Knowledge based cloud FE simulation of sheet metal forming processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions

Profile-Based Optimal Matchings in the Student-Project Allocation Problem

In the Student/Project Allocation problem (spa) we seek to assign students to individual or group projects offered by lecturers. Students provide a list of projects they find acceptable in order of preference. Each student can be assigned to at most one project and there are constraints on the maximum number of students that can be assigned to each project and lecturer. We seek matchings of students to projects that are optimal with respect to profile, which is a vector whose rth component indicates how many students have their rth-choice project. We present an efficient algorithm for finding agreedy maximum matching in the spa context – this is a maximum matching whose profile is lexicographically maximum. We then show how to adapt this algorithm to find a generous maximum matching – this is a matching whose reverse profile is lexicographically minimum. Our algorithms involve finding optimal flows in networks. We demonstrate how this approach can allow for additional constraints, such as lecturer lower quotas, to be handled flexibly

Spectral weight transfer in a disorder-broadened Landau level

In the absence of disorder, the degeneracy of a Landau level (LL) is $N=BA/\phi_0$, where $B$ is the magnetic field, $A$ is the area of the sample and $\phi_0=h/e$ is the magnetic flux quantum. With disorder, localized states appear at the top and bottom of the broadened LL, while states in the center of the LL (the critical region) remain delocalized. This well-known phenomenology is sufficient to explain most aspects of the Integer Quantum Hall Effect (IQHE) [1]. One unnoticed issue is where the new states appear as the magnetic field is increased. Here we demonstrate that they appear predominantly inside the critical region. This leads to a certain ``spectral ordering'' of the localized states that explains the stripes observed in measurements of the local inverse compressibility [2-3], of two-terminal conductance [4], and of Hall and longitudinal resistances [5] without invoking interactions as done in previous work [6-8].Comment: 5 pages 3 figure

Influence of silk–silica fusion protein design on silica condensation in vitro and cellular calcification

Biomaterial design via genetic engineering can be utilized for the rational functionalization of proteins to promote biomaterials integration and tissue regeneration. Spider silk has been extensively studied for its biocompatibility, biodegradability and extraordinary material properties. As a protein-based biomaterial, recombinant DNA derived derivatives of spider silks have been modified with biomineralization domains which lead to silica deposition and potentially accelerated bone regeneration. However, the influence of the location of the R5 (SSKKSGSYSGSKGSKRRIL) silicifying domain fused with the spider silk protein sequence on biosilicification process remains to be determined. Here we designed two silk-R5 fusion proteins that differed in the location of the R5 peptide, C- vs. N-terminus, where the spider silk domain consisted of a 15mer repeat of a 33 amino acid consensus sequence of the major ampullate dragline Spidroin 1 from Nephila clavipes (SGRGGLGG QG AGAAAAAGGA GQGGYGGLGSQGT). The chemical, physical and silica deposition properties of these recombinant proteins were assessed and compared to a silk 15mer control without the R5 present. The location of the R5 peptide did not have significant effect on wettability and surface energies, while the C - terminal location of the R5 promoted more controlled silica precipitation, suggesting differences in protein folding and possibly different access to charged amino acids that drive the silicification process. Further, cell compatibility in vitro, as well as the ability to promote human bone marrow derived mesenchymal stem cells (hMSC) differentiation were demonstrated for both variants of the fusion proteins

Renoprotection by remote ischemic conditioning during elective coronary revascularization: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND: Remote ischemic conditioning (RIC) has been recognized an emerging non-invasive approach for preventing acute kidney injury (AKI) in patients undergoing either elective coronary artery bypass graft (CABG) surgery or percutaneous coronary intervention (PCI). On the other hand, accumulating evidence has indicated the involving role of pre-CABG contrast usage for coronary angiography in post-surgery AKI risk. Along with the shortening time delay of CABG after coronary angiography, and the prevalent hybrid coronary revascularization (HCR), the AKI prevention by RIC has faced challenges following coronary revascuralization. METHODS: Randomized controlled trials (RCTs) were searched from Pubmed, EMBase, and Cochrane library (until May 2016). The primary outcome was postoperative AKI. The second outcomes were included the requirement for renal replacement therapy (RRT), and in-hospital or 30-day mortality. RESULTS: Twenty eligible RCTs (CABG, 3357 patients; PCI, 1501 patients) were selected. RIC significantly halved the incidence of AKI following PCI when compared with controls [n=1501; odds ratio (OR)=0.51; 95% CI, 0.32 to 0.82; P=0.006; I(2)=29.6%]. However, RIC did not affect the incidence of AKI following CABG (n=1850; OR=0.94; 95% CI, 0.73 to 1.19; P=0.586; I(2)=12.4%). The requirement for RRT and in-hospital mortality was not affected by RIC in CABG (n=2049, OR=1.04, P=0.87; n=1920, OR=0.89, P=0.7; respectively). CONCLUSIONS: Our meta-analysis suggests that RIC for preventing AKI following CABG has faced with challenges in terms of AKI, the requirement for RRT, and mortality. However, RIC shows a renoprotective benefit for PCI. Hence, our findings may infer the preserved renal effects of RIC in CABG with preconditioning before the coronary angiography, or in HCR

