Characterization of effluent water qualities from satellite membrane bioreactor facilities

Membrane bioreactors (MBRs) are often a preferred treatment technology for satellite water recycling facilities since they produce consistent effluent water quality with a small footprint and require little or no supervision. While the water quality produced from centralized MBRs has been widely reported, there is no study in the literature addressing the effluent quality from a broad range of satellite facilities. Thus, a study was conducted to characterize effluent water qualities produced by satellite MBRs with respect to organic, inorganic, physical and microbial parameters. Results from sampling 38 satellite MBR facilities across the U.S. demonstrated that 90% of these facilities produced nitrified (NH₄-N <0.4 mg/L-N) effluents that have low organic carbon (TOC <8.1 mg/L), turbidities of <0.7 NTU, total coliform bacterial concentrations <100 CFU/100 mL and indigenous MS-2 bacteriophage concentrations <21 PFU/100 mL. Multiple sampling events from selected satellite facilities demonstrated process capability to consistently produce effluent with low concentrations of ammonia, TOC and turbidity. UV-254 transmittance values varied substantially during multiple sampling events indicating a need for attention in designing downstream UV disinfection systems. Although enteroviruses, rotaviruses and hepatitis A viruses (HAV) were absent in all samples, adenoviruses were detected in effluents of all nine MBR facilities sampled. The presence of Giardia cysts in filtrate samples of two of nine MBR facilities sampled demonstrated the need for an appropriate disinfection process at these facilities.     

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.     

Effective components of TORDIA cognitive–behavioral therapy for adolescent depression: Preliminary findings.

In this report, we conducted a secondary analysis of the Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) study to explore the impact of specific cognitive–behavioral therapy (CBT) treatment components on outcome. In TORDIA, 334 youths (ages 12 to 18 years) with major depressive disorder who had failed to respond to an adequate course of selective serotonin reuptake inhibitor (SSRI) medication were randomized to a medication switch (either to an alternative SSRI or venlafaxine) with or without 12 weeks of adjunctive CBT. Participants who had more than 9 CBT sessions were 2.5 times more likely to have adequate treatment response than those who had 9 or fewer sessions. CBT participants who received problem-solving and social skills treatment components, controlling for number of sessions and other confounding variables, were 2.3 and 2.6 times, respectively, more likely to have a positive response. These preliminary findings underscore the importance of receiving an adequate number of sessions to attain an adequate clinical response. Finally, social skills and problem solving may be active elements in CBT for adolescent depression and should be considered in treatment by those working with seriously depressed youths. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A numerical strategy to compute optical parameters in turbulent flow: Application to telescopes

We present a numerical formulation to compute optical parameters in a turbulent air flow. The basic numerical formulation is a large eddy simulation (LES) of the incompressible Navier-Stokes equations, which are approximated using a finite element method. From the time evolution of the flow parameters we describe how to compute statistics of the flow variables and, from them, the parameters that determine the quality of the visibility. The methodology is applied to estimate the optical quality around telescope enclosures.     

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.     

Key competencies of the psychodynamic psychotherapist and how to teach them in supervision.

Four of Rodolfa et al.’s (2005) competencies in professional psychology—relationship, self-reflection, assessment-case conceptualization, and intervention—are key for the psychodynamic psychotherapist. Relationship lies at the heart of what is understood to be curative about psychodynamic psychotherapy. Self-reflection implies a complex and highly developed process that includes but goes beyond Rodolfa et al.’s and Kaslow, Dunn, and Smith’s (2008) definitions. Competent assessment, diagnosis, and case conceptualization entails making inferences about unconscious processes by observing the client and also one’s own experience, and integrating these inferences with theory. Effective psychodynamic intervention is derived from what the psychotherapist has experienced, processed, and conceptualized about the relationship with the client and about the client’s internal object world. An extended vignette shows these competencies emerging in a psychotherapist-in-training, facilitated by an intense interaction with a supervisor. Although the supervisory and clinical tasks are different, the supervisor provides a relationship experience that models these same competencies for the supervisee and catalyzes their development in the supervisee. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A probabilistic fatigue strength model for brick masonry under compression

The paper presents the development of a model for the fatigue resistance of brick masonry under compression. The model takes into account the random nature of the fatigue strength phenomena and, as a consequence, proposes different model parameters as a function of the desired probability level. The model, based on a Weibull distribution, has been calibrated with the still limited experimental data on brick masonry under high cycle compression loading. Very good correlation is obtained. The results show that there is a clear trend of the experimental data to follow the Weibull distribution. It is also shown how the fatigue resistance of brick masonry is not only dependent on the magnitude of the stress cycles, but also on the magnitude of the minimum stress level. The paper also shows how the proposed model can be used in the reliability-based assessment of the fatigue performance of existing masonry arch bridges. Either the nominal probability of failure (reliability index) to fatigue or the remaining service life with a predefined probability level for an existing bridge can be predicted with the proposed method.