Nonlinear analysis for the pre- and post-yield behaviour of a composite structure with the refined plastic hinge approach

The computational technique of the full ranges of the second-order inelastic behaviour evaluation of steel-concrete composite structure is not always sought forgivingly, and therefore it hinders the development and application of the performance-based design approach for the composite structure. To this end, this paper addresses of the advanced computational technique of the higher-order element with the refined plastic hinges to capture the all-ranges behaviour of an entire steel-concrete composite structure. Moreover, this paper presents the efficient and economical cross-section analysis to evaluate the element section capacity of the non-uniform and arbitrary composite section subjected to the axial and bending interaction. Based on the same single algorithm, it can accurately and effectively evaluate nearly continuous interaction capacity curve from decompression to pure bending technically, which is the important capacity range but highly nonlinear. Hence, this cross-section analysis provides the simple but unique algorithm for the design approach. In summary, the present nonlinear computational technique can simulate both material and geometric nonlinearities of the composite structure in the accurate, efficient and reliable fashion, including partial shear connection and gradual yielding at pre-yield stage, plasticity and strain-hardening effect due to axial and bending interaction at post-yield stage, loading redistribution, second-order P-δ and P-Δ effect, and also the stiffness and strength deterioration. And because of its reliable and accurate behavioural evaluation, the present technique can be extended for the design of the high-strength composite structure and potentially for the fibre-reinforced concrete structure.

Steel–concrete–steel sandwich system in Arctic offshore structure: Materials, experiments, and design

The gravity based structure (GBS) with external Steel–Concrete–Steel (SCS) sandwich ice-resistant wall has been developed for the Arctic oil and gas drilling. This paper firstly reported the experimental studies on the mechanical properties of steel and concretes under Arctic low temperature. With the test data, design equations were developed to incorporate the influences of the low temperature on these mechanical properties. Two types of Arctic GBS structure with flower-conical SCS sandwich shell type and plate type of ice-resistant wall have been developed for the Arctic offshore structure. Besides the studies on the materials, two SCS sandwich prototype shells and plates were, respectively, prepared and tested under patch loading that simulated the localized ice-contact pressure. The structural behaviors of the SCS sandwich structure under patch loading were reported and discussions were made on the influences of different parameters on the structural behavior of the structure. Analytical models were developed to predict the punching shear resistances of the SCS sandwich structure through modifying the code provisions. The accuracies of the developed analytical models were checked through validations against 27 tests in the literature. Corresponding design procedures on resistances of SCS sandwich structure were recommended based on these discussions and validations.

Residential tariff structure and battery energy storage impact in queensland LV network

Distributed renewable energy has become a significant contender in the supply of power in the distribution network in Queensland and throughout the world. As the cost of battery storage falls, distribution utilities turn their attention to the impacts of battery storage and other storage technologies on the low voltage (LV) network. With access to detailed residential energy usage data, Energex's available residential tariffs are investigated for their effectiveness in providing customers with financial incentives to move to Time-of Use based tariffs and to reward use of battery storage.

The study of genetic diversity and population structure of the Korean fleshy shrimp, Fenneropenaeus chinensis, using newly developed microsatellite markers

The fleshy shrimp, Fenneropenaeus chinensis, is the family of Penaeidae and one of the most economically important marine culture species in Korea. However, its genetic characteristics have never been studied. In this study, a total of 240 wild F. chinensis individuals were collected from four locations as follows: Narodo (NRD, n = 60), Beopseongpo (BSP, n = 60), Chaesukpo (CSP, n = 60), and Cheonsuman (CSM, n = 60). Genetic variability and the relationships among four wild F. chinensis populations were analyzed using 13 newly developed microsatellite loci. Relatively high levels of genetic variability (mean allelic richness = 16.87; mean heterozygosity = 0.845) were found among localities. Among the 52 population loci, 13 showed significant deviation from the Hardy–Weinberg equilibrium. Neighbor-joining, principal coordinate, and molecular variance analyses revealed the presence of three subpopulations (NRD, CSM, BSP and CSP), which was consistent with clustering based on genetic distance. The mean observed heterozygosity values of the NRD, CSM, BSP, and CSP populations were 0.724, 0.821, 0.814, and 0.785 over all loci, respectively. These genetic variability and differentiation results of the four wild populations can be applied for future genetic improvement using selective breeding and to design suitable management guidelines for Korean F. chinensis culture.

