Characterisation of Certain Split-Block Designs with a Control

The paper deals with an incomplete split-block design in which one or two factors are split into two parts, the first one containing test treatments and the second one — a control treatment. The aim of the experiment carried out in such design is to compare the average of the test treatment effects with the control treatment effect and the test treatment effects with the control treatment effect individually. All those comparisons can be expressed by contrasts, elementary or basic ones. The aim of the paper is to characterise particular cases of the incomplete split-block designs with respect to general balance and to efficiency factors of the design with respect to the contrasts. In the paper we restrict our attention to the designs in which each block has two rows or/and two columns only. These designs are suitable for certain agricultural experiments.     

Blinded sample size recalculation in adaptive enrichment designs

In the precision medicine era, (prespecified) subgroup analyses are an integral part of clinical trials. Incorporating multiple populations and hypotheses in the design and analysis plan, adaptive designs promise flexibility and efficiency in such trials. Adaptations include (unblinded) interim analyses (IAs) or blinded sample size reviews. An IA offers the possibility to select promising subgroups and reallocate sample size in further stages. Trials with these features are known as adaptive enrichment designs. Such complex designs comprise many nuisance parameters, such as prevalences of the subgroups and variances of the outcomes in the subgroups. Additionally, a number of design options including the timepoint of the sample size review and timepoint of the IA have to be selected. Here, for normally distributed endpoints, we propose a strategy combining blinded sample size recalculation and adaptive enrichment at an IA, that is, at an early timepoint nuisance parameters are reestimated and the sample size is adjusted while subgroup selection and enrichment is performed later. We discuss implications of different scenarios concerning the variances as well as the timepoints of blinded review and IA and investigate the design characteristics in simulations. The proposed method maintains the desired power if planning assumptions were inaccurate and reduces the sample size and variability of the final sample size when an enrichment is performed. Having two separate timepoints for blinded sample size review and IA improves the timing of the latter and increases the probability to correctly enrich a subgroup.     

Adaptive designs with arbitrary dependence structure

Adaptive designs were originally developed for independent and uniformly distributed p‐values. There are trial settings where independence is not satisfied or where it may not be possible to check whether it is satisfied. In these cases, the test statistics and p‐values of each stage may be dependent. Since the probability of a type I error for a fixed adaptive design depends on the true dependence structure between the p‐values of the stages, control of the type I error rate might be endangered if the dependence structure is not taken into account adequately. In this paper, we address the problem of controlling the type I error rate in two‐stage adaptive designs if any dependence structure between the test statistics of the stages is admitted (worst case scenario). For this purpose, we pursue a copula approach to adaptive designs. For two‐stage adaptive designs without futility stop, we derive the probability of a type I error in the worst case, that is for the most adverse dependence structure between the p‐values of the stages. Explicit analytical considerations are performed for the class of inverse normal designs. A comparison with the significance level for independent and uniformly distributed p‐values is performed. For inverse normal designs without futility stop and equally weighted stages, it turns out that correcting for the worst case is too conservative as compared to a simple Bonferroni design.     

A comparison of experimental designs for selection in breeding trials with nested treatment structure

Plant breeders frequently evaluate large numbers of entries in field trials for selection. Generally, the tested entries are related by pedigree. The simplest case is a nested treatment structure, where entries fall into groups or families such that entries within groups are more closely related than between groups. We found that some plant breeders prefer to plant close relatives next to each other in the field. This contrasts with common experimental designs such as the α-design, where entries are fully randomized. A third design option is to randomize in such a way that entries of the same group are separated as much as possible. The present paper compares these design options by simulation. Another important consideration is the type of model used for analysis. Most of the common experimental designs were optimized assuming that the model used for analysis has fixed treatment effects. With many entries that are related by pedigree, analysis based on a model with random treatment effects becomes a competitive alternative. In simulations, we therefore study the properties of best linear unbiased predictions (BLUP) of genetic effects based on a nested treatment structure under these design options for a range of genetic parameters. It is concluded that BLUP provides efficient estimates of genetic effects and that resolvable incomplete block designs such as the α-design with restricted or unrestricted randomization can be recommended.     

