41 resultados para Mixed network former effect
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Ethylene-propylene rubber (EPR) functionalised with glycidyl methacrylate (GMA) (f-EPR) during melt processing in the presence of a co-monomer, such as trimethylolpropane triacrylate (Tris), was used to promote compatibilisation in blends of polyethylene terephthalate (PET) and f-EPR, and their characteristics were compared with those of PET/f-EPR reactive blends in which the f-EPR was functionalised with GMA via a conventional free radical melt reaction (in the absence of a co-monomer). Binary blends of PETand f-EPR (with two types of f-EPR prepared either in presence or absence of the co-monomer) with various compositions (80/20, 60/40 and 50/50 w/w%) were prepared in an internal mixer. The blends were evaluated by their rheology (from changes in torque during melt processing and blending reflecting melt viscosity, and their melt flow rate), morphology scanning electron microscopy (SEM), dynamic mechanical properties (DMA), Fourier transform infrared (FTIR) analysis, and solubility (Molau) test. The reactive blends (PET/f-EPR) showed a marked increase in their melt viscosities in comparison with the corresponding physical (PET/EPR) blends (higher torque during melt blending), the extent of which depended on the amount of homopolymerised GMA (poly-GMA) present and the level of GMA grafting in the f-EPR. This increase was accounted for by, most probably, the occurrence of a reaction between the epoxy groups of GMA and the hydroxyl/carboxyl end groups of PET. Morphological examination by SEM showed a large improvement of phase dispersion, indicating reduced interfacial tension and compatibilisation, in both reactive blends, but with the Tris-GMA-based blends showing an even finer morphology (these blends are characterised by absence of poly-GMA and presence of higher level of grafted GMA in its f-EPR component by comparison to the conventional GMA-based blends). Examination of the DMA for the reactive blends at different compositions showed that in both cases there was a smaller separation between the glass transition temperatures compared to their position in the corresponding physical blends, which pointed to some interaction or chemical reaction between f-EPR and PET. The DMA results also showed that the shifts in the Tgs of the Tris-GMA-based blends were slightly higher than for the conventional GMA-blends. However, the overall tendency of the Tgs to approach each other in each case was found not to be significantly different (e.g. in a 60/40 ratio the former blend shifted by up to 4.5 °C in each direction whereas in the latter blend the shifts were about 3 °C). These results would suggest that in these blends the SEM and DMA analyses are probing uncorrelatable morphological details. The evidence for the formation of in situ graft copolymer between the f-EPR and PET during reactive blending was clearly illustrated from analysis by FTIR of the separated phases from the Tris-GMA-based reactive blends, and the positive Molau test pointed out to graft copolymerisation in the interface. A mechanism for the formation of the interfacial reaction during the reactive blending process is proposed.
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This paper models how the structure and function of a network of firms affects their aggregate innovativeness. Each firm has the potential to innovate, either from in-house R&D or from innovation spillovers from neighboring firms. The nature of innovation spillovers depends upon network density, the commonality of knowledge between firms, and the learning capability of firms. Innovation spillovers are modelled in detail using ideas from organizational theory. Two main results emerge: (i) the marginal effect on innovativeness of spillover intensity is non-monotonic, and (ii) network density can affect innovativeness but only when there are heterogeneous firms.
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High strength low alloy steels have been shown to be adversely affected by the existence of regions of poor impact toughness within the heat affected zone (HAZ) produced during multipass welding. One of these regions is the intercritically reheated coarse grained HAZ or intercritical zone. Since this region is generally narrow and discontinuous, of the order of 0.5 mm in width, weld simulators are often employed to produce a larger volume of uniform microstructure suitable for toughness assessment. The steel usedfor this study was a commercial quenched and tempered steel of 450 MN m -2 yield strength. Specimen blanks were subjected to a simulated welding cycle to produce a coarse grained structure of upper bainite during the first thermal cycle, followed by a second thermal cycle where the peak temperature T p2 was controlled. Charpy tests carried out for T p2 values in the range 650-850°C showed low toughness for T p2 values between 760 and 790°C, in the intercritical regime. Microstructural investigation of the development of grain boundary martensite-retained austenite (MA) phase has been coupled with image analysis to measure the volume fraction of MAformed. Most of the MA constituent appears at the prior austenite grain boundaries during intercritical heating, resulting in a 'necklace' appearance. For values of T p2 greater than 790°C the necklace appearance is lost and the second phase areas are observed throughout the structure. Concurrent with this is the development of the fine grained, predominantly ferritic structure that is associated with the improvement in toughness. At this stage the microstructure is transforming from the intercritical regime structure to the supercritically reheated coarse grained HAZ structure. The toughness improvement occurs even though the MA phase is still present, suggesting that the embrittlement is associated with the presence of a connected grain boundary network of the MA phase. The nature of the second phase particles can be controlled by the cooling rate during the second cycle and variesfrom MA phase at high cooling rates to a pearlitic structure at low cooling rates. The lowest toughness of the intercritical zone is observed only when MA phase is present. The reason suggested for this is that only the MA particles debond readily, a number of debonded particles in close proximity providing sufficient stress concentration to initiate local cleavage. © 1993 The Institute of Materials.
