Novel structured emulsions for delivering of food flavours

Flavour release from food is determined by the binding of flavours to other food ingredients and the partition of flavour molecules among different phases. Food emulsions are used as delivery systems for food flavours, and tailored structuring in emulsions provides novel means to better control flavour release. The current study investigated four structured oil-in-water emulsions with structuring in the oil phase, oil-water interface, and water phase. Oil phase structuring was achieved by the formation of monoglyceride (MG) liquid crystals in the oil droplets (MG structured emulsions). Structured interface was created by the adsorption of a whey protein isolate (WPI)-pectin double layer at the interface (multilayer emulsion). Water phase structured emulsions referred to emulsion filled protein gels (EFP gels), where emulsion droplets were embedded in WPI gel network, and emulsions with maltodextrins (MDs) of different dextrose-equivalent (DE) values. Flavour compounds with different physicochemical properties were added into the emulsions, and flavour release (release rate, headspace concentration and air-emulsion partition coefficient) was described by GC headspace analysis. Emulsion structures, including crystalline structure, particle size, emulsion stability, rheology, texture, and microstructures, were characterized using differential scanning calorimetry and X-ray diffraction, light scattering, multisample analytical centrifuge, rheometry, texture analysis, and confocal laser scanning microscopy, respectively. In MG structured emulsions, MG self-assembled into liquid crystalline structures and stable β-form crystals were formed after 3 days of storage at 25 °C. The inclusion of MG crystals allowed tween 20 stabilized emulsions to present viscoelastic properties, and it made WPI stabilized emulsions more sensitive to the change of pH and NaCl concentrations. Flavour compounds in MG structured emulsions had lower initial headspace concentration and air-emulsion partition coefficients than those in unstructured emulsions. Flavour release can be modulated by changing MG content, oil content and oil type. WPI-pectin multilayer emulsions were stable at pH 5.0, 4.0, and 3.0, but they presented extensive creaming when subjected to salt solutions with NaCl ≥ 150 mM and mixed with artificial salivas. Increase of pH from 5.0 to 7.0 resulted in higher headspace concentration but unchanged release rate, and increase of NaCl concentration led to increased headspace concentration and release rate. The study also showed that salivas could trigger higher release of hydrophobic flavours and lower release of hydrophilic flavours. In EFP gels, increases in protein content and oil content contributed to gels with higher storage modulus and force at breaking. Flavour compounds had significantly reduced release rates and air-emulsion partition coefficients in the gels than the corresponding ungelled emulsions, and the reduction was in line with the increase of protein content. Gels with stronger gel network but lower oil content were prepared, and lower or unaffected release rates of the flavours were observed. In emulsions containing maltodextrins, water was frozen at a much lower temperature, and emulsion stability was greatly improved when subjected to freeze-thawing. Among different MDs, MD DE 6 offered the emulsion the highest stability. Flavours had lower air-emulsion partition coefficients in the emulsions with MDs than those in the emulsion without MD. Moreover, the involvement of MDs in the emulsions allowed most flavours had similar release profiles before and after freeze-thaw treatment. The present study provided information about different structured emulsions as delivery systems for flavour compounds, and on how food structure can be designed to modulate flavour release, which could be helpful in the development of functional foods with improved flavour profile.

