925 resultados para Centric fusion


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Protein interactions play key roles throughout all subcellular compartments. In the present paper, we report the visualization of protein interactions throughout living mammalian cells using two oligomerizing MV (measles virus) transmembrane glycoproteins, the H (haemagglutinin) and the F (fusion) glycoproteins, which mediate MV entry into permissive cells. BiFC (bimolecular fluorescence complementation) has been used to examine the dimerization of these viral glycoproteins. The H glycoprotein is a type II membrane-receptor-binding homodimeric glycoprotein and the F glycoprotein is a type I disulfide-linked membrane glycoprotein which homotrimerizes. Together they co-operate to allow the enveloped virus to enter a cell by fusing the viral and cellular membranes. We generated a pair of chimaeric H glycoproteins linked to complementary fragments of EGFP (enhanced green fluorescent protein)--haptoEGFPs--which, on association, generate fluorescence. Homodimerization of H glycoproteins specifically drives this association, leading to the generation of a fluorescent signal in the ER (endoplasmic reticulum), the Golgi and at the plasma membrane. Similarly, the generation of a pair of corresponding F glycoprotein-haptoEGFP chimaeras also produced a comparable fluorescent signal. Co-expression of H and F glycoprotein chimaeras linked to complementary haptoEGFPs led to the formation of fluorescent fusion complexes at the cell surface which retained their biological activity as evidenced by cell-to-cell fusion.

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This study presents the findings of an empirical channel characterisation for an ultra-wideband off-body optic fibre-fed multiple-antenna array within an office and corridor environment. The results show that for received power experiments, the office and corridor were best modelled by lognormal and Rician distributions, respectively [for both line of sight (LOS) and non-LOS (NLOS) scenarios]. In the office, LOS measurements for t and tRMS were both described by the Normal distribution for all channels, whereas NLOS measurements for t and t were Nakagami and Weibull distributed, respectively. For the corridor measurements, LOS for t and t were either Nakagami or normally distributed for all channels, with NLOS measurements for t and t being Nakagami and normally distributed, respectively. This work also shows that achievable diversity gain was influenced by both mutual coupling and cross-correlation co-efficients. Although the best diversity gains were 1.8 dB for three-channel selective diversity combining, the authors present recommendations for improving these results. © The Institution of Engineering and Technology 2013.

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Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

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We investigate whether the presence of a human body in wearable communications should be considered as part of the radiating structure or as part of the local radio environment. The Rician $K$ -factor was employed as a quantitative measure of the effect of the user's body for five environments and two mounting locations. Presented empirical results indicated that the environment had a greater impact on the $K$-factor values than the position of the transmit antenna for the ultrawideband signals used, confirming that the human body should be considered primarily as part of the overall radiating system when the antenna is worn on the body. Furthermore, independent variations also existed in the $K$-factor values for the differing antenna-body mounting positions, indicating that as the position changed, then the radiating effects and the contribution from the body changed. This is significant for ensuring body-antenna systems are accurately modeled in system-level simulations.

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This paper presents a new statistical signal reception model for shadowed body-centric communications channels. In this model, the potential clustering of multipath components is considered alongside the presence of elective dominant signal components. As typically occurs in body-centric communications channels, the dominant or line-of-sight (LOS) components are shadowed by body matter situated in the path trajectory. This situation may be further exacerbated due to physiological and biomechanical movements of the body. In the proposed model, the resultant dominant component which is formed by the phasor addition of these leading contributions is assumed to follow a lognormal distribution. A wide range of measured and simulated shadowed body-centric channels considering on-body, off-body and body-to-body communications are used to validate the model. During the course of the validation experiments, it was found that, even for environments devoid of multipath or specular reflections generated by the local surroundings, a noticeable resultant dominant component can still exist in body-centric channels where the user's body shadows the direct LOS signal path between the transmitter and the receiver.

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The human body is an extremely challenging environment for the operation of wireless communications systems, not least because of the complex antenna-body electromagnetic interaction effects which can occur. This is further compounded by the impact of movement and the propagation characteristics of the local environment which all have an effect upon body centric communications channels. As the successful design of body area networks (BANs) and other types of body centric system is inextricably linked to a thorough understanding of these factors, the aim of this paper is to conduct a survey of the current state of the art in relation to propagation and channel models primarily for BANs but also considering other types of body centric communications. We initially discuss some of the standardization efforts performed by the Institute of Electrical and Electronics Engineers 802.15.6 task group before focusing on the two most popular types of technologies currently being considered for BANs, namely narrowband and Ultrawideband (UWB) communications. For narrowband communications the applicability of a generic path loss model is contended, before presenting some of the scenario specific models which have proven successful. The impacts of human body shadowing and small-scale fading are also presented alongside some of the most recent research into the Doppler and time dependencies of BANs. For UWB BAN communications, we again consider the path loss as well as empirical tap delay line models developed from a number of extensive channel measurement campaigns conducted by research institutions around the world. Ongoing efforts within collaborative projects such as Committee on Science and Technology Action IC1004 are also described. Finally, recent years have also seen significant developments in other areas of body centric communications such as off-body and body-to-body communications. We highlight some of the newest relevant research in these areas as well as discussing some of the advanced topics which are currently being addressed in the field of body centric communications. Key Points Channel models for body centric comms ©2014. The Authors.

