搜索结果：Range

Gene flow from the center of a species' range can stymie adaptation at the periphery and prevent the range from expanding outward. We study this process using simple models that track both demography and the evolution of a quantitative trait in a population that is continuously distributed in space. Stabilizing selection acts on the trait and favors an optimum phenotype that changes linearly across the habitat. One of three outcomes is possible: the species will become extinct, expand to fill all of the available habitat, or be confined to a limited range in which it is sufficiently adapted to allow population growth. When the environment changes rapidly in space, increased migration inhibits local adaptation and so decreases the species' total population size. Gene flow can cause enough maladaptation that the peripheral half of a species' range acts as a demographic sink. The trait's genetic variance has little effect on species persistence or the size of the range when gene flow is sufficiently strong to keep population densities far below the carrying capacity throughout the range, but it can increase the range width and population size of an abundant species. Under some conditions, a small parameter change can dramatically shift the balance between gene flow and local adaptation, allowing a species with a limited range to suddenly expand to fill all the available habitat.

Two-dimensional turbulence has both kinetic energy and mean-square vorticity as inviscid constants of motion. Consequently it admits two formal inertial ranges, E(k)∼ε2/3k−5/3 and E(k)∼η2/3k−3, where ε is the rate of cascade of kinetic energy per unit mass, η is the rate of cascade of mean-square vorticity, and the kinetic energy per unit mass is ∫0∞E(k) dk. The −53 range is found to entail backward energy cascade, from higher to lower wavenumbers k, together with zero-vorticity flow. The −3 range gives an upward vorticity flow and zero-energy flow. The paradox in these results is resolved by the irreducibly triangular nature of the elementary wavenumber interactions. The formal −3 range gives a nonlocal cascade and consequently must be modified by logarithmic factors. If energy is fed in at a constant rate to a band of wavenumbers ∼ki and the Reynolds number is large, it is conjectured that a quasi-steady-state results with a −53 range for k « ki and a −3 range for k » ki, up to the viscous cutoff. The total kinetic energy increases steadily with time as the −53 range pushes to ever-lower k, until scales the size of the entire fluid are strongly excited. The rate of energy dissipation by viscosity decreases to zero if kinematic viscosity is decreased to zero with other parameters unchanged.

A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: incremental updating, representation of directional uncertainty, the ability to fill gaps in the reconstruction, and robustness in the presence of outliers. Prior algorithms possess subsets of these properties. In this paper, we present a volumetric method for integrating range images that possesses all of these properties. Our volumetric representation consists of a cumulative weighted signed distance function. Working with one range image at a time, we first scan-convert it to a distance function, then combine this with the data already acquired using a simple additive scheme. To achieve space efficiency, we employ a run-length encoding of the volume. To achieve time efficiency, we resample the range image to align with the voxel grid and traverse the range and voxel scanlines synchronously. We generate the final manifold by extracting an isosurface from the volumetric grid. We show that under certain assumptions, this isosurface is optimal in the least squares sense. To fill gaps in the model, we tessellate over the boundaries between regions seen to be empty and regions never observed. Using this method, we are able to integrate a large number of range images (as many as 70) yielding seamless, high-detail models of up to 2.6 million triangles. CR Categories: I.3.5 [Computer Graphics] Computational Geometry and Object Modeling Additional keywords: Surface fitting, three-dimensional shape recovery, range image integration, isosurface extraction 1

In many fields of research, one is faced with the task of comparing the effects of treatments which have been replicated unequally. This happens for a number of reasons. In an experiment on animals, some may get sick and have to be removed from the experiment. In some experiments, the amount of material available for certain treatments may not be as much as for other treatments. If the experimenter has specified orthogonal contrasts that he is interested in before he runs the experiment, one can test the various treatment effects by an F-test after the treatment sum of squares has been partitioned into individual degrees of freedom for each orthogonal contrast. If the experimenter has not specified orthogonal contrasts, one is faced with the problem of deciding which treatments are significantly different. Several writers, including Duncan, Keuls, Newman, and Tukey, have developed multiple range tests to show differences among treatments that have been replicated the same number of times and when nothing was specified concerning the treatments. Duncan [1] compares the above methods and gives citations. This extension to unequal numbers of replications will be exemplified with reference to Duncan's New Multiple Range Test, but is applicable to any of the above writers' tests; all one has to do is use their tabled ranges. In Duncan's test for an equal number of replications, the difference between any two ranked means is significant if the difference exceeds a shortest significant range. This shortest significant range is designated by R, and is obtained by multiplying the standard error of a mean, s,, by a given value, zn2, obtained from a table of significant studentized ranges which Duncan has tabled for both the 5% and 1% test. In Duncan's terminology, n2 is the degrees of freedom of the error mean square and p = 1, 2, * *, t is the number of means concerned. Consider an experiment with five treatments, A, B. C, D, and E, each replicated n times. Suppose on ranking the means from low to high one obtains

BACKGROUND: Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. METHODS: In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. RESULTS: We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n < or = 15). For moderately sized samples (15 < n < or = 70), our simulations show that the formula range/4 is the best estimator for the standard deviation (variance). For large samples (n > 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. CONCLUSION: Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius. 1.