Toxicity of manufactured nano-ZnO to Lemna minor

The rapid development of nanotechnology has led to a rise in the large-scale production and commercial use of engineered nano-ZnO. Engineered/manufactured nano-ZnO are applied in a broad range of products such as drugs, paints, cosmetics, abrasive agents and insulators. This can result in the unintended exposure of human beings to nano-ZnO and will inevitably result in the release of nano-ZnO in to the environment. Thus, it is necessary to assess the risk of nano-ZnO to the environment. In this thesis the toxicity of nano-ZnO was analysed using the aquatic, primary producer lesser duckweed (Lemna minor), and the mechanism of toxicity was analysed. Both short-term (one week) and long-term (six weeks) toxicity of nano-ZnO (uncoated) were determined. Results show that the toxicity of nano-ZnO added to the aquatic growth medium increases with increasing concentration and that toxicity accumulates with exposure time. A study of nano-ZnO dissolution reveals that the main reason for nano-ZnO toxicity on Lemna minor is the release of Zn ions. Nano-ZnO dissolution is pH dependent, and toxicity matches the release of Zn2+. Functional coating materials are commonly added to nano-ZnO particles to improve specific industrial applications. To test if coating materials contribute to nano-ZnO toxicity on lesser duckweed, the effect of silane coupling agent (KH550) coated nano-ZnO on Lemma minor was investigated. Results show that coating can decrease the release of Zn ions, which reduces toxicity to Lemna minor, in contrast to uncoated particles. Another commonly hypothesized reason for nano-ZnO toxicity is the formation of Reactive Oxygen Species (ROS) on the particles surface. As part of this thesis, the ROS formation induced by nano-ZnO was studied. Results show that nano-ZnO catalyse ROS formation and this can negatively affect duckweed growth. In conclusion, this work has detailed potentially toxic effects of nano-ZnO on Lemna minor. This study has also provides references for future research, and informs regulatory testing for nanoparticle toxicity. Specifically, the outcomes of this study emphasize the importance of exposure time, environmental parameters and coating material when analysing NPs toxicity. Firstly, impacts of longer exposure time should be studied. Secondly, environmental parameters such as pH and medium-composition need to be considered when investigating NPs toxicity. Lastly, coating of NPs should always be considered in the context of NPs toxicity, and similar NPs with different coatings require separate toxicity tests.

Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics

We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process. We approach this problem through the Bayesian variable selection framework, where we assume that the covariates lie on an undirected graph and formulate an Ising prior on the model space for incorporating structural information. Certain computational and statistical problems arise that are unique to such high-dimensional, structured settings, the most interesting being the phenomenon of phase transitions. We propose theoretical and computational schemes to mitigate these problems. We illustrate our methods on two different graph structures: the linear chain and the regular graph of degree k. Finally, we use our methods to study a specific application in genomics: the modeling of transcription factor binding sites in DNA sequences. © 2010 American Statistical Association.

The impact of structured support groups for pregnant South African women recently diagnosed HIV positive.

The authors of this study evaluated a structured 10-session psychosocial support group intervention for newly HIV-diagnosed pregnant South African women. Participants were expected to display increases in HIV disclosure, self-esteem, active coping and positive social support, and decreases in depression, avoidant coping, and negative social support. Three hundred sixty-one pregnant HIV-infected women were recruited from four antenatal clinics in Tshwane townships from April 2005 to September 2006. Using a quasi-experimental design, assessments were conducted at baseline and two and eight months post-intervention. A series of random effects regression analyses were conducted, with the three assessment points treated as a random effect of time. At both follow-ups, the rate of disclosure in the intervention group was significantly higher than that of the comparison group (p<0.001). Compared to the comparison group at the first follow-up, the intervention group displayed higher levels of active coping (t=2.68, p<0.05) and lower levels of avoidant coping (t=-2.02, p<0.05), and those who attended at least half of the intervention sessions exhibited improved self-esteem (t=2.11, p<0.05). Group interventions tailored for newly HIV positive pregnant women, implemented in resource-limited settings, may accelerate the process of adjusting to one's HIV status, but may not have sustainable benefits over time.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Computer aided parallelisation tools (CAPTools) — conceptual overview and performance on the parallelisation of structured mesh codes

Computer Aided Parallelisation Tools (CAPTools) is a toolkit designed to automate as much as possible of the process of parallelising scalar FORTRAN 77 codes. The toolkit combines a very powerful dependence analysis together with user supplied knowledge to build an extremely comprehensive and accurate dependence graph. The initial version has been targeted at structured mesh computational mechanics codes (eg. heat transfer, Computational Fluid Dynamics (CFD)) and the associated simple mesh decomposition paradigm is utilised in the automatic code partition, execution control mask generation and communication call insertion. In this, the first of a series of papers [1–3] the authors discuss the parallelisations of a number of case study codes showing how the various component tools may be used to develop a highly efficient parallel implementation in a few hours or days. The details of the parallelisation of the TEAMKE1 CFD code are described together with the results of three other numerical codes. The resulting parallel implementations are then tested on workstation clusters using PVM and an i860-based parallel system showing efficiencies well over 80%.

