979 resultados para App iOS programmazione analisi


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用透射电子显微镜和X射线衍射等方法研究了等规立构聚丙烯(iPP)和无规立构聚丙烯(aPP)共混物溶液浇铸膜的形态结构,结果表明,aPP的加入对iPP的形态结构有很大的影响。

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聚烯烃共混物中,最常见的和已商品化的是 iPP 与三元乙丙橡胶(EPDM)的共混物。人们一直用 EPDM 或乙丙无规共聚物(EPR)作为增韧剂加入到 iPP 中以提高其冲击强度。实验证明,橡胶的加入会导致 iPP 形态结构的变化。aPP 是一种非晶聚合物,它有类似像胶的性能,据报道,aPP 与 iPP 在熔体是相容的,aPP 的加入对 iPP 形态结构有很大影响。本文用 TEM 和 X-射线衍射等方法研究了 iPP/aPP 共混物薄膜的形态结构。

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iPP/aPP共混物薄膜的形态结构研究陈晔,杨德才(中国科学院长春应用化学研究所高分子物理开放实验室,长春130022)聚烯烃共混物中,最常见的和已商品化的是iPP与三元乙丙橡胶(EPDM)的共混物。人们一直用EPDM或乙丙无规共聚物(EPR)作为增...

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The identification of subject-specific traits extracted from patterns of brain activity still represents an important challenge. The need to detect distinctive brain features, which is relevant for biometric and brain computer interface systems, has been also emphasized in monitoring the effect of clinical treatments and in evaluating the progression of brain disorders. Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. In this study we propose an approach which aims to investigate the existence of a distinctive functional core (sub-network) using an unbiased reconstruction of network topology. Brain signals from a public and freely available EEG dataset were analyzed using a phase synchronization based measure, minimum spanning tree and k-core decomposition. The analysis was performed for each classical brain rhythm separately. Furthermore, we aim to provide a network approach insensitive to the effects that epoch length has on functional connectivity (FC) and network reconstruction. Two different measures, the phase lag index (PLI) and the Amplitude Envelope Correlation (AEC), were applied to EEG resting-state recordings for a group of eighteen healthy volunteers. Weighted clustering coefficient (CCw), weighted characteristic path length (Lw) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. Results about distinctive functional core, show highest classification rates from k-core decomposition in gamma (EER=0.130, AUC=0.943) and high beta (EER=0.172, AUC=0.905) frequency bands. Results from scalp analysis concerning the influence of epoch length, show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 seconds for PLI and 6 seconds for AEC. Moreover, CCw and Lw show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1-6 seconds versus 4-8 seconds for AEC). At the source-level the results were even more reliable, with stability already at 1 second duration for PLI-based MSTs. Our results confirm that EEG analysis may represent an effective tool to identify subject-specific characteristics that may be of great impact for several bioengineering applications. Regarding epoch length, the present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of brain network topology between different studies.

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Tesis inédita presentada en la Universidad Europea de Madrid. Facultad de Artes y Comunicación. Programa de Doctorado en Comunicación

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De acuerdo a la normativa de TFEs el repositorio no puede dar acceso a este trabajo. Para consultarlo póngase en contacto con el tutor del trabajo. Puede acceder al resumen del mismo pinchando en el pdf adjunto

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In a road network, cyclists are the group exposed to the maximum amount of risk. Route choice of a cyclist is often based on level of expertise, perceived or actual road risks, personal decisions, weather conditions and a number of other factors. Consequently, cycling tends to be the only significant travel mode where optimised route choice is not based on least-path or least-time. This paper presents an Android platform based mobile-app for personalised route planning of cyclists in Dublin. The mobile-app, apart from its immediate advantage to the cyclists, acts as the departure point for a number of research projects and aids in establishing some critical calibration values for the cycling network in Dublin.