Physical and Morphological Properties of Combined Treated Wood Polymer Composites by Maleic Anhydride and Methyl Methacrylate

Wood polymer composites were prepared by consecutive impregnation with maleic anhydride (MAN) and methyl methacrylate (MMA). Samples impregnated with MAN alone, were heated at 120°C and 150°C for 4 and 8 h. Based on the Fourier transform infrared (FT-IR) analysis and soaking-drying test results, treatment with MAN at 150°C for 4 h resulted in formation of stable crosslinks. In the second stage, MMA was used for in situ polymerization within MAN-treated wood. Field emission scanning electron microscopy observation and FT-IR analysis indicated that MMA copolymerized with MAN, and the resultant polymer filled up the lumen and is also grafted on to the cell wall. Improvement of water repellency and dimensional stability were observed in the treated samples, particularly in combined treated samples. The MAN/MMA treatment improved interaction between polymer and wood.     

Meanings of limited equity homeownership in community land trusts

Abstract

Discourses regarding homeownership in the United States emphasize housing as an economic investment. This focus fosters a number of problems, including inflated housing values, increased segregation, economic divisions, and the foreclosure crisis. Community land trusts (CLTs) put land in a non-profit trust to keep it affordable long-term. We examine CLTs as affordable housing organizations where individual residents own homes in the trust and lease the land underneath from the CLT. Interviews of CLT homeowners and staff in Minnesota, USA, show that the use value of CLT housing creates opportunities for different life choices. CLT homeowners cite stability and autonomy as the primary benefits of homeownership. They expressed newfound confidence and freedom to pursue personal goals and live less restricted lives after moving into CLT homes, a finding also emphasized by CLT staff. Limited equity housing such as CLTs can both reinforce dominant meanings of homeownership as providing security and autonomy, while also fostering access and affordability for low-income residents.     

Melt blending of carbon nanotubes/polyaniline/polypropylene compounds and their melt spinning to conductive fibres

Blends of polypropylene with polyaniline and multi-walled carbon nanotubes have been prepared and melt spun to fibre filaments. The resulted filaments have been characterised regarding conductivity, morphology, thermal and mechanical properties. DSC suggests that carbon nanotubes act as nucleating sites for PP/polyaniline blend. Electrical conductivity has been measured for blends with extruded rod shape, as-spun fibre filaments and fibres made under draw ratio of four. Polypropylene containing 20 wt% polyaniline polymer modified with 7.5 wt% carbon nanotubes shows the maximum conductivity among all the samples, about 0.16 S/cm.     

Optimization of Short Load Forecasting in Electricity Market of Iran Using Artificial Neural Networks

Accurate short-term load forecasting (STLF) is one of the essential requirements for power systems. In this paper, two different seasonal artificial neural networks (ANNs) are designed and compared in terms of model complexity, robustness, and forecasting accuracy. Furthermore, the performance of ANN partitioning is evaluated. The first model is a daily forecasting model which is used for forecasting hourly load of the next day. The second model is composed of 24 sub-networks which are used for forecasting hourly load of the next day. In fact, the second model is partitioning of the first model. Time, temperature, and historical loads are taken as inputs for ANN models. The neural network models are based on feed-forward back propagation which are trained and tested using data from electricity market of Iran during 2003 to 2005. Results show a good correlation between actual data and ANN outcomes. Moreover, it is shown that the first designed model consisting of single ANN is more appropriate than the second model consisting of 24 distinct ANNs. Finally ANN results are compared to conventional regression models. It is observed that in most cases ANN models are superior to regression models in terms of mean absolute percentage error (MAPE).     

The Electrochemical Behavior of Au/AuNPs/PNA/ZnSe-QD/ACA Electrode Towards CySH Oxidation

Nano-Micro Letters - This work describes the electrochemical behavior of azodicarboxamide (ACA) film immobilized on the surface of penicillamine (PNA)/ZnSe-quantum dot (ZnSe-QD) gold nanoparticle...     

An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors

This paper introduces an integrated approach based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT) for total energy efficiency assessment and optimization in energy intensive manufacturing sectors. Total energy efficiency assessment and optimization of the proposed approach considers structural indicators in addition conventional consumption and manufacturing sector output indicators. The validity of the DEA model is verified and validated by PCA and NT through Spearman correlation experiment. Moreover, the proposed approach uses the measure-specific super-efficiency DEA model for sensitivity analysis to determine the critical energy carriers. Four energy intensive manufacturing sectors are discussed in this paper: iron and steel, pulp and paper, petroleum refining and cement manufacturing sectors. To show superiority and applicability, the proposed approach has been applied to refinery sub-sectors of some OECD (Organization for Economic Cooperation and Development) countries. This study has several unique features which are: (1) a total approach which considers structural indicators in addition to conventional energy efficiency indicators; (2) a verification and validation mechanism for DEA by PCA and NT and (3) utilization of DEA for total energy efficiency assessment and consumption optimization of energy intensive manufacturing sectors.     

