A structured overview on the use of computational simulators for teaching statistical methods

Modern technology is affecting what is taught and how statistics is taught. Computer intensive methods like bootstrapping, generalized regression, coordinate exchange algorithms and computer experiment emulators are now part of the statistical toolkit. In parallel with these new methods and tools, a similar evolution appears in statistical education. Simulators offer opportunities for hands-on experience in the classroom, bridging the gap between theory and practice. In this article, we map a wide range of simulation based tools used in teaching statistical methods, putting them in the context of a quality ladder representing various maturity levels of organizations and course level sophistication. The mapping is designed to help educators assess and integrate options related to the incorporation of simulators as teaching aids in an educational and pedagogical roadmap. The mapping is applied to specific simulation products but provides a general framework that can be expanded and used in a generic way.     

Development of semitransparent wood‐polymer composites

A new material has been developed consisting of pieces of wood embedded within a matrix of acrylic polymer, resulting in a transparent or semitransparent wood‐based product. This material presents quite appealing aesthetic features, thereby opening new possibilities for decorative applications. Because acrylic and methacrylic monomers are in the liquid state at room temperature, it is possible to introduce wood (in the current case, walnut wood) into a mixture of acrylic (hydroxypropyl acrylate) and/or methacrylic monomers (methyl methacrylate and 2‐hydroxyethyl methacrylate) along with a plasticizer (dioctyl phthalate) in the presence of a chemical initiator (benzoyl peroxide). A transparent polymeric matrix with dispersed wood is then obtained through bulk free‐radical polymerization. Introducing this reaction mixture along with pieces of wood into a mold results in a wood‐polymer composite. A 2^4?1 experimental fractional factorial design was implemented to study the importance of the composition of these materials on several relevant properties. The sheets produced were characterized by tensile testing, dynamic mechanical thermal analysis, thermal gravimetric analysis, and heat deflection temperature. The models obtained for predicting each property pointed to valuable insights regarding the influential constituents. In particular, our results suggested that monomers to be used in future applications of this material should be selected in terms of their cost and the desired flexibility for the final product, not in terms of their polarity. J. VINYL ADDIT. TECHNOL., 2012. © 2012 Society of Plastics Engineers     

Estimate of Suspended Sediment Concentration from Monitored Data of Turbidity and Water Level Using Artificial Neural Networks

Artificial neural networks (ANNs) are promising alternatives for the estimation of suspended sediment concentration (SSC), but they are dependent on the availability data. This study investigates the use of an ANN model for forecasting SSC using turbidity and water level. It is used an original method, idealized to investigate the minimum complexity of the ANN that does not present, in relation to more complex networks, loss of efficiency when applied to other samples, and to perform its training avoiding the overfitting even when data availability is insufficient to use the cross-validation technique. The use of a validation procedure by resampling, the control of overfitting through a previously researched condition of training completion, as well as training repetitions to provide robustness are important aspects of the method. Turbidity and water level data, related to 59 SSC values, collected between June 2013 and October 2015, were used. The development of the proposed ANN was preceded by the training of an ANN, without the use of the new resources, which clearly showed the overfitting occurrence when resources were not used to avoid it, with Nash-Sutcliffe efficiency (NS) equals to 0.995 in the training and NS = 0.788 in the verification. The proposed method generated efficient models (NS = 0.953 for verification), with well distributed errors and with great capacity of generalization for future applications. The final obtained model enabled the SSC calculation, from water level and turbidity data, even when few samples were available for the training and verification procedures.     

