From simulation studies to experimental tests in a reactive dividing wall distillation column

The design and control of thermally coupled distillation sequences have been studied since many years, but the real implementation occurred until middle of the 1980s using a single shell divided by a wall named dividing wall distillation column. In this work, experimental results for the production of ethyl acetate in a reactive dividing wall distillation column are presented for first time. The experimental results are in agreement with those obtained using steady state simulations with AspenONE Aspen plus. These experimental results are important since it is possible to validate most of the previous results generated using simulations.     

High removal of chlorinated solvents by reusable polydimethylsiloxane based absorbents

The objective of this work is to prepare absorbent materials based on polydimethylsiloxane (PDMS) for the absorption of organic solvents by a relative simple method, with large absorption capacities and reusability. Different particles (ZnO, MgSO₄, ZnCl₂, and NaHCO₃) were first incorporated in PDMS and then removed by immersion in HCl (c) or water. The absorbent materials were characterized by TGA, mercury porosimetry, stress–strain curves, SEM, EDS, XPS, FTIR, and water contact angle. The materials can absorb polar organic chlorinated solvents (carbon tetrachloride, dichloroethene, dichloromethane, and chloroform) more than four times its own weight. Other solvents were also tested showing 2–3 times its own weight. Additionally, these materials show demulsification properties and absorption of oleophilic compounds. The reusability of the material makes them good candidates for remediation of polluted water.     

Selective harvesting over networks

Active search on graphs focuses on collecting certain labeled nodes (targets) given global knowledge of the network topology and its edge weights (encoding pairwise similarities) under a query budget constraint. However, in most current networks, nodes, network topology, network size, and edge weights are all initially unknown. In this work we introduce selective harvesting, a variant of active search where the next node to be queried must be chosen among the neighbors of the current queried node set; the available training data for deciding which node to query is restricted to the subgraph induced by the queried set (and their node attributes) and their neighbors (without any node or edge attributes). Therefore, selective harvesting is a sequential decision problem, where we must decide which node to query at each step. A classifier trained in this scenario can suffer from what we call a tunnel vision effect: without any recourse to independent sampling, the urge to only query promising nodes forces classifiers to gather increasingly biased training data, which we show significantly hurts the performance of active search methods and standard classifiers. We demonstrate that it is possible to collect a much larger set of targets by using multiple classifiers, not by combining their predictions as a weighted ensemble, but switching between classifiers used at each step, as a way to ease the tunnel vision effect. We discover that switching classifiers collects more targets by (a) diversifying the training data and (b) broadening the choices of nodes that can be queried in the future. This highlights an exploration, exploitation, and diversification trade-off in our problem that goes beyond the exploration and exploitation duality found in classic sequential decision problems. Based on these observations we propose D\(^3\)TS, a method based on multi-armed bandits for non-stationary stochastic processes that enforces classifier diversity, which outperforms all competing methods on five real network datasets in our evaluation and exhibits comparable performance on the other two.     

Mechanical Behavior and Biodegradation of Poly(ε-caprolactone)/Starch Blends with and without Expansor

Summary The use of biodegradable polymers has provided an alternative to the problem of polymer-based products discarded in the environment. Poly(ε-caprolactone) (PCL) is a biodegradable polymer that has been used industrially, but it is very expensive. Starch is a potentially useful material for biodegradable plastics because of its natural abundance and low cost. The aim of this work was to examine the effect of adding azodicarbonomide (ADC) as an expansor to blends of PCL with corn starch. Different proportions, of ADC (0.1%, 0.2% and 0.3%, w/w) were added to pure PCL and to PCL/starch (50/50) blends and their properties were studied. Biodegradable blends of PCL with starch had a higher density than PCL alone and the addition of ADC reduced the density of the materials. The incorporation of starch increased the water absorption and ADC did not significantly alter this property. The incorporation of starch into PCL reduced the tensile strength and the elongation at break; ADC enhanced these reductions and also decreased the Young’s modulus of PCL. SEM showed that blends prepared with starch were immiscible, had a homogeneous dispersion of starch, and poor interfacial adhesion. The addition of ADC resulted in cells in the interior of the polymers. The 50/50 PCL/starch blends biodegraded faster than PCL, and ADC had no significant influence on the biodegradation of the blends but inhibited the biodegradation of PCL.     