On the PBB Designs for Multiresponse Experiments

We present the idea of using multiresponse incomplete block designs when not all responses can be observed in all experimental units. For a special class of such designs, in which partial designs are PBB designs, a method for estimating natural treatment contrast is given. We also consider the problem of testing the hypotheses concerning the natural and any estimable treatment contrasts. For testing this hypothesis the Wald statistics, being asymptotically chi-square distributed, is proposed.     

Why are fruits colorful? The relative importance of achromatic and chromatic contrasts for detection by birds

The colors of fruits and flowers are traditionally viewed as an adaptation to increase the detectability of plant organs to animal vectors. The detectability of visual signals increases with increasing contrasts between target and background. Contrasts consist of a chromatic aspect (color) and an achromatic aspect (light intensity), which are perceived separately by animals. To evaluate the relative importance of fruits’ chromatic and achromatic contrasts for the detection by avian fruit consumers we conducted an experiment with artificial fruits of four different colors in a tropical forest. We displayed the fruits against two different backgrounds, an artificial background and a natural one, because they differed in achromatic properties. We found no effect of the type of background on fruit detection rates. Detection rates differed for the four fruit colors. The probability of detection was explained by the chromatic contrast between fruits and their background, not by the achromatic contrasts. We suggest that birds attend primarily to chromatic contrast probably because these are more reliably detected under variable light conditions. Consistent with this hypothesis, we found habitat-specific differences in the conspicuousness of natural fruit colors in the study area. Fruits of understory species that are subjected to the variable light conditions within a forest displayed higher chromatic contrasts than species growing in the open restinga forest with constant bright illumination. There was no such difference for achromatic contrasts. In sum, we suggest that fruit colors differ between habitats because fruit colors that have strong chromatic contrasts against background can increase plants’ reproductive success, particularly under variable light conditions.     

Temporal variation in nest predation risk along habitat edges between grassland and secondary forest in Central Europe

Habitat fragmentation alters many ecological processes, including trophic cascades. For example, increased predation pressure along habitat edges has often been observed in fragmented landscapes. Here, we studied how nest predation risk varies along the transition zone between grassland and mixed forest in Central Europe. Using artificial nests, we tested the two mechanisms that are expected to underlie higher predation rates along edges: (1) the matrix effect model that supposes predator penetration from a habitat type with higher predator density to one with lower predator density and (2) the ecotonal effect model that assumes specific predator preferences for habitat edges. Although our results do not fully support either of these scenarios, our data show high temporal instability in nest predation along forest–grassland edges. Predation was higher in habitat interiors compared to edges during the first year, whereas the opposite pattern was observed during the subsequent year. In addition, dramatic between-year differences in the species composition of nest predators were observed. Therefore, we hypothesise that the effect of edges on nest predation is difficult to predict in landscapes with high predator diversity. In addition, our data indicate that a high abundance of wild boar considerably increases the risk of predation for ground-nesting birds.     

Optimal design of genetic studies of gene expression with two-color microarrays in outbred crosses

Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the “distant pair design” maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the “optimal pair design,” for use with F₂ crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance.     

A Distribution-Free Multi-Factorial Profiler for Harvesting Information from High-Density Screenings

Data screening is an indispensable phase in initiating the scientific discovery process. Fractional factorial designs offer quick and economical options for engineering highly-dense structured datasets. Maximum information content is harvested when a selected fractional factorial scheme is driven to saturation while data gathering is suppressed to no replication. A novel multi-factorial profiler is presented that allows screening of saturated-unreplicated designs by decomposing the examined response to its constituent contributions. Partial effects are sliced off systematically from the investigated response to form individual contrasts using simple robust measures. By isolating each time the disturbance attributed solely to a single controlling factor, the Wilcoxon-Mann-Whitney rank stochastics are employed to assign significance. We demonstrate that the proposed profiler possesses its own self-checking mechanism for detecting a potential influence due to fluctuations attributed to the remaining unexplainable error. Main benefits of the method are: 1) easy to grasp, 2) well-explained test-power properties, 3) distribution-free, 4) sparsity-free, 5) calibration-free, 6) simulation-free, 7) easy to implement, and 8) expanded usability to any type and size of multi-factorial screening designs. The method is elucidated with a benchmarked profiling effort for a water filtration process.     