Multiple dynamical time-scales in networks with hierarchically nested modular organization

Many natural and engineered complex networks have intricate mesoscopic organization, e.g., the clustering of the constituent nodes into several communities or modules. Often, such modularity is manifested at several different hierarchical levels, where the clusters defined at one level appear as elementary entities at the next higher level. Using a simple model of a hierarchical modular network, we show that such a topological structure gives rise to characteristic time-scale separation between dynamics occurring at different levels of the hierarchy. This generalizes our earlier result for simple modular networks, where fast intra-modular and slow inter-modular processes were clearly distinguished. Investigating the process of synchronization of oscillators in a hierarchical modular network, we show the existence of as many distinct time-scales as there are hierarchical levels in the system. This suggests a possible functional role of such mesoscopic organization principle in natural systems, viz., in the dynamical separation of events occurring at different spatial scales.Comment: 10 pages, 4 figure

Mapping Polarization Fields in Al0.85In0.15N/AlN/GaN Heterostructures

Extended abstract of a paper presented at Microscopy and Microanalysis 2009 in Richmond, Virginia, USA, July 26 - July 30, 200

Second-Order Assortative Mixing in Social Networks

In a social network, the number of links of a node, or node degree, is often assumed as a proxy for the node's importance or prominence within the network. It is known that social networks exhibit the (first-order) assortative mixing, i.e. if two nodes are connected, they tend to have similar node degrees, suggesting that people tend to mix with those of comparable prominence. In this paper, we report the second-order assortative mixing in social networks. If two nodes are connected, we measure the degree correlation between their most prominent neighbours, rather than between the two nodes themselves. We observe very strong second-order assortative mixing in social networks, often significantly stronger than the first-order assortative mixing. This suggests that if two people interact in a social network, then the importance of the most prominent person each knows is very likely to be the same. This is also true if we measure the average prominence of neighbours of the two people. This property is weaker or negative in non-social networks. We investigate a number of possible explanations for this property. However, none of them was found to provide an adequate explanation. We therefore conclude that second-order assortative mixing is a new property of social networks.Comment: Cite as: Zhou S., Cox I.J., Hansen L.K. (2017) Second-Order Assortative Mixing in Social Networks. In: Goncalves B., Menezes R., Sinatra R., Zlatic V. (eds) Complex Networks VIII. CompleNet 2017. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-54241-6_

A versatile cholera toxin conjugate for neuronal targeting and tracing

Tracing of neurons plays an essential role in elucidating neural networks in the brain and spinal cord. Cholera toxin B subunit (CTB) is already widely used as a tracer although its use is limited by the need for immunohistochemical detection. A new construct incorporating non-canonical azido amino acids (azido-CTB) offers a novel way to expand the range and flexibility of this neuronal tracer. Azido-CTB can be detected rapidly in vivo following intramuscular tongue injection by ‘click’ chemistry, eliminating the need for antibodies. Cadmium selenide/zinc sulfide (CdSe/ZnS) core/shell nanoparticles were attached to azido-CTB by strain-promoted alkyne–azide cycloaddition to make a nano-conjugate. Following tongue injections the complex was detected in vivo in the brainstem by light microscopy and electron microscopy via silver enhancement. This method does not require membrane permeabilization and so ultrastructure is maintained. Azido-CTB offers new possibilities to enhance the utility of CTB as a neuronal tracer and delivery vehicle by modification using ‘click’ chemistry