991 resultados para Cellular traffic offloading


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Road traffic noise affects the quality of life in the areas adjoining the road. The effect of traffic noise on people is wide ranging and may include sleep disturbance and negative impact on work efficiency. To address the problem of traffic noise, it is necessary to estimate the noise level. For this, a number of noise estimation models have been developed which can estimate noise at the receptor points, based on simple configuration of buildings. However, for a real world situation we have multiple buildings forming built-up area. In such a situation, it is almost impossible to consider multiple diffractions and reflections in sound propagation from the source to the receptor point. An engineering solution to such a real world problem is needed to estimate noise levels in built-up area.

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A range of varying chromophore nitroxide free radicals and their nonradical methoxyamine analogues were synthesized and their linear photophysical properties examined. The presence of the proximate free radical masks the chromophore’s usual fluorescence emission, and these species are described as profluorescent. Two nitroxides incorporating anthracene and fluorescein chromophores (compounds 7 and 19, respectively) exhibited two-photon absorption (2PA) cross sections of approximately 400 G.M. when excited at wavelengths greater than 800 nm. Both of these profluorescent nitroxides demonstrated low cytotoxicity toward Chinese hamster ovary (CHO) cells. Imaging colocalization experiments with the commercially available CellROX Deep Red oxidative stress monitor demonstrated good cellular uptake of the nitroxide probes. Sensitivity of the nitroxide probes to H2O2-induced damage was also demonstrated by both one- and two-photon fluorescence microscopy. These profluorescent nitroxide probes are potentially powerful tools for imaging oxidative stress in biological systems, and they essentially “light up” in the presence of certain species generated from oxidative stress. The high ratio of the fluorescence quantum yield between the profluorescent nitroxide species and their nonradical adducts provides the sensitivity required for measuring a range of cellular redox environments. Furthermore, their reasonable 2PA cross sections provide for the option of using two-photon fluorescence microscopy, which circumvents commonly encountered disadvantages associated with one-photon imaging such as photobleaching and poor tissue penetration.

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Traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) pose a serious threat to human and ecosystem health when washed off into receiving water bodies by stormwater. Climate change influenced rainfall characteristics makes the estimation of these pollutants in stormwater quite complex. The research study discussed in the paper developed a prediction framework for such pollutants under the dynamic influence of climate change on rainfall characteristics. It was established through principal component analysis (PCA) that the intensity and durations of low to moderate rain events induced by climate change mainly affect the wash-off of SVOCs and NVOCs from urban roads. The study outcomes were able to overcome the limitations of stringent laboratory preparation of calibration matrices by extracting uncorrelated underlying factors in the data matrices through systematic application of PCA and factor analysis (FA). Based on the initial findings from PCA and FA, the framework incorporated orthogonal rotatable central composite experimental design to set up calibration matrices and partial least square regression to identify significant variables in predicting the target SVOCs and NVOCs in four particulate fractions ranging from >300-1 μm and one dissolved fraction of <1 μm. For the particulate fractions range >300-1 μm, similar distributions of predicted and observed concentrations of the target compounds from minimum to 75th percentile were achieved. The inter-event coefficient of variations for particulate fractions of >300-1 μm were 5% to 25%. The limited solubility of the target compounds in stormwater restricted the predictive capacity of the proposed method for the dissolved fraction of <1 μm.

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Traffic related emissions have been recognised as one of the main sources of air pollutants. In the research study discussed in this paper, variability of atmospheric total suspended particulate matter (TSP), polycyclic aromatic hydrocarbons (PAH) and heavy metal (HM) concentrations with traffic and land use characteristics during weekdays and weekends were investigated. Data required for the study were collected from a range of sampling sites to ensure a wide mix of traffic and land use characteristics. The analysis undertaken confirmed that zinc has the highest concentration in the atmospheric phase during weekends as well as weekdays. Although the use of leaded gasoline was discontinued a decade ago, lead was the second most commonly detected heavy metal. This is attributed to the association of previously generated lead with roadside soil and re-suspension to the atmosphere. Soil related particles are the primary source of TSP and manganese to the atmosphere. The analysis further revealed that traffic sources are dominant in gas phase PAHs compared to the other sources during weekdays. Land use related sources become important contributors to atmospheric PAHs during weekends when traffic sources are at their minimal levels.

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For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

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The ability of cells to adhere, spread and migrate is essential to many physiological processes, particularly in the immune system where cells must traffic to sites of inflammation and injury. By altering the levels of individual components of the VAMP3/Stx4/SNAP23 complex we show here that this SNARE complex regulates efficient macrophage adhesion, spreading and migration on fibronectin. During cell spreading this complex mediates the polarised exocytosis of VAMP3- positive recycling endosome membrane into areas of membrane expansion, where VAMP3's surface partner Q-SNARE complex Stx4/SNAP23 was found to accumulate. Lowering the levels of VAMP3 in spreading cells resulted in a more rounded cell morphology and most cells were found to be devoid of the typical ring-like podosome superstructures seen normally in spreading cells. In migrating cells lowering VAMP3 levels disrupted the polarised localisation of podosome clusters. The reduced trafficking of recycling endosome membrane to sites of cell spreading and the disorganised podosome localisation in migrating macrophages greatly reduced their ability to persistently migrate on fibronectin. Thus, this important SNARE complex facilitates macrophage adhesion, spreading, and persistent macrophage migration on fibronectin through the delivery of VAMP3-positive membrane with its cargo to expand the plasma membrane and to participate in organising adhesive podosome structures.