Metabolic versatility in full-scale wastewater treatment plants performing enhanced biological phosphorus removal

This study analysed the enhanced biological phosphorus removal (EBPR) microbial community and metabolic performance of five full-scale EBPR systems by using fluorescence in situ hybridisation combined with off-line batch tests fed with acetate under anaerobic–aerobic conditions. The phosphorus accumulating organisms (PAOs) in all systems were stable and showed little variability between each plant, while glycogen accumulating organisms (GAOs) were present in two of the plants. The metabolic activity of each sludge showed the frequent involvement of the anaerobic tricarboxylic acid cycle (TCA) in PAO metabolism for the anaerobic generation of reducing equivalents, in addition to the more frequently reported glycolysis pathway. Metabolic variability in the use of the two pathways was also observed, between different systems and in the same system over time. The metabolic dynamics was linked to the availability of glycogen, where a higher utilisation of the glycolysis pathway was observed in the two systems employing side-stream hydrolysis, and the TCA cycle was more active in the A²O systems. Full-scale plants that showed higher glycolysis activity also exhibited superior P removal performance, suggesting that promotion of the glycolysis pathway over the TCA cycle could be beneficial towards the optimisation of EBPR systems.     

Sustained release of potassium diclofenac from a pH‐responsive hydrogel based on gum arabic conjugates into simulated intestinal fluid

This work describes the preparation, the swelling properties and the potassium diclofenac (KDF) release profile of hydrogels of gum arabic (GA), N′,N′‐dimethylacrylamide, and methacrylic acid. In order to convert GA into a hydrogel, the polysaccharide was vinyl‐modified with glycidyl methacrylate. The hydrogels showed pH‐responsive swelling changes, which were more expressive in the basic environment. Release data of KDF were adjusted to a diffusion‐based kinetic model that provides an important insight on affinity of the drug for hydrogel and solvent, which may be the leading parameter for release of guest molecules from polymers. The KDF release from the hydrogels into simulated intestinal fluid decreases when the amount of modified GA increases. This was demonstrated to be due to the higher affinity of KDF for GA‐richer hydrogel, which makes the anti‐inflammatory release less favorable. The analysis of released drug half‐time (t_1/2 = 16.10 and 21.51 h) indicated sustained release characteristics. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43319.     

Influence of the chemical structure of additives poly(ethylene-co-vinyl acetate)-based on the pour point of crude oils

One of the methods to prevent wax precipitation, during petroleum production, transport, and refining, is the use of polymer additives that can reduce the oil pour point. However, no single additive work for all types of crude oil and this relation is not yet well known. In this study, a family of polymers based on poly(ethylene-co-vinyl acetate), containing hydroxyl groups and long pendant hydrocarbon chains (from C6 to C18), were synthesized and characterized by H¹ nuclear magnetic resonance and solubility test. Four crude oil samples containing different amounts and size distribution of the wax were used. The additive's action is favored by higher contents of iso + cycloalkanes and lower contents of n-paraffins with larger chain sizes. The presence of the CH₃COO group in the copolymers promoted the lowering of the pour point, supported by a low OH concentration and the presence of a long pendant hydrocarbon chain: the best results were obtained with C10 and C12 chain lengths. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48969.     

Methicillin‐Resistant Staphylococcus aureus in Raw Meats and Prepared Foods in Public Hospitals in Salvador,Bahia, Brazil

This study investigated the presence of methicillin‐resistant Staphylococcus aureus (MRSA) in raw meat and fish and foods prepared from them for patient consumption in public hospitals in Salvador, Bahia, in northeastern Brazil. A total of 114 samples of raw meat and fish (chicken, n = 30; beef, n = 30; pork, n = 24; and fish, n = 30) and 63 samples of prepared foods (made with chicken, n = 15; beef, n = 15; pork, n = 15; and fish, n = 18) were collected from the kitchens of 10 different hospitals. Of the 114 investigated raw meat and fish samples, 28.1% were positive for MRSA, which comprised 23.3% beef, 23.3% chicken, 37.5% pork, and 30% fish samples. Of the prepared foods, 9.5% were positive for MRSA, which comprised 5.6% chicken products, 6.7% pork products, and 22.2% fish products. MRSA contamination was not detected in prepared beef dishes. A statistical analysis showed no association between the presence of MRSA and the type of raw food (P > 0.05). The high prevalence of MRSA among the raw foods tested and the presence of the microorganism in prepared foods emphasizes the necessity of enforcing hygienic practices within hospital kitchens.