Toward the prediction of porous membrane permeability from morphological data

One of the challenges in membrane technology is predicting permeability in porous membranes for liquid applications in an easy and inexpensive way. This is the aim of this work. To achieve this objective, several techniques can be considered. In this study, a morphological approach from two‐dimensional scanning electron micrographs is proposed. First, numerical membrane morphological parameters have been determined from micrographs by using the QUANTS tool, which applies a texture recognition process. Second, the obtained data have been fit to the Darcy's and Hagen–Poiseuille models to calculate permeations. The QUANTS results have also been compared with the ones obtained through a mercury porosimeter, which is a classic and well‐known methodology. Each parameter of the Hagen–Poiseuille model has been analyzed. A comparison between experimentally measured permeations and calculated ones has been performed. An even easier approach is proposed to predict flow rate with the only knowledge of membrane surface mean pore size. This method is based on cross‐section pore size interpolation by using function fits from surface mean pore sizes. The obtained results show a reasonable agreement between measured and computed results, making this technique a valid approach for predicting membrane permeability. POLYM. ENG. SCI., 56:118–124, 2016. © 2015 Society of Plastics Engineers     

A genetic algorithm for energy-efficiency in job-shop scheduling

Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost, and quality as optimization objectives. Currently, energy-efficiency is also taken into consideration in these problems. However, this problem is NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the Job-shop Scheduling Problem in which machines can consume different amounts of energy to process tasks at different rates (speed scaling). This problem represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The evaluation section shows that a powerful commercial tool for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality.     

Functional mesoporous poly(ionic liquid)-based copolymer monoliths: From synthesis to catalysis and microporous carbon production

Ionic liquid-functionalized mesoporous polymeric networks with specific surface area up to 935 m²/g have been successfully synthesized one pot by solvothermal copolymerization of divinylbenzene and monomeric ionic liquids. The as-obtained polymers exhibit a monolithic structure featuring large pore volumes, an abundant mesoporosity and an adjustable content of ionic liquids. The effect of the reaction conditions on the pore structure has been studied in detail. These poly(ionic liquid)-based porous networks (PILPNs) have then been employed as precursors in two distinct applications, namely organocatalysis and production of microporous carbon monoliths. Selected organocatalyzed reactions, including carbonatation of propylene oxide by cycloaddition with carbon dioxide, benzoin condensation, and cyanosilylation of benzaldehyde have been readily triggered by PILPNs acting as crosslinked polymer-supported (pre)catalysts. The two latter reactions required the prior deprotonation of the imidazolium salt units with a strong base to successfully generate polymer-supported N-heterocyclic carbenes, referred to as poly(NHC)s. Facile recycling and reuse of polymer-supported (pre)catalysts was achieved by simple filtration owing to the heterogeneous reaction conditions. Furthermore, PILPNs could be easily converted into microporous carbon monoliths via CO₂ activation.     

Learning curve analysis of concentrated photovoltaic systems

Price declines and volume growth of concentrated photovoltaic (CPV) systems are analysed using the learning curve methodology and compared with other forms of solar electricity generation. Logarithmic regression analysis determines a learning rate of 18% for CPV systems with 90% confidence of that rate being between 14 and 22%, which is higher than the learning rates of other solar generation systems (11% for CSP and 12 to 14% for PV). Current CPV system prices are competitive with PV and CSP, which, when combined with the higher learning rate, indicates that CPV is likely to further improve its marketability. A target price of 1 $/W in 2020 could be achieved with a compound growth rate of 67% for the total deployed volume between 2014 and 2020, which would realize a cumulative deployed volume of 7900 MW. Other projections of deployment volumes from commercial sources are converted using the learning rate into future price scenarios, resulting in predicted prices in the range of 1.1 to 1.3 $/W in 2020. © 2014 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd.     

Polyunsaturated Fatty Acid-Enriched Lipid Fingerprint of Glioblastoma Proliferative Regions Is Differentially Regulated According to Glioblastoma Molecular Subtype

Glioblastoma (GBM) represents one of the deadliest tumors owing to a lack of effective treatments. The adverse outcomes are worsened by high rates of treatment discontinuation, caused by the severe side effects of temozolomide (TMZ), the reference treatment. Therefore, understanding TMZ’s effects on GBM and healthy brain tissue could reveal new approaches to address chemotherapy side effects. In this context, we have previously demonstrated the membrane lipidome is highly cell type-specific and very sensitive to pathophysiological states. However, little remains known as to how membrane lipids participate in GBM onset and progression. Hence, we employed an ex vivo model to assess the impact of TMZ treatment on healthy and GBM lipidome, which was established through imaging mass spectrometry techniques. This approach revealed that bioactive lipid metabolic hubs (phosphatidylinositol and phosphatidylethanolamine plasmalogen species) were altered in healthy brain tissue treated with TMZ. To better understand these changes, we interrogated RNA expression and DNA methylation datasets of the Cancer Genome Atlas database. The results enabled GBM subtypes and patient survival to be linked with the expression of enzymes accounting for the observed lipidome, thus proving that exploring the lipid changes could reveal promising therapeutic approaches for GBM, and ways to ameliorate TMZ side effects.     

The contribution of electron microscopic cytochemistry to an understanding of the biogenesis of the endoplasmic reticulum of rat hepatocytes

The endoplasmic reticulum has the enzymic machinery for the synthesis of both protein and phospholipid and hence plays a central role in its own biogenesis and that of other cellular membranes. The evidence available concerning the biogenesis of the phospholipid bilayer of the endoplasmic reticulum, particularly from the application of fine structural cytochemical methods for the localization of acyltransferases, is reviewed. The observations are consistent with a model in which phospholipid is synthesized in situ at the site of membrane growth. Synthesis is asymmetric, with most enzymes located at the cytoplasmic side of the membrane, and controlled transmembrane movement of phospholipid results in an asymmetric bilayer.     

