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Preconditioning brain cultures with moderate concentrations of ethanol (EtOH) or trans-resveratrol (RES), key red wine constituents, can prevent amyloid-β (Aβ) neurotoxicity. Past studies have indicated that moderate EtOH activates synaptic N-methyl-D-aspartate receptors (NMDAR) that, in part, signal via protein kinase C (PKC) to increase protective antioxidant proteins such as peroxiredoxin-2 (Prx2). RES preconditioning also is reported to involve NMDAR and PKC. However, although moderate, the EtOH and RES concentrations used have been noticeably above circulating levels from two glasses of wine, a daily intake linked to reduced risk of cognitive decline among older social drinkers. Given their mechanistic parallels, we speculated that subprotective EtOH and RES concentrations in a combinatorial preconditioning paradigm might elicit synergistic neuroprotection. To examine this notion, rat cerebellar cultures were pretreated with 10 mM EtOH (circulating concentration after ~ 2 drinks), 5 μM RES, EtOH + RES combinatorially, or media alone (controls). After 3 days, media were removed, and fresh media aliquots containing Aβ25-35 (25 μM) were added. Assessing apoptosis 24 h later with Hoescht 33342, neurodegeneration did not differ from controls in cultures separately preconditioned with 10 mM EtOH or 5 μM RES. However, apoptosis was prevented in combinatorially preconditioned cultures. Also, immunoblotting revealed elevated Prx2 levels due to combinatorial pretreatment that correlated with subsequent neuroprotection, whereas Prx2 was unchanged in separately pretreated cultures. Although the protective mechanisms require clarification, synergistically upregulated NMDAR-PKC-Prx2 (and other antioxidant proteins) is a reasonable component. These findings imply that EtOH + RES antioxidant synergy could be involved in neurobenefits attributed to low-moderate wine consumption.

Microcystis development in most temperate lakes shows an annual cycle that is mainly triggered by water temperature and includes four stages. This study aims to identify the optimum growth temperature and the temperature thresholds for recruitment and overwintering in Microcystis in Lake Taihu, based on field data and experiments at the cellular and genetic level on Microcystis under a simulated temperature condition. The field investigation showed that the cyanobacterial biomass began to increase at 11-15 °C in spring, reached a peak at 20-30 °C and remained at a low level after the water temperature declined below 6 °C. The simulation experiment found that the recovery of gene expression, photosynthesis and growth in Microcystis cells occurred at 11-14 °C and increased to an appreciable level after the temperature exceeded 20 °C. Microcystis cells stopped growing and maintained low photosynthetic activity and gene expression when the temperature declined to 10 °C or lower. These results suggest that Microcystis in Lake Taihu begin recruitment at 11-14 °C in spring and grow vigorously at 20-30 °C, then overwinter at 10 °C or lower in winter.

Abstract Methane is responsible for 20% of the global warming resulting from greenhouse gas emissions. Municipal solid waste (MSW) landfills are the third largest anthropogenic source of methane and are thus important to estimating the global methane budget and evaluating its contribution to global greenhouse gas emissions. Based on the greenhouse gas inventory guidelines from the Intergovernmental Panel on Climate Change (IPCC) and the first-order decay method used to estimate emissions from MSW landfills – and in line with MSW management in various regions – we calculated methane emissions from MSW landfills in various Chinese provinces from 2003 to 2013. During this period, methane emissions from MSW landfills increased from 1141.10 Gg to 1858.98 Gg, representing a mean annual increase of 71.79 Gg. MSW emissions tended to increase more in the northern and western provinces than in the southern and eastern provinces, as methane emissions strongly and positively correlated with population and socioeconomic demographics. MSW decontamination is growing rapidly in China, and landfills predominate in all MSW treatments; moreover, incineration has also dramatically increased in recent years.

This paper presents a new security-constrained multiobjective optimal dispatch (SC-MOOD) framework for an economic and reliable operation of microgrids. The framework is developed based on a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The new method considers grid steady-state and dynamic constraints while solving the optimal dispatch in both grid-connected and islanded modes. The constraints consist of power balance, voltage magnitude, line flows, power generation, frequency, and voltage transients. The proposed framework finds the most economic operating solutions to not only minimize the generation cost but also minimize the reliability cost. In this paper, the PaCcET is utilized to solve the SC-MOOD. The PaCcET uses an extraordinary transformation to first transfer all the points from a multiobjective space to a transformed objective space. It then solves a linear combination of transformed objectives using a single-objective optimizer to find all the nondominated points of the original multiobjective space. The performance of the new framework is verified using the simulation results in a microgrid with several distributed energy resources in both grid-connected and islanded modes. The results are then compared with two multiobjective optimization techniques, nondominated sorting genetic algorithm II and multiobjective particle swarm optimization, as two well-known benchmarks.

