Stress and strain distribution in demineralized enamel: A micro‐CT based finite element study

Physiological oral mechanical forces may play a role on the progression of enamel carious lesions to cavitation. Thus, the aim of this study was to describe, by 3D finite element analysis, stress, and strain patterns in sound and carious enamel after a simulated occlusal load. Micro‐CT based models were created and meshed with tetrahedral elements (based on an extracted third molar), namely: a sound (ST) and a carious tooth (CT). For the CT, enamel material properties were assigned according to the micro‐CT gray values. Below the threshold corresponding to the enamel lesion (2.5 g/cm³) lower and isotropic elastic modulus was assigned (E = 18 GPa against E₁ = 80 GPa, E₂ = E₃ = 20 GPa for sound enamel). Both models were imported into a FE solver where boundary conditions were assigned and a pressure load (500 MPa) was applied at the occlusal surface. A linear static analysis was performed, considering anisotropy in sound enamel. ST showed a more efficient transfer of maximum principal stress from enamel to the dentin layer, while for the CT, enamel layer was subjected to higher and concentrated loads. Maximum principal strain distributions were seen at the carious enamel surface, especially at the central fossa, correlating to the enamel cavity seen at the original micro‐CT model. It is possible to conclude that demineralized enamel compromises appropriate stress transfer from enamel to dentin, contributing to the odds of fracture and cavitation. Enamel fracture over a dentin lesion may happen as one of the normal pathways to caries progression and may act as a confounding factor during clinical diagnostic decisions. Microsc. Res. Tech. 78:865–872, 2015. © 2015 Wiley Periodicals, Inc.     

Bayesian Model Uncertainty In Smooth Transition Autoregressions

Abstract. In this paper, we propose a fully Bayesian approach to the special class of nonlinear time‐series models called the logistic smooth transition autoregressive (LSTAR) model. Initially, a Gibbs sampler is proposed for the LSTAR where the lag length, k, is kept fixed. Then, uncertainty about k is taken into account and a novel reversible jump Markov Chain Monte Carlo (RJMCMC) algorithm is proposed. We compared our RJMCMC algorithm with well‐known information criteria, such as the Akaikes? information criteria, the Bayesian information criteria (BIC) and the deviance information criteria. Our methodology is extensively studied against simulated and real‐time series.     

Microbiological status of fresh beef cuts

Fresh beef samples (n = 1,022) obtained from two processing plants in the Midwest (July to December 2003) were analyzed for levels of microbial populations (total aerobic plate count, total coliform count, and Escherichia coli count) and for the presence or absence of E. coli O157:H7 and Salmonella. A fresh beef cut sample was a 360-g composite of 6-g portions excised from the surface of 60 individual representative cuts in a production lot. Samples of fresh beef cuts yielded levels of 4.0 to 6.2, 1.1 to 1.8, and 0.8 to 1.0 log CFU/g for total aerobic plate count, total coliform count, and E. coli count, respectively. There did not appear to be substantial differences or obvious trends in bacterial populations on different cuts. These data may be useful in establishing a baseline or a benchmark of microbiological levels of contamination of beef cuts. Mean incidence rates of E. coli O157:H7 and Salmonella on raw beef cuts were 0.3 and 2.2%, respectively. Of the 1,022 samples analyzed, cuts testing positive for E. coli O157:H7 included top sirloin butt (0.9%) and butt, ball tip (2.1%) and for Salmonella included short loins (3.4%), strip loins (9.6%), rib eye roll (0.8%), shoulder clod (3.4%), and clod, top blade (1.8%). These data provide evidence of noticeable incidence of pathogens on whole muscle beef and raise the importance of such contamination on product that may be mechanically tenderized. Levels of total aerobic plate count, total coliform count, and E. coli count did not (P > or = 0.05) appear to be associated with the presence of E. coli O157:H7 and Salmonella on fresh beef cuts. E. O157:H7 was exclusively isolated from cuts derived from the sirloin area of the carcass. Salmonella was exclusively isolated from cuts derived from the chuck, rib, and loin areas of the carcass. Results of this study suggest that contamination of beef cuts may be influenced by the region of the carcass from which they are derived.     

Long Distance Enhancement of Nonlinear Optical Properties Using Low Concentration of Plasmonic Nanostructures in Dye Doped Monolithic Sol–Gel Materials

Monolithic sol–gel silica composites incorporating platinum‐based chromophores and various types of gold nanoparticles (AuNPs) are prepared and polished to high optical quality. Their photophysical properties are investigated. The glass materials show well‐defined localized surface plasmon resonance (SPR) absorbance from the visible to NIR. No redshifts of the AuNP plasmon absorption peaks due to the increase in nanoparticle doping concentration are observed in the glasses, proving that no or very small SPR coupling effects occur between the AuNPs. At 600 nm excitation, but not at 532 nm, the AuNPs improve the nonlinear absorption performance of glasses codoped with 50 × 10^?3 m of a Pt‐acetylide chromophore. The glasses doped with lower concentrations of AuNPs (2–5 μm average distance) and 50 × 10^?3 m in chromophore, show a marked improvement in nonlinear absorption, with no or only small improvement for the more highly AuNP doped glasses. This study shows the importance of excitation wavelength and nanoparticle concentration for composite systems employing AuNPs to improve two‐photon absorption of chromophores.     

