Typical challenges that managers of remanufacturing face are composed of the lack of timely, accurate, and consistent information of remanufacturing resources. Therefore, it is difficult to implement real-time production scheduling for the shop floor. To address this problem, the authors applied the concept of the 'Internet of Things' to the remanufacturing of automobile engines to form an Internet of Manufacturing Things environment. Under the Internet of Manufacturing Things, an identification technology for disassembled engine parts was designed, and the real-time status of the remanufacturable resources can be monitored. Based on the captured remanufacturing information, a real-time production scheduling method was developed, and a mathematical model was developed to achieve cost reduction, dynamic management of remanufacturable resources, and energy consumption decrease. To obtain an optimal solution, a Pareto-based optimization method was used. Finally, a case study was performed to analyze the effectivity of the proposed method. The results showed that the remanufacturing cost and energy consumption were reduced by 34% and 34% respectively, and the worker load rate was more balanced. These improvements can contribute to more sustainable development and greener production within the remanufacturing industry, especially for remanufacturing of automobile engines. (C) 2018 Elsevier Ltd. All rights reserved.

Energy-intensive industries account for almost 51% of energy consumption in China. A continuous improvement in energy efficiency is important for energy-intensive industries. Cleaner production has proven itself as an effective way to improve energy efficiency and reduce energy consumption. However, there is a lack of manufacturing data due to the difficult implementation of sensors in harsh production environment, such as high temperature, high pressure, high acid, high alkali, and smoky environment which hinders the implementation of the cleaner production strategy. Thanks to the rapid development of the Internet of Things, many data can be sensed and collected in the manufacturing processes. In this paper, a big data driven analytical framework is proposed to reduce the energy consumption and emission for energy-intensive manufacturing industries. Then, two key technologies of the proposed framework, namely energy big data acquisition and energy big data mining, are utilized to implement energy big data analytics. Finally, an application scenario of ball mills in a pulp workshop of a partner company is presented to demonstrate the proposed framework. The results show that the energy consumption and energy costs are reduced by 3% and 4% respectively. These improvements can promote the implementation of cleaner production strategy and contribute to the sustainable development of energy intensive manufacturing industries. (C) 2018 Elsevier Ltd. All rights reserved.

Increased amount of nano-silver will be released into domestic and industrial waste streams due to its extensive application. However, great controversy still exists on the effects of silver nanoparticle (AgNP) on biological wastewater treatment processes and a toxicology model has not been built yet. Four sequencing batch reactors with activated sludge has been run for over three months with different silver species at a concentration of 1 mg Ag/L in. influent. Both freshly prepared Ag-NPs and aged Ag-NPs were tested with released silver ion as control. Results in this study showed that Ag-NPs, especially freshly prepared Ag-NPs, can help to maintain or even increase the diversity of microbial community in activated sludge and the biomass concentration even under long-term treatment. It indicates that the hormesis model need to be considered for the toxicology of Ag-NPs. (C) 2017 Elsevier B.V. All rights reserved.

Objectives: Sleep duration is associated with adiposity in adults. Abdominal adiposity specifically is strongly correlated with metabolic alterations, however, the relationships between abdominal adiposity and sleep quality are incompletely understood. The purpose of this study is to test the hypothesis that abdominal adiposity is related to poor sleep quality while total adiposity is not; and to explore whether pathways, including immune system and hypothalamic-pituitary-adrenal axis, link abdominal adiposity to poor sleep quality. Methods: Subjects were 101 men and women aged 38.88 +/- 11.96 years with body mass index between 29.35 +/- 6.93 kg/m(2). Subjective sleep quality was determined by the Pittsburgh Sleep Questionnaire Index (PSQI). Body composition was determined by dual energy X-ray absorptiometry. Saliva and blood samples were collected for assessment of cortisol and markers of inflammation. In a cross-sectional study design, correlation analysis was conducted to determine the relationships between poor sleep quality and adiposity. Participants were stratified based on PSQI score to evaluate differences in main outcomes between subjects with normal (NSQ; PSQI <= 5) vs poor sleep quality (PSQ; PSQI > 5). Results: Poor sleep quality was related to greater visceral fat (r = 0.26; p < 0.05), but not total fat. The PSQ group had greater visceral fat compared to the NSQ group (1.11 +/- 0.83 kg vs 0.79 +/- 0.62 kg; p < 0.05), however, there was no difference in total fat mass (33.18 +/- 14.21 kg vs 29.39 +/- 13.03 kg; p = 0.24). The PSQ group had significantly greater leptin (1.37 +/- 0.07 ng/ml vs 1.08 +/- 0.08 ng/ml; p < 0.05), but hypothalamic pituitary-adrenal axis activity did not differ between the PSQ and NSQ groups. Conclusions: Poor sleep quality is associated with greater visceral adiposity and leptin secretion. Further research is needed to probe potential cause and effect relationships among visceral adipose tissue, leptin, and sleep quality.

A novel 10-membered macrolactone, hypoxylide (1), was isolated from the endophytic fungus Annulohypoxylon sp. that was obtained from the Mangrove plant Rhizophora racemosa. The structure and absolute configuration of 1 were unambiguously elucidated by comprehensive 1D and 2D NMR, as well as by HRESIMS and ECD spectroscopic analyses. Hypoxylide (1) features an unprecedented polyketide skeleton comprised of a trihydroxynaphthalene-dione moiety fused to a decalactone ring. A plausible biosynthetic pathway of this novel metabolite is proposed. (C) 2018 Elsevier Ltd. All rights reserved.

This paper is concerned with an initial boundary value problem of the incompressible nematic liquid crystal flows with density-dependent viscosity in a smooth bounded domain Omega subset of R-3. The global well-posedness of strong solutions with large oscillations is established in vacuum, provided parallel to del u(0)parallel to(L2) + parallel to del d(0)parallel to(L2) suitably small with arbitrary large initial density, which extended the local strong solution by Gao et al. [12] to be a global one. (C) 2018 Elsevier Inc. All rights reserved.