925 resultados para Natural-selection


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This paper presents a study on the durability of different types of stabilised and unstabilised rammed earth walls. These rammed earth walls were constructed and exposed for 20 years to natural weathering, in a wet continental climate. None of these walls have shown complete collapse to date. A method to measure the rammed earth walls erosion by stereo-photogrammetry has been developed. The result shows that the mean erosion depth of the studied walls is about 2 mm (0.5% wall thickness) in the case of rammed earth wall stabilised with 5% by dry weight of hydraulic lime and about 6.4 mm (1.6% wall thickness) in the case of unstabilised rammed earth walls. The stabilisation enables to not use any plaster to protect the walls. In the case of the unstabilised rammed earth walls, an extrapolated lifetime longer than 60 years can be assessed. This shows a potential for the use of unstabilised rammed earth in the similar climatic conditions with this study. The method of stereo-photogrammetry used to measure the erosion of rammed earth walls on site may also help to calibrate and develop more pertinent laboratory test to assess the durability of rammed earth wall.

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Balconies, as one of the main architectural features in subtropical climates, are assumed to enhance the ventilation performance of buildings by redirecting the wind. Although there are some studies on the effect of balconies on natural ventilation inside buildings, the majority have been conducted on single zone buildings with simple geometries. The purpose of this study is to explore the effect of balconies on the internal air flow pattern and ventilation performance of multi-storey residential buildings with internal partitions. To this end, a sample residential unit was selected for investigation and three different conditions tested, base case (no balcony), an open balcony and a semi-enclosed balcony. Computational Fluid Dynamics is used as an analysis method due to its accuracy and ability to provide detailed results. The cases are analysed in terms of average velocity, flow uniformity and number of Air Changes per Hour (ACH). The results suggest the introduction of a semi-enclosed balcony into high-rise dwellings improves the average velocity and flow uniformity. Integrating an open balcony results in reduction of the aforementioned parameters at 0° wind incidence.

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In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

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Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.

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The perception of ultraviolet (UV) light by spiders has so far been only demonstrated in salticids. Crab spiders (Thomisidae) hunt mostly on flowers and need to find appropriate hunting sites. Previous studies have shown that some crab spiders that reflect UV light use UV contrast to enhance prey capture. The high UV contrast can be obtained either by modulation of body colouration or active selection of appropriate backgrounds for foraging. We show that crab spiders (Thomisus sp.)hunting on Spathiphyllum plants use chromatic contrast, especially UV contrast, to make themselves attractive to hymenopteran prey. Apart from that, they are able to achieve high UV contrast by active selection of non-UV reflecting surfaces when given a choice of UV-reflecting and non-UV reflecting surfaces in the absence of odour cues. Honeybees (Apis cerana) approached Spathiphyllum plants bearing crab spiders on which the spiders were high UV-contrast targets with greater frequency than those plants on which the UV-contrast of the spiders was low. Thus, crab spiders can perceive UV and may use it to choose appropriate backgrounds to enhance prey capture, by exploiting the attraction of prey such as honeybees to UV.

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The coordination driven self-assembly of discrete molecular triangles from a non-symmetric ambidentate linker 5-pyrimidinecarboxylate (5-pmc) and Pd(II)/Pt(II) based 90◦ acceptors is presented. Despite the possibility of formation of a mixture of isomeric macrocycles (linkage isomers) due to different connectivity of the ambidentate linker, formation of a single and symmetrical linkage somer in both the cases is an interesting observation. Moreover, the reported macrocycles represent the first example of discrete metallamacrocycles of bridging 5-pmc. While solution composition in both the cases was characterised by multinuclear NMR study and electrospray ionization mass spectrometry (ESI-MS), the identity of the assemblies in the solid state was established by X-ray single crystals structure analysis. Variable temperature NMR study clearly ruled out the formation of any other macrocycles by [4 + 4] or [2 + 2] self-assembly of the reacting components.

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Unsteady natural convection flow in a two- dimensional square cavity filled with a porous material has been studied. The flow is initially steady where the left- hand vertical wall has temperature T-h and the right- hand vertical wall is maintained at temperature T-c ( T-h > T-c) and the horizontal walls are insulated. At time t > 0, the left- hand vertical wall temperature is suddenly raised to (T-h) over bar ((T-h) over bar > T-h) which introduces unsteadiness in the flow field. The partial differential equations governing the unsteady natural convection flow have been solved numerically using a finite control volume method. The computation has been carried out until the final steady state is reached. It is found that the average Nusselt number attains a minimum during the transient period and that the time required to reach the final steady state is longer for low Rayleigh number and shorter for high Rayleigh number.

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Atherothrombosis is a systemic disease of the arterial wall that affects the carotid, coronary, and peripheral vascular beds, and the aorta. This condition is associated with complications such as stroke, myocardial infarction, and peripheral vascular disease, which usually result from unstable atheromatous plaques. The study of atheromatous plaques can provide useful information about the natural history and progression of the disease, and aid in the selection of appropriate treatment. Plaque imaging can be crucial in achieving this goal. In this Review, we focus on the various noninvasive imaging techniques that are being used for morphological and functional assessment of carotid atheromatous plaques in the clinical setting.

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Many wireless applications demand a fast mechanism to detect the packet from a node with the highest priority ("best node") only, while packets from nodes with lower priority are irrelevant. In this paper, we introduce an extremely fast contention-based multiple access algorithm that selects the best node and requires only local information of the priorities of the nodes. The algorithm, which we call Variable Power Multiple Access Selection (VP-MAS), uses the local channel state information from the accessing nodes to the receiver, and maps the priorities onto the receive power. It is based on a key result that shows that mapping onto a set of discrete receive power levels is optimal, when the power levels are chosen to exploit packet capture that inherently occurs in a wireless physical layer. The VP-MAS algorithm adjusts the expected number of users that contend in each step and their respective transmission powers, depending on whether previous transmission attempts resulted in capture, idle channel, or collision. We also show how reliable information regarding the total received power at the receiver can be used to improve the algorithm by enhancing the feedback mechanism. The algorithm detects the packet from the best node in 1.5 to 2.1 slots, which is considerably lower than the 2.43 slot average achieved by the best algorithm known to date.

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Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

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Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.

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We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.

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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.