Environmental effects shape the maternal transfer of carotenoids and vitamin E to the yolk.

This is the final version of the article. Available from BioMed Central via the DOI in this record.UNLABELLED: INTRODUCTION: Maternal effects occur when the phenotype of the offspring is influenced by the phenotype of the mother, which in turn depends on her heritable state as well as on influences from the current and past environmental conditions. All of these pathways may, therefore, form significant sources of variation in maternal effects. Here, we focused on the maternal transfer of carotenoids and vitamin E to the egg yolk, using canaries as a model species. Maternal yolk carotenoids and vitamin E are known to generate significant phenotypic variation in offspring, representing examples of maternal effects. We studied the intra-individual consistency in deposition patterns across two years and the mother-daughter resemblance across two generations in order to estimate the level of heritable variation. The effects of the current environmental conditions were studied via a food supplementation experiment, while the consequences of past environmental conditions were estimated on the basis of the early growth trajectories. RESULTS: There was a significant effect of the current environmental conditions on the yolk carotenoid and vitamin E deposition, but this effect varied between antioxidant components. The deposition of yolk carotenoids and vitamin E were linked to the process of yolk formation. Past environmental conditions did not contribute to the variation in yolk carotenoid and vitamin E levels nor did we find significant heritable variation. CONCLUSIONS: The transfer of carotenoids or vitamin E may be an example where current environmental variation is largely passed from the mother to the offspring, despite the numerous intermediate physiological steps that are involved. Differences in the effect of the environmental conditions as experienced by the mother during laying may be due to differences in availability as well as physiological processes such as competitive exclusion or selective absorption.All experiments have been conducted according to Belgian legislation for animal experimentation (permit number 2006–19 and 2008–26). We thank Peter Scheys and Geert Eens for their assistance with taking care of the birds, and four anonymous reviewers provided valuable comments, which helped to improve the manuscript. WM was supported by FWO Flanders Belgium (1503307 and 1503307 N) and by the University of Antwerp (KP BOF UA 2006, 2008). JV by the Institute for the Promotion of Innovation through Science and Technology (IWT) in Flanders, ME was supported by the University of Antwerp and FWO Flanders. JDB was supported by a Royal Society University Research Fellowship

CLUSTERING OF WALL GEOMETRY FROM UNSTRUCTURED POINT CLOUDS

The automated reconstruction of Building Information Modeling (BIM) objects from point cloud data is still ongoing research. A key aspect is retrieving the proper observations for each object. After segmenting and classifying the initial point cloud, the labeled segments should be clustered according to their respective objects. However, this procedure is challenging due to noise, occlusions and the associativity between different objects. This is especially important for wall geometry as it forms the basis for further BIM reconstruction. In this work, a method is presented to automatically group wall segments derived from point clouds according to the proper walls of a building. More specifically, a Conditional Random Field is employed that evaluates the context of each observation in order to determine which wall it belongs too. The emphasis is on the clustering of highly associative walls as this topic currently is a gap in the body of knowledge. First a set of classified planar primitives is obtained using algorithms developed in prior work. Next, both local and contextual features are extracted based on the nearest neighbors and a number of seeds that are heuristically determined. The final wall clusters are then computed by decoding the graph and thus the most likely configuration of the observations. The experiments prove that the used method is a promising framework for wall clustering from unstructured point cloud data. Compared to a conventional region growing method, the proposed method significantly reduces the rate of false positives, resulting in better wall clusters. A key advantage of the proposed method is its capability of dealing with complex wall geometry in entire buildings opposed to the presented methods in current literature.</p

