Binding of an RNA trafficking response element to heterogeneous nuclear ribonucleoproteins A1 and A2

Heterogeneous nuclear ribonucleoprotein (hnRNP) A2 binds a 21-nucleotide myelin basic protein mRNA response element, the A2RE, and A2RE-like sequences in other localized mRNAs, and is a trans-acting factor in oligodendrocyte cytoplasmic RNA trafficking. Recombinant human hnRNPs A1 and A2 were used in a biosensor to explore interactions with A2RE and the cognate oligodeoxyribonucleotide. Both proteins have a single site that bound oligonucleotides with markedly different sequences but did not bind in the presence of heparin. Both also possess a second, specific site that bound only A2RE and was unaffected by heparin, hnRNP A2 bound A2RE in the latter site with a K-d near 50 nM, whereas the K-d for hnRNP A1 was above 10 muM. UV cross-linking assays led to a similar conclusion. Mutant A2RE sequences, that in earlier qualitative studies appeared not to bind hnRNP A2 or support RNA trafficking in oligodendrocytes, had dissociation constants above 5 muM for this protein. The two concatenated RNA recognition motifs (RRMs), but not the individual RRMs, mimicked the binding behavior of hnRNP A2. These data highlight the specificity of the interaction of A2RE with these hnRNPs and suggest that the sequence-specific A2RE-binding site on hnRNP A2 is formed by both RRMs acting in cis.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

Interactions within heterogeneous systems of uncontrolled rectifiers for aircraft electrical power systems

There is an increase in the use of multi-pulse, rectifier-fed motor-drive equipment on board more-electric aircraft. Motor drives with feedback control appear as constant power loads to the rectifiers, which can cause instability of the DC filter capacitor voltage at the output of the rectifier. This problem can be exacerbated by interactions between rectifiers that share a common source impedance. In order that such a system can be analysed, there is a need for average, dynamic models of systems of rectifiers. In this study, an efficient, compact method for deriving the approximate, linear, large-signal, average models of two heterogeneous systems of rectifiers, which are fed from a common source impedance, is presented. The models give insight into significant interaction effects that occur between the converters, and that arise through the shared source impedance. First, a 6-pulse and doubly wound, transformer-fed, 12-pulse rectifier system is considered, followed by a 6-pulse and autotransformer-fed, 12-pulse rectifier system. The system models are validated against detailed simulations and laboratory prototypes, and key characteristics of the two system types are compared.

Compatibilisation of heterogeneous polymer blends by reactive processing

Functionalisation of polystyrene, PS, and ethylene-co-propylene-co-cyclopentadiene terpolymer, EPDM, with acrylic acid, AA, in a melt reactive processing procedure, in the presence of peroxide, trigonox 101, and coagents, Divinyl benzene, DVB (for PS), and trimethylolpropane triacrylate, TRIS (for EPDM), were successfully carried out. The level of grafting of the AA, as determined by infrared analysis, was significantly enhanced by the coagents. The grafting reaction of AA takes place simultaneously with homopolymerisation of the monomers, melt degradation and crosslinking reactions of the polymers. The extent of these competing reactions were inferred from measurements of melt flow index and insoluble gel content. Through a judicious use of both the peroxide and the coagent, particularly TRIS, unwanted side reactions were minimized. Five different processing methods were investigated for both functionalisation experiments; the direct addition of the pre-mixed polymer with peroxide and reactive modifiers was found to give optimum condition for grafting. The functionalised PS, F-PS, and EPDM, F-EPD, and maleinised polypropylene carrying a potential antioxidant, N-(4-anilinophenyl maleimide), F-PP were melt blended in binary mixtures of F-PS/F-EPD and F-PP/F-EPD in the presence (or absence) of organic diamines which act as an interlinking agent, e.g, Ethylene Diamine, EDA, and Hexamethylene Diamine, HEMDA. The presence of an interlinking agent, particularly HEMDA shows significant enhancement in the mechanical properties of the blend, suggesting that the copolymer formed has acted as compatibiliser to the otherwise incompatible polymer pairs. The functionalised and amidised blends, F and A-PSIEPDM (SPOI) and F and A-PPIEPDM (SPD2) were subsequently used as compatibiliser concentrates in the corresponding PSIEPDM and PPIEPDM blends containing various weight propotion of the homopolymers. The SPD1 caused general decreased in tensile strength, albeit increased in drop impact strength particularly in blend containing high PS content (80%). The SPD2 was particularly effective in enhancing impact strength in blends containing low weight ratio of PP (<70%). The SPD2 was also a good thermal antioxidant albeit less effective than commercial antioxidant. In all blends the evidence of compatibility was examined by scanning electron microscopy.

A projected process kriging algorithm for sensor networks with heterogeneous error characteristics

Large monitoring networks are becoming increasingly common and can generate large datasets from thousands to millions of observations in size, often with high temporal resolution. Processing large datasets using traditional geostatistical methods is prohibitively slow and in real world applications different types of sensor can be found across a monitoring network. Heterogeneities in the error characteristics of different sensors, both in terms of distribution and magnitude, presents problems for generating coherent maps. An assumption in traditional geostatistics is that observations are made directly of the underlying process being studied and that the observations are contaminated with Gaussian errors. Under this assumption, sub–optimal predictions will be obtained if the error characteristics of the sensor are effectively non–Gaussian. One method, model based geostatistics, assumes that a Gaussian process prior is imposed over the (latent) process being studied and that the sensor model forms part of the likelihood term. One problem with this type of approach is that the corresponding posterior distribution will be non–Gaussian and computationally demanding as Monte Carlo methods have to be used. An extension of a sequential, approximate Bayesian inference method enables observations with arbitrary likelihoods to be treated, in a projected process kriging framework which is less computationally intensive. The approach is illustrated using a simulated dataset with a range of sensor models and error characteristics.

Dynamic spectrum access in heterogeneous unlicensed wireless networks

Existing wireless systems are normally regulated by a fixed spectrum assignment strategy. This policy leads to an undesirable situation that some systems may only use the allocated spectrum to a limited extent while others have very serious spectrum insufficiency situation. Dynamic Spectrum Access (DSA) is emerging as a promising technology to address this issue such that the unused licensed spectrum can be opportunistically accessed by the unlicensed users. To enable DSA, the unlicensed user shall have the capability of detecting the unoccupied spectrum, controlling its spectrum access in an adaptive manner, and coexisting with other unlicensed users automatically. In this article, we propose a radio system Transmission Opportunity-based spectrum access control protocol with the aim to improve spectrum access fairness and ensure safe coexistence of multiple heterogeneous unlicensed radio systems. In the scheme, multiple radio systems will coexist and dynamically use available free spectrum without interfering with licensed users. Simulation is carried out to evaluate the performance of the proposed scheme with respect to spectrum utilisation, fairness and scalability. Comparing with the existed studies, our strategy is able to achieve higher scalability and controllability without degrading spectrum utilisation and fairness performance.

Fluctuation-induced traffic congestion in heterogeneous networks

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analyzing network failures caused by hardware faults or overload, where the network reaction was modeled as rerouting of traffic away from failed or congested elements. Here we model another type of the network reaction to congestion - a sharp reduction of the input traffic rate through congested routes which occurs on much shorter time scales. We consider the onset of congestion in the Internet where local mismatch between demand and capacity results in traffic losses and show that it can be described as a phase transition characterized by strong non-Gaussian loss fluctuations at a mesoscopic time scale. The fluctuations, caused by noise in input traffic, are exacerbated by the heterogeneous nature of the network manifested in a scale-free load distribution. They result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © Copyright EPLA, 2012.