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.     

Molecular interactions of pesticides at the soil-water interface

High-resolution magic angle spinning (HR-MAS) NMR spectroscopy combined with saturation-transfer double difference (STDD) NMR can be used to analyze the molecular-level interactions of pesticides and whole soils occurring at the soil-water interface. Here 1H HR-MAS STDD NMR has been applied to some common pesticides (trifluralin, acifluorfen, and (4-nitro-3-(trifluoromethyl) phenol) and a pesticide degradation product (1-naphthol). Results indicate that dipolar interactions, H-bonding, hydrophobic associations, and potentially pi-pi interactions are the predominant sorption mechanisms for these molecules at the soil-aqueous interface. It is evident that the physical and chemical characteristics of soil are highly influential in determining the mechanisms of pesticide sorption, as they significantly affect soil conformation. In particular, different binding mechanisms were observed for 1-naphthol in soil swollen using a buffer versus D2O, indicating that the K(oc) alone may not be enough to accurately predict the behavior of a molecule in a real soil environment. Preliminary kinetic-based studies suggest that both the swelling solvent and soil moisture content significantly influence the sequestration of trifluralin. These studies demonstrate that HR-MAS and STDD NMR are powerful and versatile tools which can be applied to expand our knowledge of the mechanistic interactions of agrochemicals at the molecular level.     

Comparison between lipid and protein oxidation progress in the tail and claw muscles of signal crayfish (Pacifastacus leniusculus)

Microbial activity and then oxidation progress are the most important freshness indicators during post-mortem. In this study, we monitored proteomic and microbial changes, as well as biochemical degradation, in the tail and claw muscles of crayfish stored for 12 days at +4 °C. One specified protein band at 107 kDa in the claw muscle and two specified protein bands in the tail muscle at 140 and 36–40 kDa were identified. Western blotting indicated a higher amount of oxidised proteins in the tail compared to the claw muscle. Tail muscle showed higher oxidation progress and calpain activity than claw one. Both muscles were spoiled after 12 days with respect to total viable counts. In the first days, calpain activity is the main reason for protein degradation, while protein oxidation dominates for the rest of the time. Lipid–protein oxidation progress showed probably, protein oxidation started earlier than lipid oxidation in both muscles.     

An integrated approach for aircraft turbofan engine fault detection based on data mining techniques

The present study proposes an algorithm for fault detection in terms of condition‐based maintenance with data mining techniques. The proposed algorithm is applied on an aircraft turbofan engine using flight data and consists of two main sections. In the first section, the relationship between engine exhaust gas temperature (EGT) as the main engine health monitoring criterion and other operational and environmental parameters of the engine was modelled using the data‐driven models. In the second section, a data set including EGT residuals, that is, the difference between the actual EGT of the system and the EGT estimated by the developed model in the health conditions of the engine, was created. Finally, faults occurring in each flight were detected based on the identification of abnormal events by a one‐class support vector machine trained by the health condition EGT residual data set. The results indicated that the proposed algorithm was an effective approach for inspecting aircraft engine conditions and detecting faults, with no need for technical knowledge on the interior characteristics of the aircraft engine.     

A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services

Mobile Networks and Applications - This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is...     

Optimum alternatives of tandem G/G/K queues with disaster customers and retrial phenomenon: interactive voice response systems

In this paper, we study a tandem queue with retrials where the queue experiences disasters. The probability of system failure depends on the strength of equipment, which makes servers idle and causes the removal of all customers in queues and service areas at once. The customers in the queue are forced to orbit in a retrial queue during the system failure where they decide whether or not to come back to the system. Reducing the disaster arrival rate (the probability of system failure) by employing more servers and reducing the number of lost customers is very costly. Moreover, it is important to service the customers with no interruption and reduce the time in system. The developed scenarios are compared in five dimensions including time in system, cost of lost customer, operator cost, the number of uninterrupted service customers and cost of reducing disaster arrival rate (or empowering system cost). The scenarios are modeled by computer simulation. Then, the optimal scenario is chosen using data envelopment analysis. The optimal scenario maximizes system efficiency in terms of disaster arrival rate, cost of lost customers and the number of satisfied customers. In the main problem, the disasters arrive at the system according to Poisson process; the effect of changing the distribution function of disaster arrival has been investigated finally. We are among the first ones to study and optimize G/G/K tandem queuing systems with system failures and retrial phenomena in interactive voice response systems.     

Stability Analysis of Stakeholders’ Cooperation in Inter-Basin Water Transfer Projects: a Case Study

Water Resources Management - This study investigates the conflict resolution among different stakeholders in a water transfer project. The portion of the Beheshtabad Water Transfer Project in Iran...