Although range expansions have occurred recurrently in the history of most species, their genetic consequences have been little investigated. Theoretical studies show that range expansions are quite different from pure demographic expansions and that the extent of recent gene flow conditions expected patterns of molecular diversity within and between populations. Spatially explicit simulation studies have led to unexpected and fascinating results about genetic patterns emerging after a range expansion. For instance, spatial expansions can generate allele frequency gradients, promote the surfing of rare variants into newly occupied territories, induce the structuring of newly colonized areas into distinct sectors of low genetic diversity, or lead to massive introgression of local genes into the genome of an invading species. Interestingly, most of these patterns had been previously attributed to distinct selective processes, showing that taking into account the dynamic nature of a species range can lead to a paradigm shift in our perception of evolutionary processes.

Common approximate exchange-correlation functionals suffer from self-interaction error, and as a result, their corresponding potentials have incorrect asymptotic behavior. The exact asymptote can be imposed by introducing range separation into the exchange component and replacing the long-range portion of the approximate exchange by the Hartree-Fock counterpart. The authors show that this long-range correction works particularly well in combination with the short-range variant of the Perdew-Burke-Ernzerhof (PBE) exchange functional. This long-range-corrected hybrid, here denoted LC-omegaPBE, is remarkably accurate for a broad range of molecular properties, such as thermochemistry, barrier heights of chemical reactions, bond lengths, and most notably, description of processes involving long-range charge transfer.

1. Species are shifting their ranges at an unprecedented rate through human transportation and environmental change. Correlative species distribution models (SDMs) are frequently applied for predicting potential future distributions of range-shifting species, despite these models’ assumptions that species are at equilibrium with the environments used to train (fit) the models, and that the training data are representative of conditions to which the models are predicted. Here we explore modelling approaches that aim to minimize extrapolation errors and assess predictions against prior biological knowledge. Our aim was to promote methods appropriate to range-shifting species. 2. We use an invasive species, the cane toad in Australia, as an example, predicting potential distributions under both current and climate change scenarios. We use four SDM methods, and trial weighting schemes and choice of background samples appropriate for species in a state of spread. We also test two methods for including information from a mechanistic model. Throughout, we explore graphical techniques for understanding model behaviour and reliability, including the extent of extrapolation. 3. Predictions varied with modelling method and data treatment, particularly with regard to the use and treatment of absence data. Models that performed similarly under current climatic conditions deviated widely when transferred to a novel climatic scenario. 4. The results highlight problems with using SDMs for extrapolation, and demonstrate the need for methods and tools to understand models and predictions. We have made progress in this direction and have implemented exploratory techniques as new options in the free modelling software, MaxEnt. Our results also show that deliberately controlling the fit of models and integrating information from mechanistic models can enhance the reliability of correlative predictions of species in non-equilibrium and novel settings. 5. Implications. The biodiversity of many regions in the world is experiencing novel threats created by species invasions and climate change. Predictions of future species distributions are required for management, but there are acknowledged problems with many current methods, and relatively few advances in techniques for understanding or overcoming these. The methods presented in this manuscript and made accessible in MaxEnt provide a forward step.

We present a method of recovering high dynamic range radiance maps from photographs taken with conventional imaging equipment. In our method, multiple photographs of the scene are taken with different amounts of exposure. Our algorithm uses these differently exposed photographs to recover the response function of the imaging process, up to factor of scale, using the assumption of reciprocity. With the known response function, the algorithm can fuse the multiple photographs into a single, high dynamic range radiance map whose pixel values are proportional to the true radiance values in the scene. We demonstrate our method on images acquired with both photochemical and digital imaging processes. We discuss how this work is applicable in many areas of computer graphics involving digitized photographs, including image-based modeling, image compositing, and image processing. Lastly, we demonstrate a few applications of having high dynamic range radiance maps, such as synthesizing realistic motion blur and simulating the response of the human visual system.

We propose a new long-range correction scheme that combines generalized-gradient-approximation (GGA) exchange functionals in density-functional theory (DFT) with the ab initio Hartree–Fock exchange integral by using the standard error function. To develop this scheme, we suggest a new technique that constructs an approximate first-order density matrix that corresponds to a GGA exchange functional. The calculated results of the long-range correction scheme are found to support a previous argument that the lack of the long-range interactions in conventional exchange functionals may be responsible for the underestimation of 4s−3d interconfigurational energies of the first-row transition metals and for the overestimation of the longitudinal polarizabilities of π-conjugated polyenes in DFT calculations.

