771 research outputs found

    Optimal maintenance planning for sustainable energy efficiency lighting retrofit projects by a control system approach

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    The energy savings achieved by implementing energy efficiency (EE) lighting retrofit projects are sometimes not sustainable and vanish rapidly given that lamp population decays as time goes by if without proper maintenance activities. Scope of maintenance activities refers to replacements of failed lamps due to nonrepairable lamp burnouts. Full replacements of all the failed lamps during each maintenance interval contribute to a tight project budget due to the expense for the lamp failure inspections, as well as the procurement and installation of new lamps. Since neither “no maintenance” nor “full maintenance” is preferable to the EE lighting project developers (PDs), we propose to design an optimal maintenance plan that optimises the number of replacements of the failed lamps, such that the EE lighting project achieves sustainable performance in terms of energy savings whereas the PDs obtain their maximum benefits in the sense of cost–benefit ratio. This optimal maintenance planning (OMP) problem is aptly formulated as an optimal control problem under control system framework, and solved by a model predictive control (MPC) approach. An optimal maintenance plan for an EE lighting retrofit project is designed as a case study to illustrate the effectiveness of the proposed control system approach.A preliminary version of this paper has been presented in the 19th World Congress of the International Federation of Automatic Control, Cape Town, South Africa, 24–29 August 2014.http://www.elsevier.com/locate/conengprachj201

    Identifying the physical origin of gamma-ray bursts with supervised machine learning

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    The empirical classification of gamma-ray bursts (GRBs) into long and short GRBs based on their durations is already firmly established. This empirical classification is generally linked to the physical classification of GRBs originating from compact binary mergers and GRBs originating from massive star collapses, or Type I and II GRBs, with the majority of short GRBs belonging to Type I and the majority of long GRBs belonging to Type II. However, there is a significant overlap in the duration distributions of long and short GRBs. Furthermore, some intermingled GRBs, i.e., short-duration Type II and long-duration Type I GRBs, have been reported. A multi-parameter classification scheme of GRBs is evidently needed. In this paper, we seek to build such a classification scheme with supervised machine learning methods, chiefly XGBoost. We utilize the GRB Big Table and Greiner's GRB catalog and divide the input features into three subgroups: prompt emission, afterglow, and host galaxy. We find that the prompt emission subgroup performs the best in distinguishing between Type I and II GRBs. We also find the most important distinguishing feature in prompt emission to be T_{90}, hardness ratio, and fluence. After building the machine learning model, we apply it to the currently unclassified GRBs to predict their probabilities of being either GRB class, and we assign the most probable class of each GRB to be its possible physical class.Comment: 23 pages, 8 tables, 11 figures, accepted for publication by ApJ. Full version of Table 5 is available as ancillary materia

    The genome evolution and domestication of tropical fruit mango

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    Background: Mango is one of the world’s most important tropical fruits. It belongs to the family Anacardiaceae, which includes several other economically important species, notably cashew, sumac and pistachio from other genera. Many species in this family produce family-specific urushiols and related phenols, which can induce contact dermatitis. Results: We generate a chromosome-scale genome assembly of mango, providing a reference genome for the Anacardiaceae family. Our results indicate the occurrence of a recent whole-genome duplication (WGD) event in mango. Duplicated genes preferentially retained include photosynthetic, photorespiration, and lipid metabolic genes that may have provided adaptive advantages to sharp historical decreases in atmospheric carbon dioxide and global temperatures. A notable example of an extended gene family is the chalcone synthase (CHS) family of genes, and particular genes in this family show universally higher expression in peels than in flesh, likely for the biosynthesis of urushiols and related phenols. Genome resequencing reveals two distinct groups of mango varieties, with commercial varieties clustered with India germplasms and demonstrating allelic admixture, and indigenous varieties from Southeast Asia in the second group. Landraces indigenous in China formed distinct clades, and some showed admixture in genomes. Conclusions: Analysis of chromosome-scale mango genome sequences reveals photosynthesis and lipid metabolism are preferentially retained after a recent WGD event, and expansion of CHS genes is likely associated with urushiol biosynthesis in mango. Genome resequencing clarifies two groups of mango varieties, discovers allelic admixture in commercial varieties, and shows distinct genetic background of landraces