IMAGE RECORDING CHALLENGES FOR PHOTOGRAMMETRIC CONSTRUCTION SITE MONITORING

Construction site monitoring and progress monitoring is becoming increasingly popular in the architecture, engineering and construction (AEC) industry. To this end remote sensing techniques are used to gather consecutive datasets of the construction site. This work focuses on the recording of imagery for photogrammetric processing and the challenging conditions often encountered on construction sites. The constantly evolving character of a such sites requires datasets to be captured as quickly as possible. Furthermore other recording complexities arise such as the presence of auxiliary equipment and clutter or reflections caused by wet surfaces, hindering quick and complete recordings. Apart from these external factors also construction elements themselves often complicate the capturing workflow.This work enumerates several real-world examples of difficulties construction sites pose for the recording of imagery for photogrammetry purposes. Each section provides an insight in a specific challenge, typical for construction sites, and discusses applicable field-tested solutions including an overview of relevant solutions found in literature.</p

REVIEW OF WINDOW AND DOOR TYPE DETECTION APPROACHES

The use of as-built Building Information Models (BIM) has become increasingly commonplace. This process of creating a BIM model from point cloud data, also referred to as Scan-to-BIM, is a mostly manual task. Due to the large amount of manual work, the entire Scan-to-BIM process is time-consuming and error prone. Current research focuses on the automation of the Scan-to-BIM pipeline by applying state-of-the-art techniques on its consecutive steps including the data acquisition, data processing, data interpretation and modelling. By automating the matching and modelling of window and door objects, a considerable amount of time can be saved in the Scan-to-BIM process. This is so because each window and door instance needs to be examined by the modeller and must be adapted to the actual on-site situation. Large object libraries containing predefined window and door objects exists but the matching to the best-fit predefined object remains time consuming. The aim of this research is to examine the possibilities to speed up the modelling of window and door objects. First, a literature review discussing existing methods for window and door detection and matching is presented. Second, the acquired data is examined to explore the capabilities of capturing window and door information for different remote sensing devices. Followed by tests of some commonplace features in the use for window and door occurrence matching and clustering

3D modeling and registration under wide baseline conditions

During the 90s important progess has been made in the area of structure-from-motion. From a series of closely spaced images a 3D model of the observed scene can now be reconstructed, without knowledge about the subsequent camera positions or settings. From nothing but a video, the camera trajectory and scene shape are extracted. Progress has also been important in the area of structured light techniques. Rather than having to use slow and/or bulky laser scanners, compact one-shot systems have been developed. Upon projection of a pattern onto the scene, its 3D shape and texture can be extracted from a single image. This paper presents recent extensions on both strands, that have a common theme: how to cope with large baseline conditions. In the case of shape-from-video we discuss ways to find correspondences and, hence, extract 3D shapes even when the images are taken far apart. In the case of structured light, the problem solved is how to combine partial 3D patches into complete models, without a good initialisation of their relative poses.

Wheat genotypic variation in dynamic fluxes of WSC components in different stem segments under drought during grain filling

In wheat, stem water soluble carbohydrates (WSC), composed mainly of fructans, are the major carbon sources for grain filling during periods of decreasing photosynthesis or under drought stress after anthesis. Here, in a field drought experiment, WSC levels and associated enzyme activities were followed in different stem segments (peduncle, penultimate internode, lower parts of stem, and sheath) during grain filling. The focus was on two double haploid (DH) lines, DH 307 and DH 338, derived from a Westonia/Kauz cross, two drought-tolerant wheat varieties that follow different drought adaptation strategies during grain filling. The results showed that in irrigated plants, in the period between 20 and 30 days after anthesis (DAA), 70–80% of WSC were fructans. Before and after this period, the fructan proportion varied from 10 to 60%, depending on the location along the stem. Under drought, the fructan proportion changed, depending on genotype, and developmental stages. After anthesis, stem fructans accumulation occurred mainly in the peduncle and penultimate internode until 14 DAA in both DH lines, with clear genotypic variation in subsequent fructan degradation under drought. In DH 307 a significant reduction of fructans with a concomitant increase in fructose levels occurred earlier in the lower parts of the stem and the sheath, as compared to DH 338 or other stem segments in both lines. This was associated with an earlier increase of grain weight and thousand grain weight in DH 307. Spatiotemporal analysis of fructan dynamics and enzymatic activities in fructan metabolism revealed that several types of FEHs are involved in fructan remobilization to the grain under drought