Thermal Stability of Polymer Additives: Comparison of Decomposition Models Including Oxidative Pyrolysis

The thermo‐oxidative stability of widely used polymer additives has been investigated. A comparative analytical approach with classic and innovative decomposition models for polymer additives was conducted and the results supported using quantum‐chemical calculations. Unique pyrolysis products of the analytes were compiled utilizing pyrolysis online coupled to gas chromatography followed by mass spectrometric detection (Pyr‐GC–MS). The pyrolysis was either performed under inert conditions or in an oxygen‐containing atmosphere. Squalane was applied as polymer‐mimicking liquid next to low density polyethylene (LDPE) and polyamide 6 (PA 6) as matrices for 10 selected additives. The additives included in this study range from antioxidants and plasticizers to processing aids. These were selected to address a range of application in consumer products and to cover different chemical classes. The toxicological relevance of additives and potential breakdown products was considered. Consequently, degradation of sterically hindered antioxidants, diarylamines, and a trimellitic acid derivative was investigated. The findings were used to predict the behavior of consumer products made of polymeric materials entailing additives. The level of Antioxidant 2246 [2‐tert‐butyl‐6‐[(3‐tert‐butyl‐2‐hydroxy‐5‐methylphenyl)methyl]‐4‐methylphenol] and one of its predicted decomposition products was determined in baby bottle nipples made of natural rubber [2‐tert‐butyl‐4‐methylphenol] utilizing the complementary technique of gas chromatography coupled to tandem mass spectrometry (GC–MS/MS). This study provides a comprehensive characterization of important polymer additives and enables the prioritization of degradation products for further risk assessment. J. VINYL ADDIT. TECHNOL., 25:E12–E27, 2019. © 2018 The Authors. Journal of Vinyl and Additive Technology published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineers     

Dense versus Sparse Approaches for Estimating the Fundamental Matrix

There are two main strategies for solving correspondence problems in computer vision: sparse local feature based approaches and dense global energy based methods. While sparse feature based methods are often used for estimating the fundamental matrix by matching a small set of sophistically optimised interest points, dense energy based methods mark the state of the art in optical flow computation. The goal of our paper is to show that this separation into different application domains is unnecessary and can be bridged in a natural way. As a first contribution we present a new application of dense optical flow for estimating the fundamental matrix. Comparing our results with those obtained by feature based techniques we identify cases in which dense methods have advantages over sparse approaches. Motivated by these promising results we propose, as a second contribution, a new variational model that recovers the fundamental matrix and the optical flow simultaneously as the minimisers of a single energy functional. In experiments we show that our coupled approach is able to further improve the estimates of both the fundamental matrix and the optical flow. Our results prove that dense variational methods can be a serious alternative even in classical application domains of sparse feature based approaches.     

Dual-Priority versus Background Scheduling: A Path-Wise Comparison

In this paper, two well-known scheduling policies for real-time systems, namely background scheduling (BS) and dual-priority (DP) are compared in terms of response times for soft real-time traffic (SRT). It is proved in the preemptive as well as in the non-preemptive case that, when the SRT traffic is FIFO, the DP policy always outperforms BS for all instances of SRT tasks. When the SRT traffic is not FIFO but if all tasks are of equal size then, in the non-preemptive case, the average response times is shown to be always better under DP than under BS. As a complementary result, some non-FIFO examples where BS behaves better than DP for some SRT tasks but also on the average of the SRT response times, are given. The proofs are based on a trajectorial method that may be used for comparing other scheduling policies.     

Heuristic Methods for Minimum-Cost Pipeline Network Design – a Node Valency Transfer Metaheuristic

Designing low-cost network layouts is an essential step in planning linked infrastructure. For the case of capacitated trees, such as oil or gas pipeline networks, the cost is usually a function of both pipeline diameter (i.e. ability to carry flow or transferred capacity) and pipeline length. Even for the case of incompressible, steady flow, minimizing cost becomes particularly difficult as network topology itself dictates local flow material balances, rendering the optimization space non-linear. The combinatorial nature of potential trees requires the use of graph optimization heuristics to achieve good solutions in reasonable time. In this work we perform a comparison of known literature network optimization heuristics and metaheuristics for finding minimum-cost capacitated trees without Steiner nodes, and propose novel algorithms, including a metaheuristic based on transferring edges of high valency nodes. Our metaheuristic achieves performance above similar algorithms studied, especially for larger graphs, usually producing a significantly higher proportion of optimal solutions, while remaining in line with time-complexity of algorithms found in the literature. Data points for graph node positions and capacities are first randomly generated, and secondly obtained from the German emissions trading CO₂ source registry. As political will for applications and storage for hard-to-abate industry CO₂ emissions is growing, efficient network design methods become relevant for new large-scale CO₂ pipeline networks.

     

Synthesis of Novel Niobium Aluminide-Based Composites

A reactive sintering process has been used to produce almost fully dense composites with interpenetrating networks of NbAl₃ and Al₂O₃. The process involves the reaction synthesis of niobium aluminides and Al₂O₃ from compacts of intensively milled aluminum and Nb₂O₅ powder mixtures. During carefully controlled heating under an inert atmosphere, the oxide reduction by aluminum to form niobium aluminides and Al₂O₃ proceeds at temperatures below the melting point of aluminum. At temperatures of >1000°C, the reaction-formed niobium aluminides and Al₂O₃ sinter. The present paper discusses processing parameters, such as attrition milling, the heating cycle, and the metal:ceramic ratio in the starting mixture, that control microstructure development and mechanical properties.     

