A Systematic Review of Methods for Investigating Climate Change Impacts on Water-Energy-Food Nexus

This is the final version. Available on open access from Springer via the DOI in this recordData Availability: The data sources are listed in the ‘Selected articles’ in References, some articles are not cited in the manuscript but are selected for review (Carvajal et al. 2017; Solaun and Cerda 2017; Yin et al. 2017; Bieber et al. 2018; Gaudard et al. 2018; Hasan and Wyseure 2018; Gohar et al. 2019; Ortiz-Bobea 2019; Rigden et al. 2020; Beltran-Peña and D’Odorico 2022; Kumar et al. 2023).Water, energy and food are important for human survival and sustainable development. With climate change, investigating climate change impacts on Water-Energy-Food nexus has been a topic of growing interest in recent years. However, there is a lack of a systematic review of the current state and methodologies of Water-Energy-Food nexus studies under climate change. Here, we review research articles investigating climate change impacts on Water-Food, Water-Energy and Water-Energy-Food nexus over last seven years. The existing methods and tools, spatial scales, and future climate scenarios setting in these articles are summarised and analysed. We found that the analyses methods could be divided into four categories (physics-based modelling, statistical methods, supervised learning and operation optimisation), among them, physics-based modelling accounts for the largest proportion. The reviewed studies cover a range of scales from site scale to global, with most studies focusing on the regional scale. Models used for small to middle scale are mainly related to hydrology and water resource, while large-scale modelling is based on interdisciplinary models. Future climate scenarios setting include emission scenarios and global warming scenarios based on Global Climate Models (GCMs). A number of future research challenges have been identified. These include spatial scale and resolution, internal physical mechanism, application of novel artificial intelligence models, extreme climate events, potential competition in nexus systems as well as data and model uncertainty.China Scholarship Counci

Modelling for the Identification of Mechanisms Driving Cholera Outbreaks in Endemic Regions

This is the author accepted manuscript.Engineering and Physical Sciences Research Council (EPSRC

Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions

Preparation of high-quality datasets for the urban scene understanding is a labor-intensive task, especially, for datasets designed for the autonomous driving applications. The application of the coarse ground truth (GT) annotations of these datasets without detriment to the accuracy of semantic image segmentation (by the mean intersection over union - mIoU) could simplify and speedup the dataset preparation and model fine tuning before its practical application. Here the results of the comparative analysis for semantic segmentation accuracy obtained by PSPNet deep learning architecture are presented for fine and coarse annotated images from Cityscapes dataset. Two scenarios were investigated: scenario 1 - the fine GT images for training and prediction, and scenario 2 - the fine GT images for training and the coarse GT images for prediction. The obtained results demonstrated that for the most important classes the mean accuracy values of semantic image segmentation for coarse GT annotations are higher than for the fine GT ones, and the standard deviation values are vice versa. It means that for some applications some unimportant classes can be excluded and the model can be tuned further for some classes and specific regions on the coarse GT dataset without loss of the accuracy even. Moreover, this opens the perspectives to use deep neural networks for the preparation of such coarse GT datasets.Comment: 10 pages, 6 figures, 2 tables, The Second International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2019) 26-27 January 2019, Kiev, Ukrain

Validation of a 2D flow model using high-resolution experimental data sets for sub/surface flow interactions

This is the final versionFlood risk in urban environments has undoubtedly increased over the past decade due to accelerated urbanisation and land use changes and more frequent extreme rainfall, induced by climate change, have exacerbated this convoluted issue. Effective contemporary urban flood risk analysis requires detailed computational modelling techniques which, to date, have been widely adopted to investigate behaviours of urban floods and their impacts (e.g. microbial risk assessments, flood risk zoning, property damage, in order to develop countermeasures in flood mitigation decision making [6]). Two systems are always considered for modelling purposes: the minor system refers to subterranean pipes and manholes and the major system represents flow pathways over a surface (e.g., street). The minor system is often simulated via one-dimensional (1D) sewer network models, while the major system can be modelled via either 1D channel networks or two-dimensional (2D) overland flow models. The interactions between subsurface and surface systems are analysed via 1D-1D or 1D-2D modelling approaches, where the coefficients for linking the two models require careful calibration to accurately reflect the flow dynamics between them. In this study, experimental datasets collected within a facility that replicates urban flooding scenarios are used to calibrate a 1D sewer and 2D overflow hydraulic model such that it can increase its accuracy and therefore be applied with more confidence to analyse a wider range of flooding conditionsEngineering and Physical Sciences Research Council (EPSRC