Abstract No species occurs everywhere. Indeed, the majority are absent from most places, and where they do occur they are usually quite rare. Gaston discusses the structure of these distributions - the structure of the geographic ranges of species. Gaston is particularly concerned with the factors that determine the limits to a species’ geographic range, how the sizes of those ranges vary, and patterns in that variation. Also considered are the distribution of individuals amongst those sites where a species does occur and what determines that distribution, and some of the practical implications of all these. Both in a pure and applied context, ecologists need a broader perspective on their subject matter than has historically prevailed. This book provides one such perspective. A must have book for any researchers and graduate students studying macroecology, biogeography and conservation biology.

Low-temperature solution-processed photovoltaics suffer from low efficiencies because of poor exciton or electron-hole diffusion lengths (typically about 10 nanometers). Recent reports of highly efficient CH3NH3PbI3-based solar cells in a broad range of configurations raise a compelling case for understanding the fundamental photophysical mechanisms in these materials. By applying femtosecond transient optical spectroscopy to bilayers that interface this perovskite with either selective-electron or selective-hole extraction materials, we have uncovered concrete evidence of balanced long-range electron-hole diffusion lengths of at least 100 nanometers in solution-processed CH3NH3PbI3. The high photoconversion efficiencies of these systems stem from the comparable optical absorption length and charge-carrier diffusion lengths, transcending the traditional constraints of solution-processed semiconductors.

BACKGROUND: In patients with coronary heart disease and a broad range of cholesterol levels, cholesterol-lowering therapy reduces the risk of coronary events, but the effects on mortality from coronary heart disease and overall mortality have remained uncertain. METHODS: In a double-blind, randomized trial, we compared the effects of pravastatin (40 mg daily) with those of a placebo over a mean follow-up period of 6.1 years in 9014 patients who were 31 to 75 years of age. The patients had a history of myocardial infarction or hospitalization for unstable angina and initial plasma total cholesterol levels of 155 to 271 mg per deciliter. Both groups received advice on following a cholesterol-lowering diet. The primary study outcome was mortality from coronary heart disease. RESULTS: Death from coronary heart disease occurred in 8.3 percent of the patients in the placebo group and 6.4 percent of those in the pravastatin group, a relative reduction in risk of 24 percent (95 percent confidence interval, 12 to 35 percent; P<0.001). Overall mortality was 14.1 percent in the placebo group and 11.0 percent in the pravastatin group (relative reduction in risk, 22 percent; 95 percent confidence interval, 13 to 31 percent; P<0.001). The incidence of all cardiovascular outcomes was consistently lower among patients assigned to receive pravastatin; these outcomes included myocardial infarction (reduction in risk, 29 percent; P<0.001), death from coronary heart disease or nonfatal myocardial infarction (a 24 percent reduction in risk, P<0.001), stroke (a 19 percent reduction in risk, P=0.048), and coronary revascularization (a 20 percent reduction in risk, P<0.001). The effects of treatment were similar for all predefined subgroups. There were no clinically significant adverse effects of treatment with pravastatin. CONCLUSIONS: Pravastatin therapy reduced mortality from coronary heart disease and overall mortality, as compared with the rates in the placebo group, as well as the incidence of all prespecified cardiovascular events in patients with a history of myocardial infarction or unstable angina who had a broad range of initial cholesterol levels.

Three experimental techniques based on automatic swept-frequency network and impedance analysers were used to measure the dielectric properties of tissue in the frequency range 10 Hz to 20 GHz. The technique used in conjunction with the impedance analyser is described. Results are given for a number of human and animal tissues, at body temperature, across the frequency range, demonstrating that good agreement was achieved between measurements using the three pieces of equipment. Moreover, the measured values fall well within the body of corresponding literature data.

UBVRI photoelectric observations have been made on the Johnson-Kron-Cousins photometric system of 526 stars centered on the celestial equator. The program stars within a 298 number subset have sufficient measures so that they are capable of providing, for telescopes of intermediate and large size in both hemispheres, an internally consistent homogeneous broadband standard photometric system around the sky. The stars average 29 measures each on 19 nights. The majority of the stars in this paper fall in the magnitude range 11.5-16.0, and in the color range -0.3 to +2.3.

A general scheme for systematically modeling long-range corrected (LC) hybrid density functionals is proposed. Our resulting two LC hybrid functionals are shown to be accurate in thermochemistry, kinetics, and noncovalent interactions, when compared with common hybrid density functionals. The qualitative failures of the commonly used hybrid density functionals in some "difficult problems," such as dissociation of symmetric radical cations and long-range charge-transfer excitations, are significantly reduced by the present LC hybrid density functionals.

Tree taxa shifted latitude or elevation range in response to changes in Quaternary climate. Because many modern trees display adaptive differentiation in relation to latitude or elevation, it is likely that ancient trees were also so differentiated, with environmental sensitivities of populations throughout the range evolving in conjunction with migrations. Rapid climate changes challenge this process by imposing stronger selection and by distancing populations from environments to which they are adapted. The unprecedented rates of climate changes anticipated to occur in the future, coupled with land use changes that impede gene flow, can be expected to disrupt the interplay of adaptation and migration, likely affecting productivity and threatening the persistence of many species.