System architectures assessment based on network metrics

Characterising system architectures and describing a system’s properties using quantitative metrics is required for the comparison and evaluation of engineering systems. The aim of this article is to discuss the assessment of system architectures based on network metrics derived from literature. In this paper, network metrics such as interaction density, Newman modularity index (Q), centrality measures, cyclomatic number, and graph energy measure are included into a methodological approach for evaluating five hypothetical system architecture patterns: bus-modular, sequential, hierarchical, core-periphery and integral. Network and graph theory offer a conceptual approach to model and analyse engineering system architectures. The contribution of the article is a network metrics assessment founded on describing emergent system architecture properties as integrality, modularity, centrality, cyclicality and complexity for holistically assessing system architectures. The network metrics offer quantitative tools to gain valuable insights and can function as decision aid tools during the redesign and early development of engineering systems

Complex-to-Real Mapping for Polymer Field Theories

Polymer field theory is a valuable tool for studying the behavior of dense polymer systems at near-atomistic length scales. In its most successful form, it is a complex-valued, d+1–dimensional theory that can be studied using fully-fluctuating simulations or at the level of self-consistent field theory (SCFT). This theory requires calculations using fields that depend on d spatial variables as well as a contour variable indicating the position along the polymer chain. In principle, it can be reduced to a simpler, real-valued, d-dimensional theory that is more efficient to simulate numerically—a phase field model—but these are typically less accurate due to approximations invoked in their derivations. We introduce and refine a new method for constructing phase field models, phase field mapping, that systematically parametrizes an optimized phase field (OPF) model using the output of inexpensive SCFT simulations. We develop an OPF model for the diblock copolymer melt and characterize its performance in terms of speed, accuracy, and transferability. Then we modify and generalize the model to produce a weakly compressible model suitable for running simulations in confined templates. In bulk and in confinement, the OPF model is faster to simulate than SCFT and more accurate than other phase field models. With these advantages, the OPF model is a useful alternative to complex-valued field theories

Network-based metrics for assessment of naval distributed system architectures

The architecture of a system is generally established at the end of the conceptual design phase where sixty to eighty percent of the lifetime system costs are committed. The architecture influences the system’s complexity, integrality, modularity and robustness. However, such properties of system architecture are not typically analytically evaluated early on during the conceptual process. System architectures are defined using qualitative experience, and the early stage decisions are subject to the judgement of stakeholders. This article suggests a set of network-based metrics that can potentially function as early evaluation indicators to assess complexity, integrality, modularity and robustness of distributed system architectures during conceptual design. A new robustness metric is proposed that assesses the ability of architecture to support a level functional requirement of the system after a disruption. The new robustness metric is evaluated by an electrical simulation software (MATPOWER). A ship vulnerability assessment software (SURVIVE) was used to find potential disruptive events. Two technical case studies examining existing naval distributed system architectures are elaborated. Conclusions on the network modelling and metrics as early aids to assess system architectures and to choose among alternatives during the conceptual decision phase are presented

Characterisation of battered and breaded coatings for food systems

Texture perception is due to a foods structural and mechanical properties detected through our senses. The texture of deep-fried battered and breaded coatings are recognised for their crisp outer crust contrasting a tender core. Crispness is a textural parameter used to assess the quality and freshness of deep-fried goods, it is therefore a fundamental attribute. The ultimate goal of this research is to understand the main drivers of crispness, thereby allowing an understanding of how crispness can be controlled from a formulation perspective. The ability to manipulate crispness is advantageous for developing a product to suit a desired specification or market niche. The focus of this thesis is firstly directed towards gaining an understanding of the microstructure of deep-fried battered and breaded coatings. By characterising the microstructure of the entire coating, it was then possible to study the physical and mechanical properties and relate this to textural properties. The layers of a standard deep-fried coating consisted of predust flour, liquid batter layer followed by panko breadcrumbs. The breadcrumb layer is the first point of contact when biting and assessing texture, this initiated an incentive to investigate the effect of breadcrumb size on the physical and mechanical properties of the coating layer. Eight breadcrumb fractions were investigated for their effect on mechanical and physical properties of the deep-fried coating. Instrumental characterisation was carried out using X-ray MicroCT, texture analysis, acoustics, confocal microscopy, Cryo-SEM, moisture and oil quantification. This concept was further explored by carrying out sensory studies. This consisted of using a trained sensory panel to develop a tailored lexicon for descriptive profiling. Results showed a significant difference in physical and mechanical properties as well as sensory attributes when breadcrumb size varied. These structural parameters were correlated with sensory parameters to develop a predictive statistical model for crispness. By using both instrumental and sensory characterisation methods, this provided a full representation of the contributors to crispness. In the final chapter, consumer studies were carried out to understand consumer acceptance and preference. Cluster analysis confirmed that deep-fried battered and breaded coatings were grouping into three clusters (coarse, medium, fine). These clusters were based on dissimilarities instrumentally and sensorially. These three clusters of batter and breadcrumb coatings were carried forward for liking and acceptance testing. Consumers assessed these three samples on four hedonic and nine sensory attributes (9-point scale and JAR-scale). Penalty analysis confirmed significant mean drops within all three samples, highlighting which attributes can be focused on to improve overall hedonic score. Further cluster analysis confirmed consumers grouping into three clusters, each with a higher liking score for either coarse, medium or fine. Although crispness is a known important attribute for deep-fried coatings, results showed that when crispness is scored too high, overall liking score decreases. The results also highlight the microstructural differences in coatings that exceed the crispness limit. These microstructural properties explain why quality may be perceived as lower. It is also a combination of texture, flavour and appearance related attribute that significantly reduce overall liking score

Interactions of HMGB Proteins with the Genome and the Impact on Disease

High Mobility Group Box (HMGB) proteins are small architectural DNA binding proteins that regulate multiple genomic processes such as DNA damage repair, nucleosome sliding, telomere homeostasis, and transcription. In doing so they control both normal cellular functions and impact a myriad of disease states, including cancers and autoimmune diseases. HMGB proteins bind to DNA and nucleosomes to modulate the local chromatin environment, which facilitates the binding of regulatory protein factors to the genome and modulates higher order chromosomal organization. Numerous studies over the years have characterized the structure and function of interactions between HMGB proteins and DNA, both biochemically and inside cells, providing valuable mechanistic insight as well as evidence these interactions influence pathological processes. This review highlights recent studies supporting the roles of HMGB1 and HMGB2 in global organization of the genome, as well as roles in transcriptional regulation and telomere maintenance via interactions with G-quadruplex structures. Moreover, emerging models for how HMGB proteins function as RNA binding proteins are presented. Nuclear HMGB proteins have broad regulatory potential to impact numerous aspects of cellular metabolism in normal and disease states. &nbsp;</p