Arachidin-1, a Prenylated Stilbenoid from Peanut,Induces Apoptosis in Triple-Negative Breast Cancer Cells

Triple-negative breast cancer (TNBC) is unresponsive to typical hormonal treatments, causing it to be one of the deadliest forms of breast cancer. Investigating alternative therapies to increase survival rates for this disease is essential. The goal of this study was to assess cytotoxicity and apoptosis mechanisms of prenylated stilbenoids in TNBC cells. The prenylated stilbenoids arachidin-1 (A-1) and arachidin-3 (A-3) are analogs of resveratrol (RES) produced in peanut upon biotic stress. The anticancer activity of A-1 and A-3 isolated from peanut hairy root cultures was determined in TNBC cell lines MDA-MB-231 and MDA-MB-436. After 24 h of treatment, A-1 exhibited higher cytotoxicity than A-3 and RES with approximately 11-fold and six-fold lower IC₅₀, respectively, in MDA-MB-231 cells, and nine-fold and eight-fold lower IC₅₀, respectively, in MDA-MB-436 cells. A-1 did not show significant cytotoxicity in the non-cancerous cell line MCF-10A. While A-1 blocked cell division in G2-M phases in the TNBC cells, it did not affect cell division in MCF-10A cells. Furthermore, A-1 induced caspase-dependent apoptosis through the intrinsic pathway by activating caspase-9 and PARP cleavage, and inhibiting survivin. In conclusion, A-1 merits further research as a potential lead molecule for the treatment of TNBC.     

Global optimization of mass and property integration networks with in-plant property interceptors

This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors within the structure of the network, as opposed to the end-of-pipe use of such interceptors. The model is based on a recycle and reuse scheme that simultaneously satisfies process and environmental constraints. The properties considered in this work are composition, toxicity, theoretical oxygen demand, pH, density and viscosity. The property mixing rules included in the model give rise to bilinear terms for the property operators, and a global optimization algorithm is used for the solution of the model. The model minimizes the total annual cost of the network, which includes the fresh sources cost and the annualized property treatment system and the piping costs. Three examples are included to show the applicability and advantages of the proposed model.     

Synthesis of optimal thermal membrane distillation networks

Thermal membrane distillation (TMD) is an emerging separation method which involves simultaneous heat and mass transfer through a hydrophobic semipermeable membrane. Traditionally, studies of this technology have focused on the performance of individual modules. Because of purity and recovery requirements, multiple TMD modules may be used in various configurations including series, parallel, and combinations. Furthermore, there may be a need to reroute streams from one module to another or to recycle a stream to the same unit. The objective is to develop a systematic approach to synthesize an optimal TMD network. A structural representation is developed to embed potential configurations of interest. A mathematical formulation is developed to transform the design problem into an optimization task that seeks to minimize the cost of the system. Two case studies are presented to illustrate the applicability of the developed approach and its merit over conventional design scenarios. © 2014 American Institute of Chemical Engineers AIChE J, 61: 448–463, 2015     

Kinetic Modeling of Inhibition of Ammonia Oxidation by Nitrite under Low Dissolved Oxygen Conditions

In recent years the application of partial nitrification techniques has been denoted as very promising. These methods are based on the oxidation of ammonia to nitrite and the inhibition of the nitratation using different strategies. In most cases, this inhibition causes an increase in the concentration of nitrite. However, the effect of high nitrite concentrations under low dissolved oxygen (DO) conditions on the nitrification process is not well understood. In this paper, the effect of ammonia, nitrite, and nitrate concentrations on the nitrification process under low dissolved oxygen concentrations were studied using respirometric techniques. Results showed that the specific oxygen uptake rate (SOUR) followed a Monod-type equation with respect to the DO concentration. The coefficient SOURm was constant with respect to the ammonia, nitrite, and nitrate within the tested concentrations; in addition, KO was constant with respect to ammonia and nitrate but it increased linearly with the nitrite concentration, suggesting that nitrite was a competitive inhibitor of the SOUR. The inhibitory effect of nitrite was reverted by washing, in accordance with a competition model. From the data obtained using the open respirometer, the ratio between the oxygen consumption (OC) corresponding to each pulse of ammonia at different nitrite concentrations and the OC in the absence of nitrite (OCO) was calculated. The experimental ratio OC/OCO was almost constant with respect to the nitrite concentration and it was close to the literature value. Finally, simulation results agree with the experimental data confirming that the proposed competition model represented adequately the inhibitory effect of nitrite on the respiration rate of ammonia-oxidizing bacteria.