873 resultados para POLYMERIZATION REACTOR OPTIMIZATION
Resumo:
With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.
Resumo:
The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.
Resumo:
It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.
Resumo:
One Norwegian and one UK spring wheat cultivar, Bjarne and Cadenza, respectively, were grown in climate chambers to investigate the effects of lower to moderate temperatures during grain filling on the gluten quality. Two experiments were carried out with weekly fertilization until anthesis, while post-anthesis fertilization was applied in a third experiment. The proportions of different gluten proteins were affected by temperature in a similar manner for both cultivars when grown without post-anthesis fertilization. However, whereas low temperature strongly decreased %UPP for Cadenza, Bjarne had high %UPP at all temperature regimes. The results indicated that the assembly of glutenin polymers in Bjarne was less sensitive to variation in temperature than in Cadenza. Thus, our results suggested that the temperature influenced the proportion of different gluten proteins in both cultivars, while its effects on the assembly of the glutenin polymers were cultivar dependent. The duration of grain filling was longer at the lower temperatures, and this was associated with increased grain weight. Temperature had little effect on the amount of protein accumulated per grain, thus the proportion of proteins was strongly decreased at lower temperatures. This was to some extent, but not fully counteracted by post-anthesis fertilization.
Resumo:
Verbal communication is essential for human society and human civilization. Non-verbal communication, on the other hand, is more widely used not only by human but also other kind of animals, and the content of information is estimated even larger than the verbal communication. Among the non-verbal communication mutual motion is the simplest and easiest to study experimentally and analytically. We measured the power spectrum of the hand velocity in various conditions and clarified the following points on the feed-back and feed- forward mechanism as basic knowledge to understand the condition of good communication.
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This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks.
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The effects of several fat replacement levels (0%, 35%, 50%, 70%, and 100%) by inulin in sponge cake microstructure and physicochemical properties were studied. Oil substitution for inulin decreased significantly (P < 0.05) batter viscosity, giving heterogeneous bubbles size distributions as it was observed by light microscopy. Using confocal laser scanning microscopy the fat was observed to be located at the bubbles’ interface, enabling an optimum crumb cake structure development during baking. Cryo-SEM micrographs of cake crumbs showed a continuous matrix with embedded starch granules and coated with oil; when fat replacement levels increased, starch granules appeared as detached structures. Cakes with fat replacement up to 70% had a high crumb air cell values; they were softer and rated as acceptable by an untrained sensory panel (n = 51). So, the reformulation of a standard sponge cake recipe to obtain a new product with additional health benefits and accepted by consumers is achieved.
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The C-type lectin-like receptor 2 (CLEC-2) activates platelets through Src and Syk tyrosine kinases via a single cytoplasmic YxxL motif known as a hem immunoreceptor tyrosine-based activation motif (hemITAM). Here, we demonstrate using sucrose gradient ultracentrifugation and methyl-beta-cyclodextrin treatment that CLEC-2 translocates to lipid rafts upon ligand engagement and that translocation is essential for hemITAM phosphorylation and signal initiation. HemITAM phosphorylation, but not translocation, is also critically dependent on actin polymerization, Rac1 activation, and release of ADP and thromboxane A(2) (TxA(2)). The role of ADP and TxA(2) in mediating phosphorylation is dependent on ligand engagement and rac activation but is independent of platelet aggregation. In contrast, tyrosine phosphorylation of the GPVI-FcRgamma-chain ITAM, which has 2 YxxL motifs, is independent of actin polymerization and secondary mediators. These results reveal a unique series of proximal events in CLEC-2 phosphorylation involving actin polymerization, secondary mediators, and Rac activation.