Investigation of uniform and graded sediment wash-off in an urban drainage system: Numerical model validation from a rainfall simulator in an experimental facility

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data will be made available on request.Understanding sediment wash-off in urban environments plays an essential role in sediment transport management; and is critical for accurate pluvial flood control to assist in adaptation and mitigation strategies. Sediment transport models have been researched previously, though challenges still arise due to the complicated nature of graded sediment transport. This study tested the accuracy of the van Rijn model using a sparse distribution of particle sizes using the geometric mean. As such, this study used high-resolution datasets collected in a water laboratory to investigate sediment wash-off and transport on an urban street. This included the interaction of two gully pots receiving sediment loads that were washed off from a hypothetical urban surface by three rainfall intensities. The results showed that the model was able to simulate uniform sediments entering the gully pots accurately when the sediment size was assigned to a median diameter. Using the grain diameter to represent the geometric mean can improve the model performance for simulating a graded sediment.Engineering and Physical Sciences Research Council (EPSRC)Spanish Ministry of Science, Innovation and Universitie

Association between Helicobacter pylori genotypes and severity of chronic gastritis, peptic ulcer disease and gastric mucosal interleukin-8 levels: evidence from a study in the Middle East

Background: The varied clinical presentations of Helicobacter pylori (H. pylori) infection are most likely due to differences in the virulence of individual strains, which determines its ability to induce production of interleukin-8 (IL-8) in the gastric mucosa. The aim of this study was to examine association between cagA, vacA-s1 and vacA-s2 genotypes of H. pylori and severity of chronic gastritis and presence of peptic ulcer disease (PUD), and to correlate these with IL-8 levels in the gastric mucosa. Methods: Gastric mucosal biopsies were obtained from patients during esophagogastroduodenoscopy. The severity of chronic gastritis was documented using the updated Sydney system. H. pylori cagA and vacA genotypes were detected by PCR. The IL-8 levels in the gastric mucosa were measured by ELISA. Results: H. pylori cagA and/or vacA genotypes were detected in 99 patients (mean age 38.4±12.9; 72 males), of whom 52.5% were positive for cagA, 44.4% for vacA-s1 and 39.4% for vacA-s2; and 70.7% patients had PUD. The severity of inflammation in gastric mucosa was increased with vacA-s1 (p=0.017) and decreased with vacA-s2 (p=0.025), while cagA had no association. The degree of neutrophil activity was not associated with either cagA or vacA-s1, while vacA-s2 was significantly associated with decreased neutrophil activity (p=0.027). PUD was significantly increased in patients with cagA (p=0.002) and vacA-s1 (p=0.031), and decreased in those with vacA-s2 (p=0.011). The level of IL-8 was significantly increased in patients with cagA (p=0.011) and vacA-s1 (p=0.024), and lower with vacA-s2 (p=0.004). Higher levels of IL-8 were also found in patients with a more severe chronic inflammation (p=0.001), neutrophil activity (p=0.007) and those with PUD (p=0.001). Conclusions: Presence of vacA-s1 genotype of H. pylori is associated with more severe chronic inflammation and higher levels of IL-8 in the gastric mucosa, as well as higher frequency of PUD. Patients with vacA-s2 have less severe gastritis, lower levels of IL-8, and lower rates of PUD. The presence of cagA genotype is not associated with the severity of gastritis or IL-8 induction in the gastric mucosa. The association of cagA with PUD may be a reflection of its presence with vacA-s1 genotype

Bcl-2 protein family: Implications in vascular apoptosis and atherosclerosis

Apoptosis has been recognized as a central component in the pathogenesis of atherosclerosis, in addition to the other human pathologies such as cancer and diabetes. The pathophysiology of atherosclerosis is complex, involving both apoptosis and proliferation at different phases of its progression. Oxidative modification of lipids and inflammation differentially regulate the apoptotic and proliferative responses of vascular cells during progression of the atherosclerotic lesion. Bcl-2 proteins act as the major regulators of extrinsic and intrinsic apoptosis signalling pathways and more recently it has become evident that they mediate the apoptotic response of vascular cells in response to oxidation and inflammation either in a provocative or an inhibitory mode of action. Here we address Bcl-2 proteins as major therapeutic targets for the treatment of atherosclerosis and underscore the need for the novel preventive and therapeutic interventions against atherosclerosis, which should be designed in the light of molecular mechanisms regulating apoptosis of vascular cells in atherosclerotic lesions

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz