Low-Field Nuclear Magnetic Resonance Time Domain Characterization of Polyunsaturated Fatty Acid–Rich Linseed and Fish Oil Emulsions during Thermal Air Oxidation

Linseed contains high levels of polyunsaturated fatty acids (PUFA), such as α-linolenic acid (> 50% ALA-18:3), that are naturally protected against thermal oxidation by their encapsulation within linseed oil bodies (OB) by multiple components including antioxidant proteins and mucilage emulsifying agents. Linseed OB emulsions (LSE) can be produced by grinding linseed seeds, adding water, adjusting pH, and sonication. This is a process that can encapsulate externally added PUFA to minimize their thermal oxidation, as it does for the intrinsic ALA PUFA. Fish oil (FO) encapsulation into this LSE platform to form linseed fish oil emulsions (LSFE) offers the possibility of a nutritive delivery system of the biologically essential FO PUFA eicosapentaenoic acid and docosahexaenoic acid. In this study, ¹H low-field nuclear magnetic resonance (LF-NMR) is used to characterize LSE's and LSFE's chemical and structural properties as well as their stability and changes under thermal oxidation (55 °C for 96 hours). ¹H LF-NMR data processing was developed to generate one-dimensional (1D) T₁ (spin–lattice), 1D T₂ (spin–spin), and 2D (T₁ vs. T₂) relaxation time spectra that can characterize OB emulsions and monitor their time domain fingerprints (spectrum peaks) of chemical and structural changes during the oxidation process. The ¹H LF-NMR analysis were further supported and correlated with conventional peroxide value test, self-diffusion, droplet size distribution, zeta potential estimation of surface stability, and gas chromatography–mass spectrometry analysis of fatty acid profile changes under thermal oxidation conditions. The 1D and 2D LF-NMR relaxation spectra showed that the LSE and LSFE did not suffer intense oxidation process, due to PUFA assembly in OB oxidative protection. These results were further confirmed by the supportive analytical methodologies. The results of this study demonstrate the efficacy of ¹H LF-NMR methodology to monitor PUFA's rich oil and emulsion thermal oxidation.     

Extensions of principle component analysis with applications on vision based computing

This paper mainly focuses on the principle component analysis (PCA) and its applications on vision based computing. The underlying mechanism of PCA given and several significant factors, involved with subspace training are discussed theoretically in detail including principle components energy, residuals assessment, and decomposition computation. The typical extensions, including probabilistic PCA (PPCA), kernel PCA (KPCA), multi-dimensional PCA and robust PCA (RPCA), have been presented with critical analysis on both mechanisms and computations. Combining with the studies on, such as, image compression, visual tracking, image recognition and super-resolution image reconstruction, PCA and its extensions applied to computer vision are critically reviewed and evaluated on the targeted issues in each application as well as the role they played at specific tasks to the characteristics, cost and suitable situations of each PCA based vision processing technique.     

Upper Bounds on Number of Steals in Rooted Trees

Inspired by applications in parallel computing, we analyze the setting of work stealing in multithreaded computations. We obtain tight upper bounds on the number of steals when the computation can be modeled by rooted trees. In particular, we show that if the computation with n processors starts with one processor having a complete k-ary tree of height h (and the remaining n ? 1 processors having nothing), the maximum possible number of steals is \({\sum }_{i=1}^{n}(k-1)^{i}\binom {h}{i}\).     

A study of the graphical mediating representations used by collaborating authors

Abstract

Though they have access to sophisticated authoring support systems, many authors use conventional media for the earliest stages of generating and organising ideas. This paper gives an overview of a study of six pairs of collaborating authors who were videoed in aprewriting task and who also underwent a structured post-interview concerning their use of external representations in the study and in their everyday work. Pairs were studied so that the behaviour was more externalised, there were natural verbal protocols and these protocols could be interpreted by the interlocutor rather than by the researcher. The analysis focuses on the part that the mediating representations play in the cognitive task and in coordinating cooperative cognition. The properties of the marks produced and the affordances of conventional media are considered. The study is interpreted within a ‘shared cognitive’ framework which draws on insights from distributed cognition, socially shared cognition, situated action and most importantly from Soviet psychology. It is suggested that the mediating representations perform two important and highly related functions. First, they support ‘idea sketching’ which is a form of reflexive communication where the individual mediates her own creative cognition through external representations. Second, they mediate cooperative cognition, providing the common grounding necessary to coordinate shared thought.     

CO 2 and cost optimization of reinforced concrete footings using a hybrid big bang-big crunch algorithm

A procedure is developed for the design of reinforced concrete footings subjected to vertical, concentric column loads that satisfies both structural requirements and geotechnical limit states using a hybrid Big Bang-Big Crunch (BB-BC) algorithm. The objectives of the optimization are to minimize cost, CO $_{2}$ emissions, and the weighted aggregate of cost and CO $_{2}$ . Cost is based on the materials and labor required for the construction of reinforced concrete footings and CO $_{2}$ emissions are associated with the extraction and transportation of raw materials; processing, manufacturing, and fabrication of products; and the emissions of equipment involved in the construction process. The cost and CO $_{2}$ objective functions are based on weighted values and are subjected to bending moment, shear force, and reinforcing details specified by the American Concrete Institute (ACI 318-11), as well as soil bearing and displacement limits. Two sets of design examples are presented: low-cost and low-CO $_{2}$ emission designs based solely on geotechnical considerations; and designs that also satisfy the ACI 318-11 code for structural concrete. A multi-objective optimization is applied to cost and CO $_{2}$ emissions. Results are presented that demonstrate the effects of applied load, soil properties, allowable settlement, and concrete strength on designs.     

Automatic bandwidth selection for circular density estimation

Given angular data θ₁,…,θ_n∈[0,2π) a common objective is to estimate the density. In case that a kernel estimator is used, bandwidth selection is crucial to the performance. A “plug-in rule” for the bandwidth, which is based on the concentration of a reference density, namely, the von Mises distribution is obtained. It is seen that this is equivalent to the usual Euclidean plug-in rule in the case where the concentration becomes large. In case that the concentration parameter is unknown, alternative methods are explored which are intended to be robust to departures from the reference density. Simulations indicate that “wrapped estimators” can perform well in this context. The methods are applied to a real bivariate dataset concerning protein structure.     

Parallel and distributed simulation of sediment dynamics in shallow water using particle decomposition approach

This paper describes the parallel simulation of sediment dynamics in shallow water. By using a Lagrangian model, the problem is transformed to one in which a large number of independent particles must be tracked. This results in a technique that can be parallelised with high efficiency. We have developed a sediment transport model using three different sediment suspension methods. The first method uses a modified mean for the Poisson distribution function to determine the expected number of the suspended particles in each particular grid cell of the domain over all available processors. The second method determines the number of particles to suspend with the aid of the Poisson distribution function only in those grid cells which are assigned to that processor. The third method is based on the technique of using a synchronised pseudo-random-number generator to generate identical numbers of suspended particles in all valid grid cells for each processor. Parallel simulation experiments are performed in order to investigate the efficiency of these three methods. Also the parallel performance of the implementations is analysed. We conclude that the second method is the best method on distributed computing systems (e.g., a Beowulf cluster), whereas the third maintains the best load distribution.