Dominant Mechanisms that Shape the Airborne Particle Size and Composition Distribution in Central California

The size and composition of ambient airborne particulate matter is reported for winter conditions at five locations in (or near) the San Joaquin Valley in central California. Two distinct types of airborne particles were identified based on diurnal patterns and size distribution similarity: hygroscopic sulfate/ammonium/nitrate particles and less hygroscopic particles composed of mostly organic carbon with smaller amounts of elemental carbon. Daytime PM₁₀ concentrations for sulfate/ammonium/nitrate particles were measured to be 10.1 μ g m^?3, 28.3 μ g m^?3, and 52.8 μ g m^?3 at Sacramento, Modesto and Bakersfield, California, respectively. Nighttime concentrations were 10–30% lower, suggesting that these particles are dominated by secondary production. Simulation of the data with a box model suggests that these particles were formed by the condensation of ammonia and nitric acid onto background or primary sulfate particles. These hygroscopic particles had a mass distribution peak in the accumulation mode (0.56–1.0 μ m) at all times. Daytime PM₁₀ carbon particle concentrations were measured to be 9.5 μ g m^?3, 15.1 μ g m^?3, and 16.2 μ g m^?3 at Sacramento, Modesto, and Bakersfield, respectively. Corresponding nighttime concentrations were 200–300% higher, suggesting that these particles are dominated by primary emissions. The peak in the carbon particle mass distribution varied between 0.2–1.0 μ m. Carbon particles emitted directly from combustion sources typically have a mass distribution peak diameter between 0.1–0.32 μ m. Box model calculations suggest that the formation of secondary organic aerosol is negligible under cool winter conditions, and that the observed shift in the carbon particle mass distribution results from coagulation in the heavily polluted concentrations experienced during the current study. The analysis suggests that carbon particles and sulfate/ammonium/nitrate particles exist separately in the atmosphere of the San Joaquin Valley until coagulation mixes them in the accumulation mode.     

Microbial biofilm growth on irradiated, spent nuclear fuel cladding

A fundamental criticism regarding the potential for microbial influenced corrosion in spent nuclear fuel cladding or storage containers concerns whether the required microorganisms can, in fact, survive radiation fields inherent in these materials. This study was performed to unequivocally answer this critique by addressing the potential for biofilm formation, the precursor to microbial-influenced corrosion, in radiation fields representative of spent nuclear fuel storage environments. This study involved the formation of a microbial biofilm on irradiated spent nuclear fuel cladding within a hot cell environment. This was accomplished by introducing 22 species of bacteria, in nutrient-rich media, to test vessels containing irradiated cladding sections and that was then surrounded by radioactive source material. The overall dose rate exceeded 2 Gy/h gamma/beta radiation with the total dose received by some of the bacteria reaching 5 × 10³ Gy. This study provides evidence for the formation of biofilms on spent-fuel materials, and the implication of microbial influenced corrosion in the storage and permanent deposition of spent nuclear fuel in repository environments.     

Beer and wine consumers' perceptions of the nutritional value of alcoholic and nonalcoholic beverages

ABSTRACT:  In general beer has not been portrayed as part of a balanced diet. However, red wine has been promoted as a beneficial part of a nutritious diet. The evidence is that beer is at least the equal of wine from a nutritional perspective and in countering ailments such as coronary heart disease. This study used surveys to compare beer and wine consumers' perceptions of alcoholic and nonalcoholic beverages. The consumers ranked 7 beverages based upon perceived healthfulness both before and after they were exposed to nutritional information about the beverages. The ranked data were analyzed using analysis of variance. The variance due to the 3-way interaction of place of recruitment, beverage, and ranking was found to be significant at P < 0.05. There was no significant difference between genders. Overall, consumers of alcoholic beverages perceived red wine to be more healthful than the other 6 beverages, including beer and white wine. The perceived healthfulness of a beverage does not appear to be the main factor driving the choice of beverage. Nutritional information does impact consumers' perceptions of the healthfulness of beverages. Consumers who are predominately beer drinkers were more heavily influenced by nutritional information than consumers who were predominately wine drinkers.     

Variational optical flow computation in real time.

This paper investigates the usefulness of bidirectional multigrid methods for variational optical flow computations. Although these numerical schemes are among the fastest methods for solving equation systems, they are rarely applied in the field of computer vision. We demonstrate how to employ those numerical methods for the treatment of variational optical flow formulations and show that the efficiency of this approach even allows for real-time performance on standard PCs. As a representative for variational optic flow methods, we consider the recently introduced combined local-global method. It can be considered as a noise-robust generalization of the Horn and Schunck technique. We present a decoupled, as well as a coupled, version of the classical Gauss-Seidel solver, and we develop several multgrid implementations based on a discretization coarse grid approximation. In contrast, with standard bidirectional multigrid algorithms, we take advantage of intergrid transfer operators that allow for nondyadic grid hierarchies. As a consequence, no restrictions concerning the image size or the number of traversed levels have to be imposed. In the experimental section, we juxtapose the developed multigrid schemes and demonstrate their superior performance when compared to unidirectional multgrid methods and nonhierachical solvers. For the well-known 316 x 252 Yosemite sequence, we succeeded in computing the complete set of dense flow fields in three quarters of a second on a 3.06-GHz Pentium4 PC. This corresponds to a frame rate of 18 flow fields per second which outperforms the widely-used Gauss-Seidel method by almost three orders of magnitude.