Electronic Control of Facial Selection in Additions to Sterically Unbiased Ketones and Olefins

By definition, the two faces of a pi bond are equivalent.1 However, they are rendered nonequivalent in most molecules because of the absence of a plane of symmetry encompassing the double bond and the adjacent substituents. As a result, additions to trigonal centers from the two faces need not be equally facile. Exploiting this stereodifferentiation in a controlled manner represents one of the core problems in organic synthesis. Evidently, the factors which determine such diastereoselection need to be delineated in as much detail as possible.

Analysis of a Genomic DNA Expression Library of Mycobacterium tuberculosis Using Tuberculosis Patient Sera: Evidence for Modulation of Host Immune Response

DNA obtained from a human sputum isolate of Mycobacterium tuberculosis, NTI-64719, which showed extensive dissemination in the guinea pig model resulting in a high score for virulence was used to construct an expression library in the lambda ZAP vector. The size of DNA inserts in the library ranged from 1 to 3 kb, and recombinants represented 60% of the total plaques obtained. When probed with pooled serum from chronically infected tuberculosis patients, the library yielded 176 recombinants with a range of signal intensities. Among these, 93 recombinants were classified into 12 groups on the basis of DNA hybridization experiments, The polypeptides synthesized by the recombinants were predominantly LacZ fusion proteins, Serum obtained from patients who were clinically diagnosed to be in the early phase of M. tuberculosis infection was used to probe the 176 recombinants obtained. interestingly, some recombinants that gave very strong signals in the original screen did not react with early-phase serum; conversely, others whose signals were extremely weak in the original screen gave very intense signals with serum from recently infected patients, This indicates the differential nature of either the expression of these antigens or the immune response elicited by them as a function of disease progression.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

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.

Influence of road traffic environment and mobile phone distraction on the speed selection behaviour of young drivers

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.

Perception of ultraviolet light by crab spiders and its role in selection of hunting sites

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.

Synthesis and characterisation of heterometallic molecular triangles using ambidentate linker: self-selection of a single linkage isomer

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.

Fast Multiple Access Selection through variable power transmissions

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.

Similarities in the Genomic Sequence and Coat Protein-Structure of Plant Viruses

The genomic sequences of several RNA plant viruses including cucumber mosaic virus, brome mosaic virus, alfalfa mosaic virus and tobacco mosaic virus have become available recently. The former two viruses are icosahedral while the latter two are bullet and rod shaped, respectively in particle morphology. The non-structural 3a proteins of cucumber mosaic virus and brome mosaic virus have an amino acid sequence homology of 35% and hence are evolutionarily related. In contrast, the coat proteins exhibit little homology, although the circular dichroism spectrum of these viruses are similar. The non-coding regions of the genome also exhibit variable but extensive homology. Comparison of the brome mosaic virus and alfalfa mosaic virus sequences reveals that they are probably related although with a much larger evolutionary distance. The polypeptide folds of the coat protein of three biologically distinct isometric plant viruses, tomato bushy stunt virus, southern bean mosaic virus and satellite tobacco necrosis virus have been shown to display a striking resemblance. All of them consist of a topologically similar 8-standard β-barrel. The implications of these studies to the understanding of the evolution of plant viruses will be discussed.

Model selection with misspecified spatial covariance structure

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.

Intra-cluster correlation structure in longitudinal data analysis: Selection criteria and misspecification tests

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.

Working covariance model selection for generalized estimating equations

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.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

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.

Estimation for the general sample selection models

Consider a general regression model with an arbitrary and unknown link function and a stochastic selection variable that determines whether the outcome variable is observable or missing. The paper proposes U-statistics that are based on kernel functions as estimators for the directions of the parameter vectors in the link function and the selection equation, and shows that these estimators are consistent and asymptotically normal.

Criteria for working-correlation-structure selection in GEE: Assessment via simulation

Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

On the moulding of population viscosity by natural selection

In this paper, we explore the conjoint evolution of dispersal and social behaviour. The model investigated is of a population distributed over a number of sites each with a carrying capacity of two adults and an episode of dispersal in the juvenile stage. The fertilities are governed by whether an individual and its neighbour are selfish or co-operative. It is shown that the best dispersal strategy for the co-operative genotype always involves lower levels of dispersal; and further that ecological conditions favouring low levels of dispersal increase the selective advantage of a co-operative genotype. Given this positive feedback, we suggest that in any taxon viscosity and co-operativity will tend to be correlated and bimodally distributed. Hence we predict the existence of two kinds of animal societies; viscous and co-operative (e.g. quasi-social wasps such as Mischocyttarus), and non-viscous and selfish (e.g. communal sphecid wasps such as Cerceris), and relatively few social groups with intermediate levels of co-operativity and viscosity. We also suggest that when one of the two sexes disperses, it will be the sex with lower potential for co-operative behaviour.