Estimate of undergraduate university student alcohol use in China: a systematic review and meta-analysis

Objective: To develop an estimate of self-reported last 30 day alcohol use by university students in China. Methods: A search of papers published in English and Chinese between 2006 and 2015, following pre-established selection criteria, identified 30 papers that were included in this meta-analysis. Nine moderator variables were preselected for this analysis. Results: A total of 749 papers were identified in the keyword search, and 30 studies (28 in Chinese, 2 in English) met all selection criteria and were included in the meta-analysis. The self-reported last-30-day alcohol use for undergraduate university students was 66.8% for males and 31.7% for females. Meta-regression identified three moderators associated with the different drinking rates reported: the definition of drinking, the origin of the questionnaire used in the survey, and the geographic region where the survey was conducted. These three moderators explained 56% of the heterogeneity of reported drinking rates for the male students and 47% of the heterogeneity of reported drinking rates for the female students. Conclusions: The results of this meta-analysis provide an estimate of last 30 day alcohol use by university students (age 18–23) and increase our understanding of drinking by young people in China. The meta-analysis suggested three variables that could have affected the results and which are worthy of further study. The discussion places these results in the context of Chinese drinking culture and university life

Integrated Platform for Whole Building HVAC System Automation and Simulation

Integrated optimal control strategies can reduce the overall building HVAC system energy consumption as well as improved air quality resulting in improved health and cognitive function for the occupants. However, it is time consuming to quantitatively evaluate the design-intended building HVAC automation system performance before on-site deployment, because: 1) the building and HVAC system design specs are in 2D or 3D drawings that require significant efforts to develop the system steady state or dynamic models based on them; 2) the building HVAC control strategies are designed and implemented in building automation (BA) system that could not smoothly connect with the building HVAC system steady state or dynamic models for performance evaluation through close-loop simulation. This paper presents the tool chain of an integrated simulation platform for building HVAC system automation and simulation as well as its implementation in a real case. First, building information from a Revit BIM model is automatically parsed to an EnergyPlus building energy model. Second, the HVAC system model is quickly populated with a scalable HVAC system library in Dymola. Third, the HVAC controls are developed in WebCTRL, a building HVAC automation system by Automated Logic Corporation (ALC). Finally, both the building energy model and HVAC system model are wrapped up as Functional Mock-up Units (FMU) and connected with embedded simulator in WebCTRL to perform close-loop building automation system performance simulation. A real case study, a chiller plant system in a hotel building, is conducted to verify the scalability and benefit of the developed tool chain. The case study demonstrates the values in identifying both HVAC automation system design-intended control issues and improvement areas for integrated optimal controls. This platform enables testing of building HVAC control strategies before on-site deployment, which reduces the labor and time required for building HVAC control development-to-market process and ensure the delivering quality. Furthermore, this platform can be calibrated with metered real-time data from the specific building HVAC system and serve as its “digital twin” that empowers the system fault detection, diagnostics and predictive maintenance

Tertiary Regulation of Cascaded Run-of-the-River Hydropower in the Islanded Renewable Power System Considering Multi-Timescale Dynamics

To enable power supply in rural areas and to exploit clean energy, fully renewable power systems consisting of cascaded run-of-the-river hydropower and volatile energies such as pv and wind are built around the world. In islanded operation mode, the primary and secondary frequency control, i.e., hydro governors and automatic generation control (AGC), ensure the frequency stability. However, due to limited water storage capacity of run-of-the-river hydropower and river dynamics constraints, without coordination between the cascaded plants, the traditional AGC with fixed participation factors cannot fully exploit the adjustability of cascaded hydropower. When imbalances between the volatile energy and load occur, load shedding can be inevitable. To address this issue, this paper proposes a coordinated tertiary control approach by jointly considering power system dynamics and the river dynamics that couples the cascaded hydropower plants. The timescales of the power system and river dynamics are very different. To unify the multi-timescale dynamics to establish a model predictive controller that coordinates the cascaded plants, the relation between AGC parameters and turbine discharge over a time interval is approximated by a data-based second-order polynomial surrogate model. The cascaded plants are coordinated by optimising AGC participation factors in a receding-horizon manner, and load shedding is minimised. Simulation of a real-life system shows a significant improvement in the proposed method in terms of reducing load shedding.Comment: Submitted to IET Renewable Power Generation; 11 page

Tracking dynamics of plant biomass composting by changes in substrate structure, microbial community, and enzyme activity

<p>Abstract</p> <p>Background</p> <p>Understanding the dynamics of the microbial communities that, along with their secreted enzymes, are involved in the natural process of biomass composting may hold the key to breaking the major bottleneck in biomass-to-biofuels conversion technology, which is the still-costly deconstruction of polymeric biomass carbohydrates to fermentable sugars.</p> <p>However, the complexity of both the structure of plant biomass and its counterpart microbial degradation communities makes it difficult to investigate the composting process.</p> <p>Results</p> <p>In this study, a composter was set up with a mix of yellow poplar (<it>Liriodendron tulipifera</it>) wood-chips and mown lawn grass clippings (85:15 in dry-weight) and used as a model system. The microbial rDNA abundance data obtained from analyzing weekly-withdrawn composted samples suggested population-shifts from bacteria-dominated to fungus-dominated communities. Further analyses by an array of optical microscopic, transcriptional and enzyme-activity techniques yielded correlated results, suggesting that such population shifts occurred along with early removal of hemicellulose followed by attack on the consequently uncovered cellulose as the composting progressed.</p> <p>Conclusion</p> <p>The observed shifts in dominance by representative microbial groups, along with the observed different patterns in the gene expression and enzymatic activities between cellulases, hemicellulases, and ligninases during the composting process, provide new perspectives for biomass-derived biotechnology such as consolidated bioprocessing (CBP) and solid-state fermentation for the production of cellulolytic enzymes and biofuels.</p