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Activated sludge basins (ASBs) are a key-step in wastewater treatment processes that are used to eliminate biodegradable pollution from the water discharged to the natural environment. Bacteria found in the activated sludge consume and assimilate nutrients such as carbon, nitrogen and phosphorous under specific environmental conditions. However, applying the appropriate agitation and aeration regimes to supply the environmental conditions to promote the growth of the bacteria is not easy. The agitation and aeration regimes that are applied to activated sludge basins have a strong influence on the efficacy of wastewater treatment processes. The major aims of agitation by submersible mixers are to improve the contact between biomass and wastewater and the prevention of biomass settling. They induce a horizontal flow in the oxidation ditch, which can be quantified by the mean horizontal velocity. Mean values of 0.3-0.35 m s-1 are recommended as a design criteria to ensure best conditions for mixing and aeration (Da Silva, 1994). To give circulation velocities of this order of magnitude, the positioning and types of mixers are chosen from the plant constructors' experience and the suppliers' data for the impellers. Some case studies of existing plants have shown that measured velocities were not in the range that was specified in the plant design. This illustrates that there is still a need for design and diagnosis approach to improve process reliability by eliminating or reducing the number of short circuits, dead zones, zones of inefficient mixing and poor aeration. The objective of the aeration is to facilitate the quick degradation of pollutants by bacterial growth. To achieve these objectives a wastewater treatment plant must be adequately aerated; thus resulting in 60-80% of all energetic consummation being dedicated to the aeration alone (Juspin and Vasel, 2000). An earlier study (Gillot et al., 1997) has illustrated the influence that hydrodynamics have on the aeration performance as measure by the oxygen transfer coefficient. Therefore, optimising the agitation and aeration systems can enhance the oxygen transfer coefficient and consequently reduce the operating costs of the wastewater treatment plant. It is critically important to correctly estimate the mass transfer coefficient as any errors could result in the simulations of biological activity not being physically representative. Therefore, the transfer process was rigorously examined in several different types of process equipment to determine the impact that different hydrodynamic regimes and liquid-side film transfer coefficients have on the gas phase and the mass transfer of oxygen. To model the biological activity occurring in ASBs, several generic biochemical reaction models have been developed to characterise different biochemical reaction processes that are known as Activated Sludge Models, ASM (Henze et al., 2000). The ASM1 protocol was selected to characterise the impact of aeration on the bacteria consuming and assimilating ammonia and nitrate in the wastewater. However, one drawback of ASM protocols is that the hydrodynamics are assumed to be uniform by the use of perfectly mixed, plug flow reactors or as a number of perfectly mixed reactors in series. This makes it very difficult to identify the influence of mixing and aeration on oxygen mass transfer and biological activity. Therefore, to account for the impact of local gas-liquid mixing regime on the biochemical activity Computational Fluid Dynamics (CFD) was used by applying the individual ASM1 reaction equations as the source terms to a number of scalar equations. Thus, the application of ASM1 to CFD (FLUENT) enabled the investigation of the oxygen transfer efficiency and the carbon & nitrogen biological removal in pilot (7.5 cubic metres) and plant scale (6000 cubic metres) ASBs. Both studies have been used to validate the effect that the hydrodynamic regime has on oxygen mass transfer (the circulation velocity and mass transfer coefficient) and the effect that this had on the biological activity on pollutants such as ammonia and nitrate (Cartland Glover et al., 2005). The work presented here is one part to of an overall approach for improving the understanding of ASBs and the impact that they have in terms of the hydraulic and biological performance on the overall wastewater treatment process. References CARTLAND GLOVER G., PRINTEMPS C., ESSEMIANI K., MEINHOLD J., (2005) Modelling of wastewater treatment plants ? How far shall we go with sophisticated modelling tools? 3rd IWA Leading-Edge Conference & Exhibition on Water and Wastewater Treatment Technologies, 6-8 June 2005, Sapporo, Japan DA SILVA G. (1994). Eléments d'optimisation du transfert d'oxygène par fines bulles et agitateur séparé en chenal d'oxydation. PhD Thesis. CEMAGREF Antony ? France. GILLOT S., DERONZIER G., HEDUIT A. (1997). Oxygen transfer under process conditions in an oxidation ditch equipped with fine bubble diffusers and slow speed mixers. WEFTEC, Chicago, USA. HENZE M., GUJER W., MINO T., van LOOSDRECHT M., (2000). Activated Sludge Models ASM1, ASM2, ASM2D and ASM3, Scientific and Technical Report No. 9. IWA Publishing, London, UK. JUSPIN H., VASEL J.-L. (2000). Influence of hydrodynamics on oxygen transfer in the activated sludge process. IWA, Paris - France.