    Effects of caesarean section on maternal health in low risk nulliparous women: a prospective matched cohort study in Shanghai, China

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    <p>Abstract</p> <p>Background</p> <p>Rates of caesarean section are progressively increasing in many parts of the world. As a result of psychosocial factors there has been an increasing tendency for pregnant women without justifiable medical indications for caesarean section to ask for this procedure in China. A critical examination of this issue in relation to maternal outcomes is important. At present there are no clinical trials to help assess the risks and benefits of caesarean section in low risk women. To fill the gap left by trials, this indication-matched cohort study was carried out to examine prospectively the outcomes of caesarean section on women with no absolute obstetric indication compared with similar women who had vaginal delivery.</p> <p>Methods</p> <p>An indication-matched cohort study was undertaken to compare maternal outcomes following caesarean section with those undergoing vaginal delivery, in which the two groups were matched for non-absolute indications. 301 nulliparous women with caesarean section were matched successfully with 301 women who delivered vaginally in the Maternal and Children's Hospitals (MCHs) in Shanghai, China. Logistic regression model or binomial regression model was used to estimate the relative risk (RR) directly. Adjusted RRs were calculated adjusting for propensity score and medical indications.</p> <p>Results</p> <p>The incidence of total complications was 2.2 times higher in the caesarean section group during hospitalization post-partum, compared with the vaginal delivery group (RR = 2.2; 95% CI: 1.1-4.4). The risk of haemorrhage from the start of labour until 2 hours post-partum was significantly higher in the caesarean group (RR = 5.6; 95% CI: 1.2-26.9). The risk of chronic abdominal pain was significantly higher for the caesarean section group (RR = 3.6; 95% CI: 1.2-10.9) than for the vaginal delivery group within 12 months post-partum. The two groups had similar incidences of anaemia and complicating infections such as wound complications or urinary tract infection.</p> <p>Conclusions</p> <p>In nulliparous women who were at low risk, caesarean section was associated with a higher rate of post-partum morbidity. Those requesting the surgical procedure with no conventional medical indication, should be advised of the potential risks.</p

    Pb(II)-inducible proviolacein biosynthesis enables a dual-color biosensor toward environmental lead

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    With the rapid development of synthetic biology, various whole-cell biosensors have been designed as valuable biological devices for the selective and sensitive detection of toxic heavy metals in environmental water. However, most proposed biosensors are based on fluorescent and bioluminescent signals invisible to the naked eye. The development of visible pigment-based biosensors can address this issue. The pbr operon from Klebsiella pneumoniae is selectively induced by bioavailable Pb(II). In the present study, the proviolacein biosynthetic gene cluster was transcriptionally fused to the pbr Pb(II) responsive element and introduced into Escherichia coli. The resultant biosensor responded to Pb(II) in a time- and dose-dependent manner. After a 5-h incubation with Pb(II), the brown pigment was produced, which could be extracted into n-butanol. Extra hydrogen peroxide treatment during n-butanol extract resulted in the generation of a stable green pigment. An increased brown signal was observed upon exposure to lead concentrations above 2.93 nM, and a linear regression was fitted from 2.93 to 3,000 nM. Extra oxidation significantly decreased the difference between parallel groups. The green signal responded to as low as 0.183 nM Pb(II), and a non-linear regression was fitted in a wide concentration range from 0.183 to 3,000 nM. The specific response toward Pb(II) was not interfered with by various metals except for Cd(II) and Hg(II). The PV-based biosensor was validated in monitoring bioaccessible Pb(II) spiked into environmental water. The complex matrices did not influence the regression relationship between spiked Pb(II) and the dual-color signals. Direct reading with the naked eye and colorimetric quantification enable the PV-based biosensor to be a dual-color and low-cost bioindicator for pollutant heavy metal
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