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Cell migration is a highly complex process that requires the extension of cell membrane in the direction of travel. This membrane is continuously remodeled to expand the leading edge and alter its membrane properties. For a long time it has been known that there is a continual flow of polarized membrane traffic towards the leading edge during migration and that this trafficking is essential for cell migration. However, there is little information on how the cell coordinates exocytosis at the leading edge. It is also unclear whether these internal membranes are incorporated into the leading edge or are just delivering the necessary proteins for migration to occur. We have shown that recycling endosome membrane is incorporated into the plasma membrane at the leading edge to expand the membrane and at the same time delivers receptors to the leading edge to mediate migration. In order for this to happen the surface Q-SNARE complex Stx4/SNAP23 translocates to the leading edge where it binds to the R-SNARE VAMP3 on the recycling endosome allowing incorporation into the plasma membrane. Loss of any one of the components of this complex reduces efficient lamellipodia formation and restrains cell migration.

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In comparison to our knowledge of the recycling of adhesion receptors and actin assembly, exactly how the cell controls its surface membrane to form a lamellipodium during migration is poorly understood. Here, we show the recycling endosome membrane is incorporated into the leading edge of a migrating cell to expand lamellipodia membrane. We have identified the SNARE complex that is necessary for fusion of the recycling endosome with the cell surface, as consisting of the R-SNARE VAMP3 on the recycling endosome partnering with the surface Q-SNARE Stx4/SNAP23, which was found to translocate and accumulate on the leading edge of migrating cells. Increasing VAMP3-mediated fusion of the recycling endosome with the surface increased membrane ruffling, while inhibition of VAMP3-mediated fusion showed that incorporation of the recycling endosome is necessary for efficient lamellipodia formation. At the same time, insertion of this recycling endosome membrane also delivers its cargo integrin α5β1 to the cell surface. The loss of this extra membrane for lamellipodia expansion and delivery of cargo in cells resulted in macrophages with a diminished capacity to effectively migrate. Thus, the recycling endosome membrane is incorporated into the leading edge and this aids expansion of the lamellipodia and simultaneously delivers integrins necessary for efficient cell migration.

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This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

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Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

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Many governments throughout the world rely heavily on traffic law enforcement programs to modify driver behaviour and enhance road safety. There are two related functions of traffic law enforcement, apprehension and deterrence, and these are achieved through three processes: the establishment of traffic laws, the policing of those laws, and the application of penalties and sanctions to offenders. Traffic policing programs can vary by visibility (overt or covert) and deployment methods (scheduled and non-scheduled), while sanctions can serve to constrain, deter or reform offending behaviour. This chapter will review the effectiveness of traffic law enforcement strategies from the perspective of a range of high-risk, illegal driving behaviours including drink/drug driving, speeding, seat belt use and red light running. Additionally, this chapter discusses how traffic police are increasingly using technology to enforce traffic laws and thus reduce crashes. The chapter concludes that effective traffic policing involves a range of both overt and covert operations and includes a mix of automatic and more traditional manual enforcement methods. It is important to increase both the perceived and actual risk of detection by ensuring that traffic law enforcement operations are sufficiently intensive, unpredictable in nature and conducted as widely as possible across the road network. A key means of maintaining the unpredictability of operations is through the random deployment of enforcement and/or the random checking of drivers. The impact of traffic enforcement is also heightened when it is supported by public education campaigns. In the future, technological improvements will allow the use of more innovative enforcement strategies. Finally, further research is needed to continue the development of traffic policing approaches and address emerging road safety issues.

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Navigational safety analysis relying on collision statistics is often hampered because of low number of observations. A promising alternative approach that overcomes this problem is proposed in this paper. By analyzing critical vessel interactions this approach proactively measures collision risk in port waters. The proposed method is illustrated for quantitative measurement of collision risks in Singapore port fairways, and validated by examining correlations between the measured risks with those perceived by pilots. This method is an ethically appealing alternative to the collision-based analysis for fast, reliable and effective safety assessment, thus possesses great potential for managing collision risks in port waters.

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Navigational collisions are one of the major safety concerns for many seaports. Despite the extent of work recently done on collision risk analysis in port waters, little is known about the influencing factors of the risk. This paper develops a technique for modeling collision risks in port waterways in order to examine the associations between the risks and the geometric, traffic, and regulatory control characteristics of waterways. A binomial logistic model, which accounts for the correlations in the risks of a particular fairway at different time periods, is derived from traffic conflicts and calibrated for the Singapore port fairways. Estimation results show that the fairways attached to shoreline, traffic intersection and international fairway attribute higher risks, whereas those attached to confined water and local fairway possess lower risks. Higher risks are also found in the fairways featuring higher degree of bend, lower depth of water, higher numbers of cardinal and isolated danger marks, higher density of moving ships and lower operating speed. The risks are also found to be higher for night-time conditions.

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This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.

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Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.