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Despite the increasing body of evidence supporting the hypothesis of schizophrenia as a disconnection syndrome, studies of resting-state EEG Source Functional Connectivity (EEG-SFC) in people affected by schizophrenia are sparse. The aim of the present study was to investigate resting-state EEG-SFC in 77 stable, medicated patients with schizophrenia (SCZ) compared to 78 healthy volunteers (HV). In order to study the effect of illness duration, SCZ were divided in those with a short duration of disease (SDD; n = 25) and those with a long duration of disease (LDD; n = 52). Resting-state EEG recordings in eyes closed condition were analyzed and lagged phase synchronization (LPS) indices were calculated for each ROI pair in the source-space EEG data. In delta and theta bands, SCZ had greater EEG-SFC than HV; a higher theta band connectivity in frontal regions was observed in LDD compared with SDD. In the alpha band, SCZ showed lower frontal EEG-SFC compared with HV whereas no differences were found between LDD and SDD. In the beta1 band, SCZ had greater EEG-SFC compared with HVs and in the beta2 band, LDD presented lower frontal and parieto-temporal EEG-SFC compared with HV. In the gamma band, SDD had greater connectivity values compared with LDD and HV. This study suggests that resting state brain network connectivity is abnormally organized in schizophrenia, with different patterns for the different EEG frequency components and that EEG can be a powerful tool to further elucidate the complexity of such disordered connectivity.
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One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.
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While some aspects of social processing are shared between humans and other species, some aspects are not. The former seems to apply to merely tracking another's visual perspective in the world (i.e., what a conspecific can or cannot perceive), while the latter applies to perspective taking in form of mentally “embodying” another's viewpoint. Our previous behavioural research had indicated that only perspective taking, but not tracking, relies on simulating a body schema rotation into another's viewpoint. In the current study we employed Magnetoencephalography (MEG) and revealed that this mechanism of mental body schema rotation is primarily linked to theta oscillations in a wider brain network of body-schema, somatosensory and motor-related areas, with the right posterior temporo-parietal junction (pTPJ) at its core. The latter was reflected by a convergence of theta oscillatory power in right pTPJ obtained by overlapping the separately localised effects of rotation demands (angular disparity effect), cognitive embodiment (posture congruence effect), and basic body schema involvement (posture relevance effect) during perspective taking in contrast to perspective tracking. In a subsequent experiment we interfered with right pTPJ processing using dual pulse Transcranial Magnetic Stimulation (dpTMS) and observed a significant reduction of embodied processing. We conclude that right TPJ is the crucial network hub for transforming the embodied self into another's viewpoint, body and/or mind, thus, substantiating how conflicting representations between self and other may be resolved and potentially highlighting the embodied origins of high-level social cognition in general.
