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Abstract Residues from the liquefaction of Black Thunder subbituminous and Illinois No. 6 bituminous coals in an autoclave and a bench unit were examined petrographically. Optical microscopy proved valuable for ranking the samples on the basis of overall coal conversion and presence of vitroplast, granular residue and inertinite. It was observed that in the autoclave that runs on Black Thunder coal, K 2 CO 3 was a superior water gas shift reaction catalyst to NaAlO 2 , or a combination of CS 2 and Fe or Mo catalysts. The amount of vitroplast showing vacuoles and cenospheric morphology in the residues was inversely related to the CO conversion, indicating that the mechanism of vitroplast dissolution is linked to the availability of active CO intermediates (e.g. formate ion, HCOO − ). A CO-steam mixture was more effective than syngas or pure H 2 and N 2 in increasing Black Thunder coal conversion, and resulted in greater morphological changes to the coal particles. In contrast, for Illinois No. 6 coal pure H 2 had a greater effect on coal solubilization and overall conversion than pure CO at the same temperature; this was attributed to the absence of carboxylates to react with the formate ions. Higher mesophase and coke contents were detected in some bench unit runs on Black Thunder coal that were operated in counterflow mode. Higher severity, poorer mixing, longer residence time and a reduction in pressure by almost 3.5 MPa are believed to be responsible for the retrogressive reactions forming mesospheres in these cases.

Urea is the most common nitrogen (N) fertilizer in agriculture, due to its cheaper price and high N content. Although the reciprocal influence between NO3- and NH4+ nutrition are well known, urea (U) interactions with these N-inorganic forms are poorly studied. Here, the responses of two tomato genotypes to ammonium nitrate (AN), U alone or in combination were investigated. Significant differences in root and shoot biomass between genotypes were observed. Under AN+U supply, Linosa showed higher biomass compared to UC82, exhibiting also higher values for many root architectural traits. Linosa showed higher Nitrogen Uptake (NUpE) and Utilization Efficiency (NUtE) compared to UC82, under AN+U nutrition. Interestingly, Linosa exhibited also a significantly higher DUR3 transcript abundance. These results underline the beneficial effect of AN+U nutrition, highlighting new molecular and physiological strategies for selecting crops that can be used for more sustainable agriculture. The data suggest that translocation and utilization (NUtE) might be a more important component of NUE than uptake (NUpE) in tomato. Genetic variation could be a source for useful NUE traits in tomato; further experiments are needed to dissect the NUtE components that confer a higher ability to utilize N in Linosa.

The author comments on the paper by J. Ma et al. (see ibid., vol.17, p.881-5, 2002), pointing out the practical aspects to be considered for actual conditions in the field.

CK2 is a highly conserved protein kinase involved in different cellular processes, which shows a higher activity in actively proliferating mammalian cells and in various types of cancer and cancer cell lines. We recently demonstrated that CK2 activity is strongly influenced by growth rate in yeast cells as well. Here, we extend our previous findings and show that, in cells grown in either glucose or ethanol-supplemented media, CK2 presents no alteration in K(m) for both the ATP and the peptide substrate RRRADDSDDDDD, while a significant increase in V (max) is observed. In chemostat-grown cells, no difference of CK2 activity was observed in cells grown at the same dilution rate in media supplemented with either ethanol or glucose, excluding the contribution of carbon metabolism on CK2 activity. By using the eIF2β-derived peptide, which can be phosphorylated by the holoenzyme but not by the free catalytic subunits, we show that the holoenzyme activity requires the concurrent presence of both β and β' encoding genes. Finally, conditions of nitrogen deprivation leading to a G0-like arrest result in a decrease of total CK2 activity, but have no effect on the activity of the holoenzyme. These findings newly indicate a regulatory role of β and β' subunits of CK2 in the nutrient response.