Forest edge contrasts have a predictable effect on the spatial distribution of carabid beetles in urban forests

Fragmented urban forest remnants are characterised by sharp edges and are bordered by various land-use types, which may have a considerable effect on the fauna and flora at forest edges, and into forest interiors. To investigate the effects of differentially contrasting edges (low vs. intermediate vs. high) on carabid beetle assemblages in urban boreal forests, we placed pitfall traps along a gradient from 6?m into three matrix types (secondary forest vs. grassland vs. asphalt) up to 60?m into urban forest patches in the cities of Vantaa and Helsinki, southern Finland. Individual species and carabid beetle assemblages were strongly affected by edge contrasts and distance from the forest edge. The strongest effect on individual species was caused by high contrasting edges: generalist and open-habitat species were favoured or not affected while forest specialists were affected negatively. Effects of the abundances of potential prey and competitors on the carabid beetles were also evaluated. Forest and moisture-associated carabid species were negatively to neutrally associated with springtail abundances while generalist and open habitat, and dryness associated species were more positively related to springtail abundances (a potential food source). In terms of potential competitors, forest and moisture-associated carabid species were negatively and/or neutrally affected by ant and wood ant numbers, while generalist and open-habitat species were neutrally to positively associated with these taxa. It appears that carabid beetle habitat associations are more important in the responses of these beetles across edges of different contrast than are the prey and competitor numbers collected there. We recommend the creation of “soft” or low-contrast urban edges if the aim of urban management is to protect forest carabids in cities.     

Motion edges and regions guide image segmentation by colour.

Image segmentation is an important early stage in visual processing in which the visual system groups together parts of the image that belong together, prior to or in conjunction with object recognition. Two principal processes may be involved in image segmentation: an edge-based process that uses feature contrasts to mark boundaries of coherent regions, and a region-based process that groups similar features over a larger scale. Earlier, we have shown that motion and colour interact strongly in image segmentation by the human visual system. Here we explore the nature of this interaction in terms of edge- and region-based processes. We measure performance on a region-based colour segmentation task in the presence of distinct types of motion information, in the form of edges and regions which in themselves do not reveal the location of the colour target. The results show that both motion edges and regions may guide the integrative process required for this colour segmentation task. Motion edges appear to act by delimiting areas over which to integrate colour information, whereas motion similarities define primitive surfaces within which colour grouping and segmentation processes are deployed.     

Species-specific distribution of two sympatric Maculinea butterflies across different meadow edges

An important consequence of habitat fragmentation is the increase of edge habitats. Environmental factors in the edges are different from those in the interiors, which causes changes in the distribution of plant and animal species. We aimed to study how edges affect the distribution of two butterfly species within meadow fragments. We therefore investigated the effect of distance from edge and edge type (road edge versus tree edge) on two sympatric large blue species (Maculinea teleius and M. nausithous). Our results showed that edge type had contrasting effects on the two species. M. teleius favoured both interiors and road edges, while M. nausithous preferred the tree edges. In the case of the latter species a strong positive edge effect was also found. This kind of within-habitat niche segregation is probably related to the different microenvironmental conditions at the edges. Foodplant density did not seem to limit the distribution of these species. Our results suggest that interiors of meadows are important for M. teleius, while tree edges maintain the habitats of the regionally rarer butterfly, M. nausithous.     

Test‐compatible confidence intervals for adaptive two‐stage single‐arm designs with binary endpoint

Inference after two‐stage single‐arm designs with binary endpoint is challenging due to the nonunique ordering of the sampling space in multistage designs. We illustrate the problem of specifying test‐compatible confidence intervals for designs with nonconstant second‐stage sample size and present two approaches that guarantee confidence intervals consistent with the test decision. Firstly, we extend the well‐known Clopper–Pearson approach of inverting a family of two‐sided hypothesis tests from the group‐sequential case to designs with fully adaptive sample size. Test compatibility is achieved by using a sample space ordering that is derived from a test‐compatible estimator. The resulting confidence intervals tend to be conservative but assure the nominal coverage probability. In order to assess the possibility of further improving these confidence intervals, we pursue a direct optimization approach minimizing the mean width of the confidence intervals. While the latter approach produces more stable coverage probabilities, it is also slightly anti‐conservative and yields only negligible improvements in mean width. We conclude that the Clopper–Pearson‐type confidence intervals based on a test‐compatible estimator are the best choice if the nominal coverage probability is not to be undershot and compatibility of test decision and confidence interval is to be preserved.     