Preparation of polymer-coated, scintillating ion-exchange resins for monitoring of 99Tc in groundwater

The present study was oriented to prepare new scintillating anion-exchange resins for measurement of (99)TcO(4)(-) in natural waters. The organic fluor 2-(1-naphthyl)-5-phenyloxazole was diffused into (chloromethyl)polystyrene resin. Thereafter, a thin layer of poly[[2-(methacryloyloxy)ethyl]trimethylammonium chloride] was grafted from the resin surface by surface-initiated atom transfer radical polymerization as an attempt to overcome potential problems related to the leaching of fluor molecules during usage. The residual chloromethyl groups of the polymer-coated resin were aminated by reaction with two different tertiary amines, triethylamine (TEA) and methyldioctylamine (MDOA). Off- and on-line quantification of (99)Tc was achieved with high detection efficiencies of 60.72 ± 1.93% and 72.83 ± 0.81% for resin with TEA and MDOA functional groups, respectively. The detection limit was determined to be less than the maximum contaminant level (33 Bq L(-1)) established under the Safe Drinking Water Act. The two functionalized resins were demonstrated to be selective for pertechnetate from synthetic groundwater containing up to 1000 ppm Cl(-), SO(4)(2-), and HCO(3)(-) and up to 1200 ppb Cr(2)O(7)(2-) in an acidic medium.     

An integrated fuzzy regression-data envelopment analysis algorithm for optimum oil consumption estimation with ambiguous data

This study introduces an integrated fuzzy regression (FR) data envelopment analysis (DEA) algorithm for oil consumption estimation and optimization with uncertain and ambiguous data. This is quite important as oil consumption estimations deals with several uncertainties due to social, economic factors. Furthermore, DEA is integrated with FR because there is no clear cut as to which FR approach is superior for oil consumption estimation. The standard indicators used in this paper are population, cost of crude oil, gross domestic production (GDP) and annual oil production. Fifteen popular and most cited FR models are considered in the algorithm. Each FR model has different approach and advantages. The input data is divided into train and test data. The FR models have been tuned for all their parameters according to the train data, and the best coefficients are identified. Center of Average Method for defuzzification output process is applied. For determining the rate of error of FR models estimations, the rate of defuzzified output of each model is compared with its actual rate consumption in test data. The efficiency of 15 FR models is examined by the output-oriented Data Envelopment Analysis (DEA) model without inputs by considering three types of relative error: RMSE, MAE and MAPE. The applicability and superiority of the proposed algorithm is shown for monthly oil consumption of Canada, United States, Japan and Australia from 1990 to 2005.     

Glass microparticle- versus microsphere-filled experimental dental adhesives

This study aimed to formulate antibacterial dental adhesives. Phosphate-substituted methacrylate adhesives were modified with 0–20 wt % copper-doped glass microparticles. Two shapes of microparticles were used: regular shaped (microspheres) and irregular shaped (microparticles). The morphology/composition, roughness, monomer conversion (DC%), thermogravimetric analysis, and antibacterial action against S. mutans and P. aeruginosa and ion release were investigated. The results showed that microspheres produced adhesives with a relatively smoother surface than microparticles did. The DC% of adhesives increased with increasing glass filler content. Filled adhesives showed polymer decomposition at ~315 °C and glass melting at 600–1000 °C. The weight loss percent of adhesives decreased with increasing weight percent of fillers. Glass microparticles at 0–20 wt % significantly increased the antibacterial action of adhesives against both bacteria. Glass microspheres at 0–5 wt % significantly increased the antibacterial action of adhesives against both bacteria. Only 20 wt % microparticle-filled adhesive showed an inhibition zone similar to tobramycin (positive control). Microparticle-filled adhesives (with >5 wt % filler) significantly reduced S. mutans more than their microsphere counterparts. Microsphere-filled adhesives (with ≤5 wt % filler) significantly reduced P. aeruginosa more than their microparticle counterparts. Microsphere-filled adhesives showed higher Cu release than their microparticle counterparts. Accordingly, phosphate-substituted methacrylate filled with glass could be used as an antibacterial adhesive. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47832.     

Application of saturation transfer double difference NMR to elucidate the mechanistic interactions of pesticides with humic acid

Elucidation of mechanistic interactions of anthropogenic chemicals is critical to understanding and eventually predicting their behavior in the environment Here, a recently developed technique, saturation transfer double difference (STDD) NMR spectroscopy is employed to determine the interactions of pesticides with humic acid (HA) at the molecular level. The degree of interaction at each NMR observable nucleus in the pesticide can be quantified in the form of an epitope map, which depicts the mechanism of the pesticide-HA interaction. Our results indicate that, at pH 7, halogen atoms (F and Cl) in water-soluble pesticides (diflufenzopyr, acifluorfen, and chlorsulfuron) play a dominant role in influencing binding to HA, whereas carboxyl groups likely play a secondary role when halogen atoms are also present in the molecule, as observed with diflufenzopyr and acifluorfen. However, when present on its own, the carboxyl group dominates in binding affinityto HA (e.g., imazapyr). Electronegativity and electron density appear to play a key role in the mechanism of binding and results suggest that polar bonds are the primary points of HA contact in the water soluble pesticides investigated. Likely interactions may include hydrogen bonding and dipole-dipole interactions.