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There is currently great scientific and medical interest in the potential of tissue grown from stem cells. These cells present opportunities for generating model systems for drug screening and toxicological testing which would be expected to be more relevant to human outcomes than animal based tissue preparations. Newly realised astrocytic roles in the brain have fundamental implications within the context of stem cell derived neuronal networks. If the aim of stem cell neuroscience is to generate functional neuronal networks that behave as networks do in the brain, then it becomes clear that we must include and understand all the cellular components that comprise that network, and which are important to support synaptic integrity and cell to cell signalling. We have shown that stem cell derived neurons exhibit spontaneous and coordinated calcium elevations in clusters and in extended processes, indicating local and long distance signalling (1). Tetrodotoxin sensitive network activity could also be evoked by electrical stimulation. Similarly, astrocytes exhibit morphology and functional properties consistent with this glial cell type. Astrocytes also respond to neuronal activity and to exogenously applied neurotransmitters with calcium elevations, and in contrast to neurons, also exhibited spontaneous rhythmic calcium oscillations. Astroctyes also generate propagating calcium waves that are gap junction and purinergic signalling dependent. Our results show that stem cell derived astrocytes exhibit appropriate functionality and that stem cell neuronal networks interact with astrocytic networks in co-culture. Using mixed cultures of stem cell derived neurons and astrocytes, we have also shown both cell types also modulate their glucose uptake, glycogen turnover and lactate production in response to glutamate as well as increased neuronal activity (2). This finding is consistent with their neuron-astrocyte metabolic coupling thus demonstrating a tractable human model, which will facilitate the study of the metabolic coupling between neurons and astrocytes and its relationship with CNS functional issues ranging from plasticity to neurodegeneration. Indeed, cultures treated with oligomers of amyloid beta 1-42 (Aβ1-42) also display a clear hypometabolism, particularly with regard to utilization of substrates such as glucose (3). Both co-cultures of neurons and astrocytes and purified cultures of astrocytes showed a significant decrease in glucose uptake after treatment with 2 and 0.2 μmol/L Aβ at all time points investigated (p <0.01). In addition, a significant increase in the glycogen content of cells was also measured. Mixed neuron and astrocyte co-cultures as well as pure astrocyte cultures showed an initial decrease in glycogen levels at 6 hours compared with control at 0.2 μmol/L and 2 μmol/L P <0.01. These changes were accompanied by changes in NAD+/NADH (P<0.05), ATP (P<0.05), and glutathione levels (P<0.05), suggesting a disruption in the energy-redox axis within these cultures. The high energy demands associated with neuronal functions such as memory formation and protection from oxidative stress put these cells at particular risk from Aβ-induced hypometabolism. As numerous cell types interact in the brain it is important that any in vitro model developed reflects this arrangement. Our findings indicate that stem cell derived neuron and astrocyte networks can communicate, and so have the potential to interact in a tripartite manner as is seen in vivo. This study therefore lays the foundation for further development of stem cell derived neurons and astrocytes into therapeutic cell replacement and human toxicology/disease models. More recently our data provides evidence for a detrimental effect of Aβ on carbohydrate metabolism in both neurons and astrocytes. As a purely in vitro system, human stem cell models can be readily manipulated and maintained in culture for a period of months without the use of animals. In our laboratory cultures can be maintained in culture for up to 12 months months thus providing the opportunity to study the consequences of these changes over extended periods of time relevant to aspects of the disease progression time frame in vivo. In addition, their human origin provides a more realistic in vitro model as well as informing other human in vitro models such as patient-derived iPSC.
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When required to represent a perspective that conflicts with one's own, functional magnetic resonance imaging (fMRI) suggests that the right ventrolateral prefrontal cortex (rvlPFC) supports the inhibition of that conflicting self-perspective. The present task dissociated inhibition of self-perspective from other executive control processes by contrasting belief reasoning-a cognitive state where the presence of conflicting perspectives was manipulated-with a conative desire state wherein no systematic conflict existed. Linear modeling was used to examine the effect of continuous theta burst stimulation (cTBS) to rvlPFC on participants' reaction times in belief and desire reasoning. It was anticipated that cTBS applied to rvlPFC would affect belief but not desire reasoning, by modulating activity in the Ventral Attention System (VAS). We further anticipated that this effect would be mediated by functional connectivity within this network, which was identified using resting state fMRI and an unbiased model-free approach. Simple reaction-time analysis failed to detect an effect of cTBS. However, by additionally modeling individual measures from within the stimulated network, the hypothesized effect of cTBS to belief (but, importantly, not desire) reasoning was demonstrated. Structural morphology within the stimulated region, rvlPFC, and right temporoparietal junction were demonstrated to underlie this effect. These data provide evidence that inconsistencies found with cTBS can be mediated by the composition of the functional network that is being stimulated. We suggest that the common claim that this network constitutes the VAS explains the effect of cTBS to this network on false belief reasoning. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
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In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.
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In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.