Parallel evolution of drug resistance in HIV: failure of nonsynonymous/synonymous substitution rate ratio to detect selection.

Parallel or convergent evolution at the molecular level has been difficult to demonstrate especially when rigorous statistical criteria are applied. We present sequence data from the protease gene from eight patients infected with the human immunodeficiency virus (HIV-1). These patients have been on multiple drug therapies for at least 2 years. We present sequence data from two timepoints: time zero--the initiation of drug therapy--and a subsequent timepoint between 59 and 104 weeks after the initiation of drug therapy. In addition to the sequence data, we present viral load data from both initial and final timepoints. Our phylogenetic analyses indicate significant evolution of virus from initial to final time points, even in three of eight patients who show low viral loads. Of the five patients who escaped drug therapy, identical amino acid replacements were seen in all five patients at two different codon positions, an indication of parallel evolution. We also measured genetic diversity for these patients and found no correlation between genetic diversity and viral load. Finally, we calculated the nonsynonymous and synonymous substitution rates and showed that the ratio of nonsynonymous to synonymous substitution compared to the value of one may be a poor indicator of natural selection.     

Moving and stationary actin filaments are involved in spreading of postmitotic PtK2 cells

We have investigated spreading of postmitotic PtK2 cells and the behavior of actin filaments in this system by time-lapse microscopy and photoactivation of fluorescence. During mitosis PtK2 cells round up and at cytokinesis the daughter cells spread back to regain their interphase morphology. Normal spreading edges are quite homogenous and are not comprised of two distinct areas (lamellae and lamellipodia) as found in moving edges of interphase motile cells. Spreading edges are connected to a network of long, thin, actin-rich fibers called retraction fibers. A role for retraction fibers in spreading was tested by mechanical disruption of fibers ahead of a spreading edge. Spreading is inhibited over the region of disruption, but not over neighboring intact fibers. Using photoactivation of fluorescence to mark actin filaments, we have determined that the majority of actin filaments move forward in spreading edges at the same rate as the edge. As far as we are aware, this is the first time that forward movement of a cell edge has been correlated with forward movement of actin filaments. In contrast, actin filaments in retraction fibers remain stationary with respect to the substrate. Thus there are at least two dynamic populations of actin polymer in spreading postmitotic cells. This is supported by the observation that actin filaments in some spreading edges not only move forward, but also separate into two fractions or broaden with time. A small fraction of postmitotic cells have a spreading edge with a distinct lamellipodium. In these edges, marked actin polymer fluxes backward with respect to substrate. We suggest that forward movement of actin filaments may participate in generating force for spreading in postmitotic cells and perhaps more generally for cell locomotion.     

Input-output transformation in the visuo-oculomotor loop: comparison of real-time optical imaging recordings in V1 to ocular following responses upon center-surround stimulation

In psychophysics and physiology, it is well established that lateral interactions are crucial mechanisms to constrain response normalization and contextual modulations. To study the cortical mechanisms involved in the contextual modulation of the behavioral contrast response function, we compared in behaving monkeys the Ocular Following Response (OFR) to V1 population activity measured using Optical Imaging of Voltage-Sensitive Dyes (VSD). If contrast response functions (CRF) to a simple local stimulus are similar in V1 and in the OFR, lateral interaction leads however to quite different modulation at those two levels. At the behavioural level, contrast response function is strongly suppressed by lateral interactions, and this suppression is stronger for higher contrasts. In V1, we showed a slow dynamic of facilitation for low contrasts integration and a fast suppression operating on high contrasts. These modulatory interactions influence differently the contrast response functions, interrupting the dynamic increase of contrast sensitivity in OFR, but not in V1 response. The temporal properties of those effects lead us to hypothesize that horizontal and feedback connectivity have differential effect on low and high contrasts integration in V1. V1 provides then an input to MT whose contextual dependency is not totally determined and must be refined before affecting the behavioural OFR.     