Computational magnetohydrodynamics - Application

There are many processes, particularly in the nuclear and metals processing industries, where electromagnetic fields are used to influence the flow behaviour of a fluid. Procedures exploiting finite volume (FV) methods in both structured and unstructured meshes have recently been developed which enable this influence to be modelled in the context of conventional FV CFD codes. A range of problems have been tackled by the authors, including electromagnetic pumps and brakes, weirs and dams in steelmaking tundishes and interface effects in aluminium smelting cells. Two cases are presented here, which exemplify the application of the new procedures. The first case investigates the influence of electromagnetic fields on solidification front progression in a tin casting and the second case shows how the liquid metals free surface may be controlled through an externally imposed magnetic field in the semi-levitation casting process.

An automatable generic strategy for dynamic load balancing in parallel structured mesh CFD codes

Parallel computing is now widely used in numerical simulation, particularly for application codes based on finite difference and finite element methods. A popular and successful technique employed to parallelize such codes onto large distributed memory systems is to partition the mesh into sub-domains that are then allocated to processors. The code then executes in parallel, using the SPMD methodology, with message passing for inter-processor interactions. In order to improve the parallel efficiency of an imbalanced structured mesh CFD code, a new dynamic load balancing (DLB) strategy has been developed in which the processor partition range limits of just one of the partitioned dimensions uses non-coincidental limits, as opposed to coincidental limits. The ‘local’ partition limit change allows greater flexibility in obtaining a balanced load distribution, as the workload increase, or decrease, on a processor is no longer restricted by the ‘global’ (coincidental) limit change. The automatic implementation of this generic DLB strategy within an existing parallel code is presented in this chapter, along with some preliminary results.

Automatic and effective multi-dimensional parallelisation of structured mesh based codes

The most common parallelisation strategy for many Computational Mechanics (CM) (typified by Computational Fluid Dynamics (CFD) applications) which use structured meshes, involves a 1D partition based upon slabs of cells. However, many CFD codes employ pipeline operations in their solution procedure. For parallelised versions of such codes to scale well they must employ two (or more) dimensional partitions. This paper describes an algorithmic approach to the multi-dimensional mesh partitioning in code parallelisation, its implementation in a toolkit for almost automatically transforming scalar codes to parallel form, and its testing on a range of ‘real-world’ FORTRAN codes. The concept of multi-dimensional partitioning is straightforward, but non-trivial to represent as a sufficiently generic algorithm so that it can be embedded in a code transformation tool. The results of the tests on fine real-world codes demonstrate clear improvements in parallel performance and scalability (over a 1D partition). This is matched by a huge reduction in the time required to develop the parallel versions when hand coded – from weeks/months down to hours/days.

Modelling the nano-scale phenomena in condensed matter physics via computer-based numerical simulations

A review of the atomistic modelling of the behaviour of nano-scale structures and processes via molecular dynamics (MD) simulation method of a canonical ensemble is presented. Three areas of application in condensed matter physics are considered. We focus on the adhesive and indentation properties of the solid surfaces in nano-contacts, the nucleation and growth of nano-phase metallic and semi-conducting atomic and molecular films on supporting substrates, and the nano- and multi-scale crack propagation properties of metallic lattices. A set of simulations selected from these fields are discussed, together with a brief introduction to the methodology of the MD simulation. The pertinent inter-atomic potentials that model the energetics of the metallic and semi-conducting systems are also given.