The Feeding Practices and Structure Questionnaire (FPSQ-28): A parsimonious version validated for longitudinal use from 2-5 years

Prospective studies and intervention evaluations that examine change over time assume that measurement tools measure the same construct at each occasion. In the area of parent-child feeding practices, longitudinal measurement properties of the questionnaires used are rarely verified. To ascertain that measured change in feeding practices reflects true change rather than change in the assessment, structure, or conceptualisation of the constructs over time, this study examined longitudinal measurement invariance of the Feeding Practices and Structure Questionnaire (FPSQ) subscales (9 constructs; 40 items) across 3 time points. Mothers participating in the NOURISH trial reported their feeding practices when children were aged 2, 3.7, and 5 years (N = 404). Confirmatory Factor Analysis (CFA) within a structural equation modelling framework was used. Comparisons of initial cross-sectional models followed by longitudinal modelling of subscales, resulted in the removal of 12 items, including two redundant or poorly performing subscales. The resulting 28-item FPSQ-28 comprised 7 multi-item subscales: Reward for Behaviour, Reward for Eating, Persuasive Feeding, Overt Restriction, Covert Restriction, Structured Meal Setting and Structured Meal Timing. All subscales showed good fit over 3 time points and each displayed at least partial scalar (thresholds equal) longitudinal measurement invariance. We recommend the use of a separate single item indicator to assess the family meal setting. This is the first study to examine longitudinal measurement invariance in a feeding practices questionnaire. Invariance was established, indicating that the subscales of the shortened FPSQ-28 can be used with mothers to validly assess change in 7 feeding constructs in samples of children aged 2-5 years of age.

Higher-resolution structure of the human insulin receptor ectodomain: Multi-modal inclusion of the insert domain

Insulin receptor (IR) signaling is critical to controlling nutrient uptake and metabolism. However, only a low-resolution (3.8 Å) structure currently exists for the IR ectodomain, with some segments ill-defined or unmodeled due to disorder. Here, we revise this structure using new diffraction data to 3.3 Å resolution that allow improved modeling of the N-linked glycans, the first and third fibronectin type III domains, and the insert domain. A novel haptic interactive molecular dynamics strategy was used to aid fitting to low-resolution electron density maps. The resulting model provides a foundation for investigation of structural transitions in IR upon ligand binding.

The structure of glycosaminoglycans and their interactions with proteins

Glycosaminoglycans (GAGs) are important complex carbohydrates that participate in many biological processes through the regulation of their various protein partners. Biochemical, structural biology and molecular modelling approaches have assisted in understanding the molecular basis of such interactions, creating an opportunity to capitalize on the large structural diversity of GAGs in the discovery of new drugs. The complexity of GAG–protein interactions is in part due to the conformational flexibility and underlying sulphation patterns of GAGs, the role of metal ions and the effect of pH on the affinity of binding. Current understanding of the structure of GAGs and their interactions with proteins is here reviewed: the basic structures and functions of GAGs and their proteoglycans, their clinical significance, the three-dimensional features of GAGs, their interactions with proteins and the molecular modelling of heparin binding sites and GAG–protein interactions. This review focuses on some key aspects of GAG structure–function relationships using classical examples that illustrate the specificity of GAG–protein interactions, such as growth factors, anti-thrombin, cytokines and cell adhesion molecules. New approaches to the development of GAG mimetics as possible new glycotherapeutics are also briefly covered.