Application of repeated measures designs in environmental impact and monitoring studies

Abstract Traditional environmental studies have employed sampling at different times, but based on re-randomized ‘replicate’ samples taken at each time. For example, in a 4 year monitoring study of near-shore marine benthic communities there might be three box cores collected annually at each of three depths along each of three transects. Repeated measures designs, long used in medicine and the social sciences, are based on resampling replicates (e.g. sites) at a series of times. In such designs spatial sampling variability is not used for tests of environmental impact. Error for such tests is based on variability of time trends among similar sites (similar with respect to impact). For example in a tropical oil spill study five oiled and five unoiled coral reefs were studied over 5 years. Error for tests of oil impact was based on variability among reefs (within degree-of-oiling category) in the year-to-year trends of biological response variables. It was not based on variability among field samples within reefs at given times. The two approaches (univariate and multivariate) to repeated measures analysis of variance are described. The pros and cons of each are discussed, as are the assumptions and consequences of their violations. Emphasis is especially placed on the adequacy of error degrees of freedom in the two approaches, and some exploration of power to detect impact is presented. Examples of application of repeated measures designs to various impact and monitoring studies are presented and discussed, including (i) interpretation of significant effects; (ii) decomposition of effects by contrasts (e.g. before vs after impact); and (iii) modelling time trends by polynomial and cosine functions.     

Dark nests and conspicuousness in color patterns of nestlings of altricial birds

Nests of altricial birds exhibit variable spectral properties that may affect the efficacy (conspicuousness) of the colored begging traits that a nestling displays to its parents. Here we explored whether selection for efficient perception has favored the evolution of nestling color designs that maximizes nestling detectability in variable light environments. Visual models were used to estimate how parents perceive the coloration of mouths, flanges, heads, and breasts of nestlings within their nest in 21 species of European birds. We show that the largest chromatic and achromatic contrasts against the nest background appeared for nestling mouths and flanges, respectively. Nestlings of open-nesting species showed a larger general achromatic contrast with the nest than did nestlings of hole-nesting species. However, nestlings of hole nesters showed a more evident achromatic contrast between flanges and other traits than did nestlings of open nesters. In addition, species with larger clutch sizes showed larger general achromatic contrasts with the nest. Gaping traits of open-nesting species contrasting with the nest background were better perceived under rich light regimes than under poor ones. These findings are consistent with a scenario in which selection for nestling detectability in dark environments has favored the evolution of particular achromatic components of gape coloration but also nestling traits that enhance signal efficacy by maximizing color contrasts within a nestling.     

Statistical analysis of noninferiority trials with a rate ratio in small-sample matched-pair designs

Testing of noninferiority has become increasingly important in modern medicine as a means of comparing a new test procedure to a currently available test procedure. Asymptotic methods have recently been developed for analyzing noninferiority trials using rate ratios under the matched-pair design. In small samples, however, the performance of these asymptotic methods may not be reliable, and they are not recommended. In this article, we investigate alternative methods that are desirable for assessing noninferiority trials, using the rate ratio measure under small-sample matched-pair designs. In particular, we propose an exact and an approximate exact unconditional test, along with the corresponding confidence intervals based on the score statistic. The exact unconditional method guarantees the type I error rate will not exceed the nominal level. It is recommended for when strict control of type I error (protection against any inflated risk of accepting inferior treatments) is required. However, the exact method tends to be overly conservative (thus, less powerful) and computationally demanding. Via empirical studies, we demonstrate that the approximate exact score method, which is computationally simple to implement, controls the type I error rate reasonably well and has high power for hypothesis testing. On balance, the approximate exact method offers a very good alternative for analyzing correlated binary data from matched-pair designs with small sample sizes. We illustrate these methods using two real examples taken from a crossover study of soft lenses and a Pneumocystis carinii pneumonia study. We contrast the methods with a hypothetical example.     

Fuzzy Index to Evaluate Edge Detection in Digital Images

In literature, we can find different metrics to evaluate the detected edges in digital images, like Pratt''s figure of merit (FOM), Jaccard’s index (JI) and Dice’s coefficient (DC). These metrics compare two images, the first one is the reference edges image, and the second one is the detected edges image. It is important to mention that all existing metrics must binarize images before their evaluation. Binarization step causes information to be lost because an incomplete image is being evaluated. In this paper, we propose a fuzzy index (FI) for edge evaluation that does not use a binarization step. In order to process all detected edges, images are represented in their fuzzy form and all calculations are made with fuzzy sets operators and fuzzy Euclidean distance between both images. Our proposed index is compared to the most used metrics using synthetic images, with good results.