Active nano-CuPt3 electrocatalyst supported on graphene for enhancing reactions at the cathode in all-vanadium redox flow batteries

Graphene-supported monometallic (Pt) and bimetallic (CuPt₃) cubic nanocatalysts have been investigated as new positive electrode materials for improving the VO₂⁺/VO²⁺ redox process occurring in the vanadium redox flow batteries (VRB). High-resolution transmission electron microscopy (HRTEM) and scanning electron microscopy (SEM) have been employed to characterize the electrodes. The presence of the CuPt₃ nanocubes on graphene conferred higher electrocatalytic activity due to the much higher electroactive area compared to that obtained with the Pt nanoparticles. The electrochemical surface area of the nano-(CuPt₃)-decorated graphene electrode was 105% higher compared to non-decorated graphene, being then a promising alternative for improving the VRB.     

Driving factors of the phytoplankton functional groups in a deep Mediterranean reservoir

The control of phytoplankton growth is mainly related to the availability of light and nutrients. Both may select phytoplankton species, but only if they occur in limiting amounts. During the last decade, the functional groups approach, based on the physiological, morphological and ecological attributes of the species, has proved to be a more efficient way to analyze seasonal changes in phytoplankton biomass. We analysed the dynamics of the phytoplankton functional groups sensu Reynolds, recognising the driving forces (light, mixing regime, and nutrients) in the Sau Reservoir, based on a one-year cycle (monthly surface-water sampling). The Sau Reservoir is a Mediterranean water-supply reservoir with a canyon-shaped basin and a clear and mixed epilimnion layer. The long stratification period and high light availability led to high phytoplankton biomass (110.8 fresh-weight mg L⁻¹) in the epilimnion during summer. The reservoir showed P-limitation for phytoplankton growth in this period. All functional groups included one or more species (X2-Rhodomonas spp.; Y-Cryptomonas spp.; F-Oocystis lacustris; K-Aphanocapsa spp.) selected by resources, especially phosphorus. Species of Cryptomonas (group Y) dominated during the mixing period (winter season) in conditions of low light and relatively high availability of dissolved nutrients. Increases in water-column stability during spring stratification led to phytoplankton biomass increases due to the dominance of small flagellate functional groups (X2 and X3, chrysophyceans). The colonial chlorophycean O. lacustris (group F) peaked during the mid-summer stratification, when the mixed epilimnion was clearly depleted in nutrients, especially SRP. High temperature and increases in nutrient concentration during the end-summer and mid-autumn resulted in a decrease of green algae (group F) and increase of Aphanocapsa spp. (cyanobacteria, group K) and dinoflagellates (group L_o). The study also revealed the important role of physical processes in the seasonal gradient, in selecting phytoplankton functional groups, and consequently in the assessment of ecological status. The Q index (assemblage index) based on functional groups indicated the overall good ecological status of the Sau Reservoir, which varied as a function of the mixing regime. This is the first application of the Assemblage Index to a European water-supply reservoir.     

Computerized and written questionnaires: Are they equivalent?

In this set of three studies, comparisons were made between computer-administered questionnaires and those administered in written form. Specifically, we examined nonclinical subjects' affective reactions to the two modes of questionnaire administration and their responses to a variety of commonly used attitude and personality measures. Subjects' affective reactions to the two modes of administration did not differ. With respect to questionnaire responses, there is some evidence suggesting that computer administration may slightly increase socially desirable responding amongst those subjects with relatively little computer experience. Overall, however, the differences between the two conditions were negligible, suggesting that social scientists should not hesitate to take advantage of the benefits of computer-administered questionnaires.     

Environmental aspects of ethanol-based fuels from Brassica carinata: A case study of second generation ethanol

One of the main challenges faced by mankind in the 21st century is to meet the increasing demand for energy requirements by means of a more sustainable energy supply. In countries that are net fossil fuel importers, expectation about the benefit of using alternative fuels on reducing oil imports is the primary driving force behind efforts to promote its production and use. Spain is scarce in domestic energy sources and more than 50% of the energy used is fossil fuel based. The promotion of renewable energies use is one of the principal vectors in the Spanish energy policy. Selected herbaceous crops such as Brassica carinata are currently under study as potential energy sources. Its biomass can be considered as potential feedstock to ethanol conversion by an enzymatic process due to the characteristics of its composition, rich in cellulose and hemicellulose. This paper aims to analyse the environmental performance of two ethanol-based fuel applications (E10 and E85) in a passenger car (E10 fuel: a mixture of 10% ethanol and 90% gasoline by volume; E85 fuel: a mixture of 85% ethanol and 15% gasoline by volume) as well as their comparison with conventional gasoline as transport fuel. Two types of functional units are applied in this study: ethanol production oriented and travelling distance oriented functional units in order to reflect the availability or not of ethanol supply. E85 seems to be the best alternative when ethanol production based functional unit is considered in terms of greenhouse gas (GHG) emissions and E10 in terms of non-renewable energy resources use. Nevertheless, E85 offers the best environmental performance when travelling distance oriented functional unit is assumed in both impacts. In both functional unit perspectives, the use of ethanol-based fuels reduces the global warming and fossil fuels consumption. However, the contributions to other impact indicators (e.g. acidification, eutrophication and photochemical oxidants formation) were lower for conventional gasoline.Life Cycle Assessment (LCA) procedure helps to identify the key areas in the B. carinata ethanol production life cycle where the researchers and technicians need to work to improve the environmental performance. Technological development could help in lowering both the environmental impact and the prices of the ethanol fuels.