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Proanthocyanidins (PAs) in sainfoin (Onobrychis viciifolia Scop.) are of interest to ameliorate the sustainability of livestock production. However, sainfoin forage yield and PA concentrations, as well as their composition, require optimization. Individual plants of 27 sainfoin accessions from four continents were analyzed with LC-ESI-QqQ-MS/MS for PA concentrations and simple phenolic compounds. Large variability existed in PA concentrations (23.0–47.5 mg g–1 leaf dry matter (DM)), share of prodelphinidins (79–96%), and mean degree of polymerization (11–14) among, but also within, accessions. PAs were mainly located in leaves (26.8 mg g–1 DM), whereas stems had less PAs (7.8 mg g–1 DM). Overall, high-yielding plants had lower PA leaf concentrations (R2 = 0.16, P < 0.001) and fewer leaves (R2 = 0.66, P < 0.001). However, the results show that these two trade-offs between yield and bioactive PAs can be overcome.
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In this paper we study the problem of maximizing a quadratic form 〈Ax,x〉 subject to ‖x‖q=1, where A has matrix entries View the MathML source with i,j|k and q≥1. We investigate when the optimum is achieved at a ‘multiplicative’ point; i.e. where x1xmn=xmxn. This turns out to depend on both f and q, with a marked difference appearing as q varies between 1 and 2. We prove some partial results and conjecture that for f multiplicative such that 0
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With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.
Investigation and optimization of parameters affecting the multiply charged ion yield in AP-MALDI MS
Resumo:
Liquid matrix-assisted laser desorption/ionization (MALDI) allows the generation of predominantly multiply charged ions in atmospheric pressure (AP) MALDI ion sources for mass spectrometry (MS) analysis. The charge state distribution of the generated ions and the efficiency of the ion source in generating such ions crucially depend on the desolvation regime of the MALDI plume after desorption in the AP-tovacuum inlet. Both high temperature and a flow regime with increased residence time of the desorbed plume in the desolvation region promote the generation of multiply charged ions. Without such measures the application of an electric ion extraction field significantly increases the ion signal intensity of singly charged species while the detection of multiply charged species is less dependent on the extraction field. In general, optimization of high temperature application facilitates the predominant formation and detection of multiply charged compared to singly charged ion species. In this study an experimental setup and optimization strategy is described for liquid AP-MALDI MS which improves the ionization effi- ciency of selected ion species up to 14 times. In combination with ion mobility separation, the method allows the detection of multiply charged peptide and protein ions for analyte solution concentrations as low as 2 fmol/lL (0.5 lL, i.e. 1 fmol, deposited on the target) with very low sample consumption in the low nL-range.
Resumo:
Plant-derived proanthocyanidins (PAC) have been promoted as a natural method of improving health and immune function in livestock. It has previously been shown that PAC are effective agonists for activating ruminant γδ T-cells in vitro, however effects on other livestock species are not yet clear. Moreover, the fine structural characteristics of the PAC which contribute to this stimulatory effect have not been elucidated. Here, we demonstrate activation of porcine γδ T-cells by PAC via up-regulation of CD25 (IL-2Rα) and show that 1) activation is dependent on degree of polymerization (DP), with PAC fractions containing polymers with mean DP >6 significantly more effective than fractions with mean DP <6, whilst flavan-3-ol monomers (the constituent monomeric units of PAC) did not induce CD25 expression and 2) both procyanidin and prodelphinidin-type PAC are effective agonists. Furthermore, we show that this effect of PAC is restricted to the γδ T-cell population within porcine peripheral mononuclear cells as significant CD25 up-regulation was not observed in non γδ T-cells, and no activation (via CD80/86 up-regulation) was evident in monocytes. Our results show that dietary PAC may contribute to enhancement of innate immunity in swine via activation of γδ T-cells.
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Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.
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Immediate loading of dental implants shortens the treatment time and makes it possible to give the patient an esthetic appearance throughout the treatment period. Placement of dental implants requires precise planning that accounts for anatomic limitations and restorative goals. Diagnosis can be made with the assistance of computerized tomographic scanning, but transfer of planning to the surgical field is limited. Recently, novel CAD/CAM techniques such as stereolithographic rapid prototyping have been developed to build surgical guides in an attempt to improve precision of implant placement. The aim of this case report was to show a modified surgical template used throughout implant placement as an alternative to a conventional surgical guide.