Computational methods for the prediction of the structure and interactions of coiled-coil peptides

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

Evaluating viewpoint entropy for ribbon representation of protein structure

While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon’s Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative su- perfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 molecular biology experts to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy. Our results show that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy is highly dependent on the complexity of the structure: while most participants agree on good viewpoints for small, non-globular structures with few secondary structure elements, viewpoint preference varies considerably for complex structures. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure.

The influence of impurities on calcium phosphate floc structure and size in sugar solutions

Settling, dewatering and filtration of flocs are important steps in industry to remove solids and improve subsequent processing. The influence of non-sucrose impurities (Ca2+, Mg2+, phosphate and aconitic acid) on calcium phosphate floc structure (scattering exponent, Sf), size and shape were examined in synthetic and authentic sugar juices using X-ray diffraction techniques. In synthetic juices, Sf decreases with increasing phosphate concentration to values where loosely bound and branched flocs are formed for effective trapping and removal of impurities. Although, Sf did not change with increasing aconitic acid concentration, the floc size significantly decreased reducing the ability of the flocs to remove impurities. In authentic juices, the flocs structures were marginally affected by increasing proportions of non-sucrose impurities. However, optical microscopy indicated the formation of well-formed macro-floc network structures in sugar cane juices containing lower proportions of non-sucrose impurities. These structures are better placed to remove suspended colloidal solids.

Dual yolk-shell structure of carbon and silica-coated silicon for high-performance lithium-ion batteries

Silicon batteries have attracted much attention in recent years due to their high theoretical capacity, although a rapid capacity fade is normally observed, attributed mainly to volume expansion during lithiation. Here, we report for the first time successful synthesis of Si/void/SiO2/void/C nanostructures. The synthesis strategy only involves selective etching of SiO2 in Si/SiO2/C structures with hydrofluoric acid solution. Compared with reported results, such novel structures include a hard SiO2-coated layer, a conductive carbon-coated layer, and two internal void spaces. In the structures, the carbon can enhance conductivity, the SiO2 layer has mechanically strong qualities, and the two internal void spaces can confine and accommodate volume expansion of silicon during lithiation. Therefore, these specially designed dual yolk-shell structures exhibit a stable and high capacity of 956 mA h g−1 after 430 cycles with capacity retention of 83%, while the capacity of Si/C core-shell structures rapidly decreases in the first ten cycles under the same experimental conditions. The novel dual yolk-shell structures developed for Si can also be extended to other battery materials that undergo large volume changes.

Recent progress on synthesis, multi-scale structure, and properties of Y-Si-O oxides

Yttrium silicates (Y-Si-O oxides), including Y2Si2O7, Y2SiO5, and Y4·67(SiO4)3O apatite, have attracted wide attentions from material scientists and engineers, because of their extensive polymorphisms and important roles as grain boundary phases in improving the high-temperature mechanical/thermal properties of Si3N4and SiC ceramics. Recent interest in these materials has been renewed by their potential applications as high-temperature structural ceramics, oxidation protective coatings, and environmental barrier coatings (EBCs). The salient properties of Y-Si-O oxides are strongly related to their unique chemical bonds and microstructure features. An in-depth understanding on the synthesis - multi-scale structure-property relationships of the Y-Si-O oxides will shine a light on their performance and potential applications. In this review, recent progress of the synthesis, multi-scale structures, and properties of the Y-Si-O oxides are summarised. First, various methods for the synthesis of Y-Si-O ceramics in the forms of powders, bulks, and thin films/coatings are reviewed. Then, the crystal structures, chemical bonds, and atomic microstructures of the polymorphs in the Y-Si-O system are summarised. The third section focuses on the properties of Y-Si-O oxides, involving the mechanical, thermal, dielectric, and tribological properties, their environmental stability, and their structure-property relationships. The outlook for potential applications of Y-Si-O oxides is also highlighted.

Stationary processes for object detection and non-rigid structure-from-motion

Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.