The influence of stabilizers on the fusion of rigid poly(vinyl chloride)

It is known that the fusion rate of rigid PVC in an extruder partly depends upon the lubricants that are used. In the present study it is shown that different stabilizers have a great influence upon the rate of fusion of rigid PVC. Results from extrusion experiments and the Brabender Plastograph strongly indicate that a correlation exists between rapid melting in the extruder and the melt viscosity-temperature relation of the polymer blend. The reason why certain stabilizers cause a more rapid fusion of the PVC is attributed to the chemical structure of the stabilizers.     

The diversity of systemic safety drift: the role of infrastructure in the railway sector

Cognition, Technology & Work - The paper is motivated by a concern that the “drift” metaphor may trigger stereotyped responses to accidents such as recurring requirements for better...     

The Effect of Stunning Methods and Season on Muscle Texture Hardness in Atlantic Salmon (Salmo salar L.)

Commercially collected records of Atlantic salmon (Salmo salar L.) muscle texture hardness were used to evaluate the effect of slaughter procedures and seasonality on texture quality. A database collected by Marine Harvest® contained flesh hardness records of Atlantic salmon slaughtered at processing plants in Norway from summer 2010 to summer 2011. The fish were slaughtered either by (1) percussion followed by automated bleeding (“Percussive”) or (2) live chilling with exposure to carbon dioxide (CO₂) followed by manual severing gill arches and bleeding (“CO₂”) or (3) live chilling with exposure to CO₂ followed by percussive stunning and at the end automated bleeding (“CO₂·percussive”). Hardness in salmon muscle cutlets was measured in Newtons (N) by Materials Testing Machine Zwick 500N. The hardness in salmon varied significantly over the study period (P < 0.05, mixed effect model) and showed the softest value of 21.2 (± 0.7) Newton (N) in summer 2011 and hardest 24.1 (± 0.2) N in autumn 2010. Slaughter procedures had a significant effect on salmon muscle hardness (P < 0.05, mixed effect model), where percussion followed by automated bleeding resulted in the hardest value (24.0 ± 0.4 N) as compared with CO₂ stunning (21.8 ± 0.2 N) and combination of CO₂ and percussive stunning (23.1 ± 0.15 N). CO₂ is suspected as a causal factor in accelerated postmortem softening of the salmon muscle.     

Extensions to “Output prediction under scarce data operation: control applications”

Albertos et al. (Automatica, 35 (1999) 1671–1681), proposed a simple and computationally cheap output estimation algorithm for systems where some output data is missing. In the original paper, a stability analysis of the algorithm is provided for the special case that every Nth sample of the output is observed. We here show how the stability can be analysed for arbitrary periodical missing data patterns.     

Second-order peak detection for multicomponent high-resolution LC/MS data

The first step when analyzing multicomponent LC/MS data from complex samples such as biofluid metabolic profiles is to separate the data into information and noise via, for example, peak detection. Due to the complex nature of this type of data, with problems such as alternating backgrounds and differing peak shapes, this can be a very complex task. This paper presents and evaluates a two-dimensional peak detection algorithm based on raw vector-represented LC/MS data. The algorithm exploits the fact that in high-resolution centroid data chromatographic peaks emerge flanked with data voids in the corresponding mass axis. According to the proposed method, only 4 per thousand of the total amount of data from a urine sample is defined as chromatographic peaks; however, 94% of the raw data variance is captured within these peaks. Compared to bucketed data, results show that essentially the same features that an experienced analyst would define as peaks can automatically be extracted with a minimum of noise and background. The method is simple and requires a priori knowledge of only the minimum chromatographic peak width-a system-dependent parameter that is easily assessed. Additional meta parameters are estimated from the data themselves. The result is well-defined chromatographic peaks that are consistently arranged in a matrix at their corresponding m/z values. In the context of automated analysis, the method thus provides an alternative to the traditional approach of bucketing the data followed by denoising and/or one-dimensional peak detection. The software implementation of the proposed algorithm is available at http://www.anchem.su.se/peakd as compiled code for Matlab.     

Continuum-molecular modelling of graphene

In the present contribution we address the modeling of graphene membranes using a hierarchical modeling strategy to bridge the scales required to describe and understand the material. Quantum Mechanical (QM) and optimized Molecular Mechanical (MM) models are used to describe details on the nanoscale, while a multiscale continuum mechanical method is used to model the graphene response at the device or micrometer scale. The complete method is obtained on the basis of the Cauchy Born Rule (CBR), where the continuum model is coupled to the atomic field via the CBR and a local discrete fluctuation field. The MM method, often used to model carbon structures, involves the Tersoff–Brenner (TB) potential; however, when applying this potential to graphene with standard parameters one obtains material stress behavior much weaker than experiments. On the other hand, the more fundamental Hartree Fock and Density Functional Theory (DFT) methods are computationally too expensive and very limited in terms of their applicability to model the geometric scale at the device level. In this contribution a simple calibration of some of the TB parameters is proposed in order to reproduce the results obtained from QM calculations. Subsequently, the fine-tuned TB-potential is used for the multiscale modeling of a nano indentation sample, where experimental data are available. Effects of the mechanical response after the calibration are demonstrated.     

Maximum likelihood estimation of Gaussian models with missing data—Eight equivalent formulations

In this paper we derive the maximum likelihood problem for missing data from a Gaussian model. We present in total eight different equivalent formulations of the resulting optimization problem, four out of which are nonlinear least squares formulations. Among these formulations are also formulations based on the expectation–maximization algorithm. Expressions for the derivatives needed in order to solve the optimization problems are presented. We also present numerical comparisons for two of the formulations for an ARMAX model.     

Computer-assisted simulation of high-voltage electron microscopy using serial images recorded by conventional transmission electron microscopy

Here we describe a computer-assisted method which, based on conventional transmission electron microscopy, renders simulated high-voltage electron micrographs. We perform arithmetic minimum filtering on stacks of aligned serial transmission electron microscopic images. In this way, the structural information of the separate images is fused into one compound image that highlights organization patterns otherwise easily overlooked or impossible to comprehend. Our method, like high-voltage electron microscopy, offers the possibility to build stereo-pairs for high-resolution three-dimensional analysis of tissue layers 1-2 microm thick. The use of background elimination and the development of a depth enhancement routine improved the three-dimensional effect and facilitated the analysis of the interior of objects. As an example, we use the method to display the distribution of axonal organelles at nodes of Ranvier and the shape and contents of a highly branched hippocampal dendritic spine.