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Correctly modelling and reasoning with uncertain information from heterogeneous sources in large-scale systems is critical when the reliability is unknown and we still want to derive adequate conclusions. To this end, context-dependent merging strategies have been proposed in the literature. In this paper we investigate how one such context-dependent merging strategy (originally defined for possibility theory), called largely partially maximal consistent subsets (LPMCS), can be adapted to Dempster-Shafer (DS) theory. We identify those measures for the degree of uncertainty and internal conflict that are available in DS theory and show how they can be used for guiding LPMCS merging. A simplified real-world power distribution scenario illustrates our framework. We also briefly discuss how our approach can be incorporated into a multi-agent programming language, thus leading to better plan selection and decision making.

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The propagation of UWB signals for body-centric communications within a modern classroom/conference room environment was investigated. Presented results demonstrate that the body-antenna mounting position has a marked impact on the received power levels and positioning the antenna on the chest as opposed to the shoulder or wrist creates more extreme values in receive power, mean excess delay and rms delay spread. Additionally, the best fit models for each scenario are presented and highlight the difference between the chest and other compared antenna locations. The work concluded that the chest is a poor choice of mounting position for the antenna due to significant body shadowing effects, with the wrist or shoulder considered better options for UWB systems.

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Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.

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Induced in high glucose-1 (IHG-1) is a conserved mitochondrial protein associated with diabetic nephropathy (DN) that amplifies profibrotic transforming growth factor (TGF)-β1 signaling and increases mitochondrial biogenesis. Here we report that inhibition of endogenous IHG-1 expression results in reduced mitochondrial respiratory capacity, ATP production, and mitochondrial fusion. Conversely, overexpression of IHG-1 leads to increased mitochondrial fusion and also protects cells from reactive oxygen species-induced apoptosis. IHG-1 forms complexes with known mediators of mitochondrial fusion-mitofusins (Mfns) 1 and 2-and enhances the GTP-binding capacity of Mfn2, suggesting that IHG-1 acts as a guanine nucleotide exchange factor. IHG-1 must be localized to mitochondria to interact with Mfn1 and Mfn2, and this interaction is necessary for increased IHG-1-mediated mitochondrial fusion. Together, these findings indicate that IHG-1 is a novel regulator of both mitochondrial dynamics and bioenergetic function and contributes to cell survival following oxidant stress. We propose that in diabetic kidney disease increased IHG-1 expression protects cell viability and enhances the actions of TGF-β, leading to renal proximal tubule dedifferentiation, an important event in the pathogenesis of this devastating condition.

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Depending on the representation setting, different combination rules have been proposed for fusing information from distinct sources. Moreover in each setting, different sets of axioms that combination rules should satisfy have been advocated, thus justifying the existence of alternative rules (usually motivated by situations where the behavior of other rules was found unsatisfactory). These sets of axioms are usually purely considered in their own settings, without in-depth analysis of common properties essential for all the settings. This paper introduces core properties that, once properly instantiated, are meaningful in different representation settings ranging from logic to imprecise probabilities. The following representation settings are especially considered: classical set representation, possibility theory, and evidence theory, the latter encompassing the two other ones as special cases. This unified discussion of combination rules across different settings is expected to provide a fresh look on some old but basic issues in information fusion.

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Gender profiling is a fundamental task that helps CCTV systems to
provide better service for intelligent surveillance. Since subjects being detected
by CCTVs are not always cooperative, a few profiling algorithms are proposed
to deal with situations when faces of subjects are not available, among which
the most common approach is to analyze subjects’ body shape information. In
addition, there are some drawbacks for normal profiling algorithms considered
in real applications. First, the profiling result is always uncertain. Second, for a
time-lasting gender profiling algorithm, the result is not stable. The degree of
certainty usually varies, sometimes even to the extent that a male is classified
as a female, and vice versa. These facets are studied in a recent paper [16] using
Dempster-Shafer theory. In particular, Denoeux’s cautious rule is applied for
fusion mass functions through time lines. However, this paper points out that if
severe mis-classification is happened at the beginning of the time line, the result
of applying Denoeux’s rule could be disastrous. To remedy this weakness,
in this paper, we propose two generalizations to the DS approach proposed in
[16] that incorporates time-window and time-attenuation, respectively, in applying
Denoeux’s rule along with time lines, for which the DS approach is a special
case. Experiments show that these two generalizations do provide better results
than their predecessor when mis-classifications happen.