Energy management is an enabling technique to guarantee the reliability and economy of hybrid electric systems. This paper proposes a novel machine learning-based energy management strategy for a hybrid electric bus (HEB), with an emphasized consciousness of both thermal safety and degradation of the onboard lithium-ion battery (LIB) system. Firstly, the deep deterministic policy gradient (DDPG) algorithm is combined with an expert-assistance system, for the first time, to enhance the “cold start” performance and optimize the power allocation of HEB. Secondly, in the framework of the proposed algorithm, the penalties to over-temperature and LIB degradation are embedded to improve the management quality in terms of the thermal safety enforcement and overall driving cost reduction. The proposed strategy is tested under different road missions to validate its superiority over state-of-the-art techniques in terms of training efficiency and optimization performance.

This paper extends the analysis of the stability of electromagnetic transient simulation algorithms to non-linear systems with switching elements and non-linear inductor branches. A theoretical analysis based on common quadratic Lyapunov function (CQLF) theory is used to investigate the stability of numerical algorithms for the simulation of lumped strictly passive switched circuits (LSPSC). It is proved that only when certain fundamental physical properties, i.e., passivity and invariance of Lyapunov energy function are satisfied, does the widely used trapezoidal method result in stable simulations of such networks for any time-step size. This is different from the simulation of linear time invariant (LTI) systems where any real world stable system has a stable simulation if an A-stable integration method (e.g., trapezoidal rule) is used. Subsequently, it is shown that the problem of simulating a piecewise linear inductor can be equivalent to simulating a LSPSC; and ergo its simulation with the trapezoidal rule is also stable.

Abstract Recharging infrastructure (RI) deployment plays a vital role in improving the public recharging availability for transport electrification. Decarbonizing transportation using low-emission electricity requires massive RI network. Even though the consumers are reluctant to purchase electric vehicles (EVs) until RIs are sufficiently placed, the investors are not willing to invest in RIs due to recharging demand uncertainties. Therefore, a scientific planning framework is needed to ensure the sustainable deployment of EV-RIs in complex networks. In this study, a lifecycle thinking-based multi-period infrastructure-planning framework is proposed to develop sustainable public EV-RIs in an urban context. This framework consists of a temporal model to find the dynamic EV-RI demands, a stochastic model to obtain travel distances, and a multi-objective optimization model to select the best desirable capacities and locations for potential EV-RIs. A case study of a typical medium-scale municipality in Canada was assessed using the proposed framework and validated using conventional infrastructure planning scenarios. The geo-processing data, regional travel behaviors, and recharging characteristics were used as model inputs. The results of the case study showed that the proposed framework can be used to estimate multi-period public recharging demands, minimize lifecycle costs, maximize service coverage and infrastructure utilization, and ensure reasonable paybacks compared to conventional planning approaches. Moreover, this framework can be used to compare different investment assistances, which are required in the early stages of the RI deployment process to encourage investors. Furthermore, government and private institutions can use this framework to identify recharging demands, permitting, and developing RIs in the long-run.

Abstract The residential sector accounts for most of energy-consumption in developing countries in the form of traditional energy. The use of commercial energy is nominal and confined mostly to urban areas where fuelwood is already monetized. A model, based on an end-use/process analysis approach, is developed on a spreadsheet, which is capable of simulating scenarios to address issues of increasing traditional energy-demand caused by population growth, sustainable supply capacity of the existing energy resources, potential for development of new and renewable energy resources, technology. This paper is divided into two parts: general energy issues and the modelling approach, and the application of this approach to Nepal in the context of fuelwood-supply sustainability.

The Soutpansberg Transect investigates the abundance and diversity of ants and spiders along an altitudinal gradient in the Western Soutpansberg Mountains, South Africa. It has a north-south orientation over the mountain and is a long term project initiated in 2009. Data collection is carried out in intervals that suit the data logger capacity. To study the diversity patterns in ants and other invertebrate groups across the spatial transect over a long-term period and the climate the invertebrates.