Internet of Things Based Monitoring System of Leaks in Water Supply Networks Using Pressure-Based Model

Leaks in water distribution networks impose several impacts on economy, freshwater resources, water quality, health and safety. Fast leak detection and reparation is a key for lowering its negative impacts and associated costs with conventional detection techniques. This study has been used a pressure-based model to detect leaks events and its coordinates based on pressure and flow measurements. Pressure and flow data for systems that having leaks in their structure were analyzed and compared with data generated from non-leaking systems using EPANET software packages. An extension package of EPANET software (EpanetWaterGen) has been used as it has the advantage of its ability to better simulate leaks. The results show the ability of the model to detect leaks in a small and large water distribution networks with uncertainty level associated with low pressure change. The developed leak detection model utilizes pressure and flow sensors and enables the network managers and administrators to optimally place the sensors in a manner to increase efficiency and optimize cost. The system allows operators to detect leak location and volume of lost water, thus enabling a better and more efficient response to leaks, such that the network managers can address and respond to most urgent leaks and optimize the time end efforts of technical and maintenance personnel

Internet of Things Based Monitoring System of Leaks in Water Supply Networks Using Pressure-Based Model

Leaks in water distribution networks impose several impacts on economy, freshwater resources, water quality, health and safety. Fast leak detection and reparation is a key for lowering its negative impacts and associated costs with conventional detection techniques. This study has been used a pressure-based model to detect leaks events and its coordinates based on pressure and flow measurements. Pressure and flow data for systems that having leaks in their structure were analyzed and compared with data generated from non-leaking systems using EPANET software packages. An extension package of EPANET software (EpanetWaterGen) has been used as it has the advantage of its ability to better simulate leaks. The results show the ability of the model to detect leaks in a small and large water distribution networks with uncertainty level associated with low pressure change. The developed leak detection model utilizes pressure and flow sensors and enables the network managers and administrators to optimally place the sensors in a manner to increase efficiency and optimize cost. The system allows operators to detect leak location and volume of lost water, thus enabling a better and more efficient response to leaks, such that the network managers can address and respond to most urgent leaks and optimize the time end efforts of technical and maintenance personnel

Emergence and genomic characterization of the first reported optrA-carrying linezolid-resistant enterococci isolated from retail broiler meat in the United Arab Emirates

The foodborne transfer of resistant genes from enterococci to humans and their tolerance to several commonly used antimicrobials are of growing concern worldwide. Linezolid is a last-line drug for managing complicated illnesses resulting from multidrug-resistant Gram-positive bacteria. The optrA gene has been reported in enterococci as one of the acquired linezolid resistance mechanisms. The present study uses whole-genome sequencing analysis to characterize the first reported isolates of linezolid-resistant E. faecium (n = 6) and E. faecalis (n = 10) harboring the optrA gene isolated from samples of supermarket broiler meat (n = 165) in the United Arab Emirates (UAE). The sequenced genomes were used to appraise the study isolates’ genetic relatedness, antimicrobial resistance determinants, and virulence traits. All 16 isolates carrying the optrA gene demonstrated multidrug-resistance profiles. Genome-based relatedness classified the isolates into five clusters that were independent of the isolate sources. The most frequently known genotype among the isolates was the sequence type ST476 among E. faecalis (50% (5/10)). The study isolates revealed five novel sequence types. Antimicrobial resistance genes (ranging from 5 to 13) were found among all isolates that conferred resistance against 6 to 11 different classes of antimicrobials. Sixteen different virulence genes were found distributed across the optrA-carrying E. faecalis isolates. The virulence genes in E. faecalis included genes encoding invasion, cell adhesion, sex pheromones, aggregation, toxins production, the formation of biofilms, immunity, antiphagocytic activity, proteases, and the production of cytolysin. This study presented the first description and in-depth genomic characterization of the optrA-gene-carrying linezolid-resistant enterococci from retail broiler meat in the UAE and the Middle East. Our results call for further monitoring of the emergence of linezolid resistance at the retail and farm levels. These findings elaborate on the importance of adopting a One Health surveillance approach involving enterococci as a prospective bacterial indicator for antimicrobial resistance spread at the human–food interface

First Report of Colistin-Resistant <i>Escherichia coli</i> Carrying <i>mcr-1</i> IncI2(delta) and IncX4 Plasmids from Camels (<i>Camelus dromedarius</i>) in the Gulf Region.

Addressing the emergence of antimicrobial resistance (AMR) poses a significant challenge in veterinary and public health. In this study, we focused on determining the presence, phenotypic background, and genetic epidemiology of plasmid-mediated colistin resistance (mcr) in Escherichia coli bacteria isolated from camels farmed in the United Arab Emirates (UAE). Fecal samples were collected from 50 camels at a Dubai-based farm in the UAE and colistin-resistant Gram-negative bacilli were isolated using selective culture. Subsequently, a multiplex PCR targeting a range of mcr-genes, plasmid profiling, and whole-genome sequencing (WGS) were conducted. Eleven of fifty camel fecal samples (22%) yielded colonies positive for E. coli isolates carrying the mcr-1 gene on mobile genetic elements. No other mcr-gene variants and no chromosomally located colistin resistance genes were detected. Following plasmid profiling and WGS, nine E. coli isolates from eight camels were selected for in-depth analysis. E. coli sequence types (STs) identified included ST7, ST21, ST24, ST399, ST649, ST999, and STdaa2. Seven IncI2(delta) and two IncX4 plasmids were found to be associated with mcr-1 carriage in these isolates. These findings represent the first identification of mcr-1-carrying plasmids associated with camels in the Gulf region. The presence of mcr-1 in camels from this region was previously unreported and serves as a novel finding in the field of AMR surveillance