Electrical characterization of poly(amide-imide) for application in organic field effect devices

The admittance spectra and current–voltage (I–V) characteristics are reported of metal–insulator–metal (MIM) and metal–insulator–semiconductor (MIS) capacitors employing cross-linked poly(amide–imide) (c-PAI) as the insulator and poly(3-hexylthiophene) (P3HT) as the active semiconductor. The capacitance of the MIM devices are constant in the frequency range from 10 Hz to 100 kHz, with tan δ values as low as 7 × 10⁻³ over most of the range. Except at the lowest voltages, the I–V characteristics are well-described by the Schottky equation for thermal emission of electrons from the electrodes into the insulator. The admittance spectra of the MIS devices displayed a classic Maxwell–Wagner frequency response from which the transverse bulk hole mobility was estimated to be ∼2 × 10⁻⁵ cm² V⁻¹s⁻¹ or ∼5 × 10⁻⁸ cm² V⁻¹s⁻¹ depending on whether or not the surface of the insulator had been treated with hexamethyldisilazane (HMDS) prior to deposition of the P3HT. From the maximum loss observed in admittance-voltage plots, the interface trap density was estimated to be ∼5 × 10¹⁰ cm⁻² eV⁻¹ or ∼9 × 10¹⁰ cm⁻² eV⁻¹ again depending whether or not the insulator was treated with HMDS. We conclude, therefore, that HMDS plays a useful role in promoting order in the P3HT film as well as reducing the density of interface trap states. Although interposing the P3HT layer between the insulator and the gold electrode degrades the insulating properties of the c-PAI, nevertheless, they remain sufficiently good for use in organic electronic devices.     

Parallel discovery of network motifs

Many natural structures can be naturally represented by complex networks. Discovering network motifs, which are overrepresented patterns of inter-connections, is a computationally hard task related to graph isomorphism. Sequential methods are hindered by an exponential execution time growth when we increase the size of motifs and networks. In this article we study the opportunities for parallelism in existing methods and propose new parallel strategies that adapt and extend one of the most efficient serial methods known from the Fanmod tool. We propose both a master–worker strategy and one with distributed control, in which we employ a randomized receiver initiated methodology capable of providing dynamic load balancing during the whole computation process. Our strategies are capable of dealing both with exact and approximate network motif discovery. We implement and apply our algorithms to a set of representative networks and examine their scalability up to 128 processing cores. We obtain almost linear speedups, showcasing the efficiency of our proposed approach and are able to reach motif sizes that were not previously achievable using conventional serial algorithms.     

Interface Characterization in Fiber-Reinforced Polymer–Matrix Composites

A novel methodology is presented and applied to measure the shear interface strength of fiber-reinforced polymers. The strategy is based in fiber push-in tests carried out on the central fiber of highly-packed fiber clusters with hexagonal symmetry, and it is supported by a detailed finite element analysis of the push-in test to account for the influence of hygrothermal residual stresses, fiber constraint and fiber anisotropy on the interface strength. Examples of application are presented to determine the shear interface strength in carbon and glass fiber composites reinforced with either thermoset or thermoplastic matrices. In addition, the influence of the environment (either dry or wet conditions) on the interface strength in C/epoxy composites is demonstrated.     

Crystallization of porcine insulin with carbon dioxide as acidifying agent

Recent studies on the use of volatile electrolytes such as CO₂ in protein precipitation showed that these agents are a promising alternative to the conventional acids. This use of volatile electrolytes prevents protein denaturation due to local pH extremes, and saline effluent generation is greatly reduced, as the volatile electrolyte may be separated and recovered from solution just by pressure release. In this work, insulin was successfully crystallized in the presence of zinc using CO₂ as acidifying agent. The crystals obtained were rhombohedral, a common shape for porcine insulin crystals that contain zinc in their structure, and their average size varied with the mixing applied.     

Multi‐criteria algorithm‐based methodology used to select suitable domes for compressed air energy storage

Storing energy allows both the efficiency and availability of renewable energy to be increased, thus dissociating actual from expected generation and from consumption demands. Compressed air energy storage (hereinafter ‘CAES’) enables the efficient and cost‐effective storage of large amounts of energy, achieving a capacity of over 100 MWh. There are several geological structures that can be used as CAES, among which the use and construction of salt domes are particularly noteworthy. However, there is a high exploration risk associated with subsurface exploration. To this end, it is advisable to establish a detailed schedule to select and characterize structures, with the purpose of minimizing the aforementioned risk. Multi‐criteria algorithms can be used to establish a hierarchy of the alternatives and to identify the structures with the greatest potential with an objective approach. The analytic hierarchy process method is used in this paper as the selection algorithm, which is based on identifying and assessing criteria and weighting each criterion. In accordance with the analytic hierarchy process method, the goal was divided into a series of different level criteria, defining a breakdown structure of the problem to select salt domes. This paper defines a structure hierarchization method that allows the objective establishment of the areas with the highest potential for CAES, considering both technical and socioeconomic factors. Therefore, a supporting decision‐making method may be established to reduce the exploration risk associated with underground structures. Copyright © 2017 John Wiley & Sons, Ltd.