7,700 research outputs found

    Cost effectiveness and sustainability of sanitation options: A case study of South Can Tho - Technical Report

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    The Institute for Sustainable Futures (ISF), from the University of Technology Sydney, in collaboration with Can Tho University (CTU) and Can Tho Water Supply and Sewerage Company (WSSC) completed a 2-year collaborative research project assessing the wastewater infrastructure options for Can Tho City. The comparison of alternatives was made on the basis of cost-effectiveness and on the relative sustainability of the options, as determined through a participatory stakeholder sustainability assessment process with several government agencies in Can Tho

    Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

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    Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

    Transport Jc in Bulk Superconductors: A Practical Approach?

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    The characterisation of the critical current density of bulk high temperature superconductors is typically performed using magnetometry, which involves numerous assumptions including, significantly, that Jc within the sample is uniform. Unfortunately, magnetometry is particularly challenging to apply where a local measurement of Jc across a feature, such as a grain boundary, is desired. Although transport measurements appear to be an attractive alternative to magnetization, it is extremely challenging to reduce the cross-sectional area of a bulk sample sufficiently to achieve a sufficiently low critical current that can be generated by a practical current source. In the work described here, we present a technique that enables transport measurements to be performed on sections of bulk superconductors. Metallographic techniques and resin reinforcement were used to create an I-shaped sample of bulk superconductor from a section of Gd-Ba-Cu-O containing 15 wt % Ag2O. The resulting superconducting track had a cross-sectional area of 0.44 mm2. The sample was found to support a critical current of 110 A using a field criterion in the narrowed track region of 1 μV cm-1. We conclude, therefore, that it is possible to measure critical current densities in excess of 2.5 x 108 A m-2 in sections of a bulk superconductor.This work was supported by the Engineering and Physical Sciences Research Council, via a Doctoral Training Award (grant number is EP/L504920/1) and funding from grant number EP/K02910X/1. This work was also supported by the Boeing Company. All data are provided in full in the results section of this paper.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/TASC.2016.253764

    Oxidative stress, mitochondrial perturbations and fetal programming of renal disease induced by maternal smoking

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    © 2015 Elsevier Ltd. An adverse in-utero environment is increasingly recognized to predispose to chronic disease in adulthood. Maternal smoking remains the most common modifiable adverse in-utero exposure leading to low birth weight, which is strongly associated with chronic kidney disease (CKD) in later life. In order to investigate underlying mechanisms for such susceptibility, female Balb/c mice were sham or cigarette smoke-exposed (SE) for 6 weeks before mating, throughout gestation and lactation. Offspring kidneys were examined for oxidative stress, expression of mitochondrial proteins, mitochondrial structure as well as renal functional parameters on postnatal day 1, day 20 (weaning) and week 13 (adult age). From birth throughout adulthood, SE offspring had increased renal levels of mitochondrial-derived reactive oxygen species (ROS), which left a footprint on DNA with increased 8-hydroxydeoxyguanosin (8-OHdG) in kidney tubular cells. Mitochondrial structural abnormalities were seen in SE kidneys at day 1 and week 13 along with a reduction in oxidative phosphorylation (OXPHOS) proteins and activity of mitochondrial antioxidant Manganese superoxide dismutase (MnSOD). Smoke exposure also resulted in increased mitochondrial DNA copy number (day 1-week 13) and lysosome density (day 1 and week 13). The appearance of mitochondrial defects preceded the onset of albuminuria at week 13. Thus, mitochondrial damage caused by maternal smoking may play an important role in development of CKD at adult life

    Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation

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    Unsupervised domain adaptation has caught appealing attentions as it facilitates the unlabeled target learning by borrowing existing well-established source domain knowledge. Recent practice on domain adaptation manages to extract effective features by incorporating the pseudo labels for the target domain to better solve cross-domain distribution divergences. However, existing approaches separate target label optimization and domain-invariant feature learning as different steps. To address that issue, we develop a novel Graph Adaptive Knowledge Transfer (GAKT) model to jointly optimize target labels and domain-free features in a unified framework. Specifically, semi-supervised knowledge adaptation and label propagation on target data are coupled to benefit each other, and hence the marginal and conditional disparities across different domains will be better alleviated. Experimental evaluation on two cross-domain visual datasets demonstrates the effectiveness of our designed approach on facilitating the unlabeled target task learning, compared to the state-of-the-art domain adaptation approaches
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