• Energy Research
• Closed Access close
• US close
• GB close
• IT close
• ES close

Low-salinity water injection emerges to be a cost-effective and environmentally friendly enhanced oil recovery technique. Furthermore, additives, such as the surfactant and nanoparticles in combina...

Abstract This paper aims to present a feasibility study of the innovative plant for methanol synthesis from carbon dioxide-sequestered by fossil fuel power plant and hydrogen, which is produced by water electrolyzer employing the over-production on the electrical grid. The thermo-economic analysis is performed in the framework of the MefCO2 H2020 EU project and it is referred to the German economic scenario, properly taking into account the real market costs and cost functions for different components of the plant. Three different plant capacities for methanol production (4000 10,000 and 50,000 ton/year) have been investigated, assuming an average cost for electrical energy to feed electrolysers and analyzing the influence of the most significant parameters (oxygen selling option, methanol selling price and electrolysers’ capital cost) on the profitability of the plant. The analysis has been performed in W-ECoMP, software for the thermo-economic analysis and plant optimization developed by the University of Genoa.

Plants exhibit plasticity in response to their current environment and, in some cases, to that of the previous generation (i.e. maternal effects). However, few studies have evaluated both within- and between-generation plasticities and the extent to which they interact to influence fitness, especially in natural environments. The plasticity of adult traits to two generations of natural differences in light was determined for Campanulastrum americanum, a forest-edge herb that expresses annual and biennial life histories. Plasticity was found to an individual's light environment (within generation) and the maternal light environment (between generations). Responses to ambient light for size traits and timing of flowering were probably passive, whereas apparently adaptive responses were found for light acquisition traits. Maternal light influenced the expression of most adult traits but had the strongest effect when plants were germinated in natural environments. The transgenerational effects of light were consistent with adaptive plasticity for several traits. Plastic within-generation changes in flowering time may also result in adaptive between-generation effects by altering the offspring life history schedule. Finally, the results underscore the importance of conducting studies of within- and between-generation plasticity in natural populations, where the environmental context is relevant to that in which the traits evolved.

Abstract In recent years living walls have increasingly spread, thus becoming a diffuse architectural envelope cladding technology. Consequently, a more precise understanding of their thermal behavior and impact on the building energy balance are needed. One of the most important effects provided by the use of living walls is the shading of the building envelope, with clear benefits during the cooling period. Furthermore, many features characterize the thermal behavior of living walls, namely plant species, leaf area index (LAI), evapotranspiration, emissivity and air cavity type. All these particular characteristics have been accounted in the mathematical model developed in the frame of the presented research, whose aim is to provide a tool for the prediction of the thermal behavior of living walls. Two kinds of living walls, one with grass and closed air cavity and the other one with vertical garden and open air cavity were considered. The results achieved by means of the developed model show a good agreement with the measurements also supported by model efficiency indexes such as Nash–Sutcliffe efficiency index (NSEC). Values of around 0.7 were obtained for the NSEC index for both the investigated living walls.

The effect of low concentrations of ethanol on Na+,K(+)-ATPase activity, defined as ouabain-inhibitable 86Rb+ (K+) uptake, was investigated in a crude synaptosome preparation which was subject to minimal subcellular fractionation procedures. Moderate (20-30%) but potent (EC50 = 3.8 mM) stimulation of total ouabain (1 mM)-inhibitable K+ uptake by ethanol was observed following incubation periods of up to 20 min. The activity of the ethanol-induced component of K+ uptake was antagonized by nanomolar concentrations of ouabain. Thus, the moderate stimulation of total ouabain-inhibitable K+ uptake by ethanol was attributable to the activation of a component of K+ uptake which was very sensitive (VS; IC50 = 2.8 x 10(-10) M) to inhibition by ouabain. Slightly higher concentrations of ouabain (10(-9) - 10(-6.6) M) stimulated K+ uptake above control (no ethanol or ouabain) in both the absence and presence of ethanol. The selectivity of the VS-ethanol interaction was demonstrated by the lack of any ethanol effect on two other components of ouabain-inhibitable K+ uptake which accounted for inhibition of K+ uptake by concentrations of ouabain above 10(-6.6) M and were defined as sensitive (S; IC50 = 10(-6) M) and insensitive (I; IC50 = 10(-4) M) to ouabain. These results define the ethanol-inducible component of ouabain-inhibitable Na+,K(+)-ATPase activity and promote the view that changes in Na+,K(+)-ATPase-dependent ion translocation may contribute to ethanol intoxication in vivo.

AbstractThe brief exposure of recently ovulated mouse oocytes to a dilute solution of ethanol in vitro for 1, 3, or 5 min induced a uniform high incidence of parthenogenetic activation. The majority of parthenogenones developed a single haploid pronucleus after the extrusion of a second polar body. The proportionate incidence of this parthenogenetic class was significantly reduced as the duration of ethanol exposure increased from 1 min to 5 min. There was a concomitant increase in the incidence of parthenogenones that developed two haploid pronuclei following failure of extrusion of the second polar body. Cytogenetic analysis of the ethanol‐induced single‐pronuclear haploid parthenogenones at metaphase of the first cleavage division clearly demonstrated that a significant proportion were aneuploid. The incidence of aneuploidy observed was directly related to the duration of ethanol exposure. G‐band analysis of the aneuploid metaphases revealed that the chromosomes were not randomly involved in the malsegregation events. This observation may be a reflection of the relationship of particular chromosomes to the meiotic spindle apparatus rather than on any specific property of the agent to which they were exposed. It is believed that ethanol disrupts the organisation of cytoskeletal elements and, in particular, interferes with the processes of chromosome segregation at the second meiotic division.

Abstract Conventional spouted beds have been extensively used in many real-life applications but are not suited for all types of materials, especially fine particles, which require internal devices to improve their motion in the spouted bed. However, unlike conventional spouted beds, there are almost no mechanistic or empirical models available for the design of spouted beds with internals. Given the availability of an extensive but not experimentally designed database, the main purpose of this study is to present an analysis of neural networks and empirical models in terms of their suitability to fit and predict average cycle times in conical spouted beds with and without draft tubes. The parameters investigated are particle size, density, contactor angle, gas inlet diameter, static bed height, and draft tube features. Although the amount of information is always a key factor when fitting models, the size of the database used in this study strongly affects the fitting performance of empirical models, whereas artificial neural networks are more influenced by how the data are scaled. Results of model verification show that both techniques are suitable for predicting average cycle times for data outside the range covered by the database.

Algae production process is a key cost center in production of biofuels/bioproducts from microalgae. Decline in the growth of algae in outdoor ponds during non-optimal conditions is one of the hurdles for achieving consistently high algal production rates. An optimal controller can be used to overcome this limitation and provide reliable growth in outdoor conditions. A model predictive controller (MPC) was developed to optimize the algal growth, predicted by flux balance analysis, under natural disturbances, embedding within the cost function, the economic and environmental constraints associated with the process. The model, developed in MATLAB, was validated on a 30-L continuous algal culture under light, temperature and a combination of light and temperature disturbances. The MPC proved effective in minimization of a decrease in growth under these natural disturbances. The growth rates with MPC were observed to be 79-116% higher as compared to the non-MPC growth.