Surface physics at the nano-scale via scanning probe microscopy and molecular dynamics simulations

Probe-based scanning microscopes, such as the STM and the AFM, are used to obtain the topographical and electronic structure maps of material surfaces, and to modify their morphologies on nanoscopic scales. They have generated new areas of research in condensed matter physics and materials science. We will review some examples from the fields of experimental nano-mechanics, nano-electronics and nano-magnetism. These now form the basis of the emerging field of Nano-technology. A parallel development has been brought about in the field of Computational Nano-science, using quantum-mechanical techniques and computer-based numerical modelling, such as the Molecular Dynamics (MD) simulation method. We will report on the simulation of nucleation and growth of nano-phase films on supporting substrates. Furthermore, a theoretical modelling of the formation of STM images of metallic clusters on metallic substrates will also be discussed within the non-equilibrium Keldysh Green function method to study the effects of coherent tunnelling through different atomic orbitals in a tip-sample geometry.

Magnetic modelling and magneto-hydro-dynamic simulations of an aluminium production electrolytic cell

A simulation of the motion of molten aluminium inside an electrolytic cell is presented. Since the driving term of the aluminium motion is the Lorentz (j × B) body force acting within the fluid,this problem involves the solution of the magneto-hydro-dynamic equations. Different solver modules for the magnetic field computation and for the fluid motion simulation are coupled together. The interactions of all these are presented and discussed.

Modeling the dynamics of electromagnetically agitated metallurgical flows: levitation, cold crucible, aluminium electrolysis, etc.

We present practical modelling techniques for electromagnetically agitated liquid metal flows involving dynamic change of the fluid volume and shape during melting and the free surface oscillation. Typically the electromagnetic field is strongly coupled to the free surface dynamics and the heat-mass transfer. Accurate pseudo-spectral code and the k-omega turbulence model modified for complex and transitional flows with free surfaces are used for these simulations. The considered examples include magnetic suspension melting, induction scull remelting (cold crucible), levitation and aluminium electrolysis cells. The process control and the energy savings issues are analysed.

Nonlinear MHD stability of aluminium reduction cells

An industrial electrolysis cell used to produce primary aluminium is sensitive to waves at the interface of liquid aluminium and electrolyte. The interface waves are similar to stratified sea layers [1], but the penetrating electric current and the associated magnetic field are intricately involved in the oscillation process, and the observed wave frequencies are shifted from the purely hydrodynamic ones [2]. The interface stability problem is of great practical importance because the electrolytic aluminium production is a major electrical energy consumer, and it is related to environmental pollution rate. The stability analysis was started in [3] and a short summary of the main developments is given in [2]. Important aspects of the multiple mode interaction have been introduced in [4], and a widely used linear friction law first applied in [5]. In [6] a systematic perturbation expansion is developed for the fluid dynamics and electric current problems permitting reduction of the three-dimensional problem to a two dimensional one. The procedure is more generally known as “shallow water approximation” which can be extended for the case of weakly non-linear and dispersive waves. The Boussinesq formulation permits to generalise the problem for non-unidirectionally propagating waves accounting for side walls and for a two fluid layer interface [1]. Attempts to extend the electrolytic cell wave modelling to the weakly nonlinear case have started in [7] where the basic equations are derived, including the nonlinearity and linear dispersion terms. An alternative approach for the nonlinear numerical simulation for an electrolysis cell wave evolution is attempted in [8 and references there], yet, omitting the dispersion terms and without a proper account for the dissipation, the model can predict unstable waves growth only. The present paper contains a generalisation of the previous non linear wave equations [7] by accounting for the turbulent horizontal circulation flows in the two fluid layers. The inclusion of the turbulence model is essential in order to explain the small amplitude self-sustained oscillations of the liquid metal surface observed in real cells, known as “MHD noise”. The fluid dynamic model is coupled to the extended electromagnetic simulation including not only the fluid layers, but the whole bus bar circuit and the ferromagnetic effects [9].