Abstract Lithium-ion batteries (LIBs) have driven the industry of rechargeable batteries in recent years due to their advantages such as high energy and power density and relatively long lifespan. Nevertheless, the dispose of spent LIBs has harmful impacts on the environment which needs to be addressed by recycling LIBs. However, none of the currently developed recycling processes is economical. The physical recycling process of LIBs may be economical if the cathode active materials can be separated, regenerated, and reused to make new LIBs. However, the first barrier for regeneration and reusing is the separation of different types of spent cathode active materials in the filter cake that are mixed with each other and come in the form of very fine powders with various sizes (< 30 μm) from the physical recycling process. The aim of this study is to separate the mixture of cathode active materials by adopting Stokes’ law. The focus will be only on mechanical separation with no thermal or chemical separation methods. For the validation, an experiment was designed and successfully performed where different types of spent cathode materials (e.g., LiCoO2, LiFePO4, and LiMn2O4) were separated from the spent anode materials (e.g., graphite) with high efficiency and reasonable time.

Abstract In this study, the influence of compressor speed, ejector motive nozzle needle position and evaporator inlet metering valve opening on the oil circulation rates (OCRs) of an R744 transcritical standard ejector cycle was experimentally investigated. Significantly higher OCR (∼10%) was observed at the evaporator inlet of the ejector cycle than that at the high pressure side (∼1%) measured in the same cycle under the same conditions. It has been observed that evaporator OCR was increased with increasing compressor speed. When the motive nozzle needle moved towards the nozzle throat, both compressor discharge flow rate and evaporator OCR were observed to be significantly lowered. As the evaporator inlet metering valve opening was adjusted, the compressor mass flow rate did not vary significantly while the evaporator mass flow rate decreased with decreasing metering valve opening. The evaporator OCR decreased from 6.5% to 2.2% as the metering valve opening varied from 86% to 27%. High evaporator OCR results in large evaporator pressure drop and low heat transfer coefficient. In addition to the standard ejector cycle, several alternative ejector cycles were theoretically analyzed to see if there is similar problem of high OCR in the evaporator. In ejector liquid recirculation cycle and multi-stage multi-ejector supermarket refrigeration cycle, similar high OCR problem in the evaporator may exist, while in two evaporator ejector cycle, evaporator OCR is equal to compressor OCR at steady state.

Abstract Thermal management system requires robust design as well as suitable paraffin/expanded graphite composites for confining the temperature of heat source within safe limits. However, paraffin/expanded graphite composites provide thermal management only for a certain period of time i.e. until the attainment of saturation energy storage limit. Herein, design, fabrication and simulation of a compact paraffin based thermal management system equipped with thermal bridge are presented. By keeping the highest safe temperature limit of batteries i.e. 65 °C and phase transition of paraffin as the test standards, performance of heat source was evaluated in terms of its total temperature retardation time along with quantitative effect of paraffin/expanded graphite composite. In the light of fundamental theories on mass and energy balance, substantial design steps and certain empirical equations have been introduced with further validation through experimental analysis. With heat dissipation rate of 6 W, it has been found that 75 g paraffin/expanded graphite composite with melting temperature of 54 °C kept the heat source temperature under the highest safe limit for around 13,000 s, providing the longest temperature retardation time in comparison to other types of paraffin/expanded graphite composites. Further, differential scanning calorimeter depicted that latent heat of 5 wt% paraffin/expanded graphite composite was slightly reduced from 182 J/g to 174 J/g even after 400 accelerated thermal cycles, demonstrating the promising thermal reliability and long life, which fits well with the set criterion of overall life expectancy of batteries. Besides, finite element analysis conducted via computational fluid dynamics software Fluent established qualitatively reliable fitness with experimental results.

Abstract This paper presents the application of the process of KDD (knowledge discovery in databases) for the forecasting of the electrical power demand of a supply fan of an AHU (air handling unit). The case study uses trend data from the BAS (Building Automation System), which is recorded every 15 min in an office building. Data mining techniques are used as a preprocessing step in the development of the forecasting model. A clustering analysis detects atypical operations and then partitions the whole dataset into three subsets of typical daily profiles of the supply fan modulation. A hybrid model, combining a closed-loop nonlinear ANN (autoregressive neural network) model and a physical model, forecasts the electric power demand over a horizon of up to 6 h. The optimum architecture of ANN, found by using a Simple Genetic Algorithm, is composed of 13 input neurons, 1 hidden neuron and 23-day training set size, for the cluster corresponding to working days except Mondays. The results show good agreement between the forecasts and measurements of fan modulation, and electric demand, respectively. The fan modulation was forecasted over the testing period with RMSE (Root Mean Squared Error) of 5.5% and CV(RMSE) of 17.6%. The fan electric demand was forecasted with a RMSE of 1.4 kW, CV(RMSE) of 30% over a 6-h time horizon. The sensitivity analysis indicated that the reduction of training data set size from 23 days to 4 or 8 days does not have a negative impact of the value of RMSE.