases of S. enterica Derby that occurred in France in 2014–2015 to non-human reservoirs. The authors analyzed 299 S. enterica Derby genomes corresponding to all S. enterica Derby sporadic human cases registered in the time frame, along with 141 non-human genomes. Within the non-human genomes, three main genomic lineages were detected in France: ST39-ST40 and ST682 associated to pork and ST71 associated to poultry. Within human genomes, 94% of S. enterica Derby clustered within the three genetic groups associated with pork, identifying this animal reservoir as the major contributor of S. enterica Derby to sporadic human cases in France. Relative abundance of antimicrobial resistance genes in shotgun metagenomic data was chosen in an antimicrobial resistance source attribution study by Duarte et al.. Starting from the assumption that fecal resistomes are source related, authors compared the resistomes of pooled fecal samples of pigs, broilers, turkeys, and veal calves with the resistomes of individual fecal samples of humans occupationally exposed to livestock production. Five supervised random forest models were applied on a total of 479 observations. Among the four livestock species, the results indicated that pigs have the resistome composition closest to the composition of the human resistome suggesting that occupational exposure to AMR determinants was higher among workers exposed to pigs than workers of broiler farms. Zhang et al. characterized genetic diversity and antimicrobial resistance of 236 Campylobacter jejuni and C. coli isolates collected from 2,945 individual stool samples of hospitalized patients with diarrhea in Beijing from 2017 to 2018. MLST results confirmed the high genetic diversity among isolates as well as CC21 as the most common clonal complex of C. jejuni in diarrhea patients in China. Clonal complex CC828 was the most frequently identified among C. coli isolates. Regarding antimicrobial resistance, rates higher than 88% were identified for the antimicrobials nalidixic acid, ciprofloxacin, and tetracycline. Last but not least, Kurpas et al. genetically characterized 48 L. monocytogenes isolates of PCR-serogroup IIb and IVb collected from ready-to-eat food and food processing environments. Additionally, the authors compared them with public genomes collected from humans in Poland. Among food isolates, 65% belonged to CC1, CC2, and CC6 already described as hypervirulent strains in humans. The clonal complex CC5 was also identified; mostly collected from food processing environments and belonging to PCR-serogroup IIB. Genomes of this clonal complex showed mutations in the inlA gene and a deletion of 144 bp in the inlB gene suggesting them as hypovirulent. Based on these studies, we conclude that the application of NGS data, in particular source attribution models, shows great potential. The results are improved by becoming more specific and to the point, which is considered very valuable for the decision support process. Integrations with phenotypic tests will continue to be essential for confirmation of NGS predicted outcomes