Reconstrucción digital de estructuras de tejados históricos: desarrollo de un flujo de trabajo de análisis altamente automatizado

[EN] Planning on adaptive reuse, maintenance and restoration of historic timber structuresrequiresextensive architectural and structural analysis of the actual condition. Current methods for a modellingof roof constructions consist of several manual steps including the time-consuming dimensional modelling. The continuous development of terrestrial laser scanners increases the accuracy, comfort and speed of the surveying work inroof constructions. Resultingpoint clouds enabledetailed visualisation of theconstructionsrepresented by single points or polygonal meshes, but in fact donot containinformation about the structural system and the beam elements. The developed workflow containsseveral processing steps on the point cloud dataset. The most important among them arethenormal vector computation, the segmentation of points to extract planarfaces, a classification of planarsegmentsto detect the beam side facesand finally theparametric modelling of the beams on the basis of classified segments. Thisenablesa highly automated transitionfrom raw point cloud data to a geometric model containing beams of the structural system. The geometric model,as well as additional information about the structural properties of involved wooden beams and their joints,is necessaryinput for a furtherstructural modellingof timber constructions. The results of the workflow confirm that the proposed methods work well for beams with a rectangularcross-section and minor deformations. Scan shadows and occlusionof beamsby additional installationsor interlockingbeamsdecreases the modelling performance, but in generala high level ofaccuracy and completeness isachieved ata high degree of automation.[ES] Las estructuras históricas de madera requieren un análisis arquitectónico y estructural exhaustivo de su condición real en aras de planificar la reutilización flexible, el mantenimiento y la restauración. Los métodos actuales que modelan las construcciones de cubiertas pasan por aplicar varias etapas en modo manual, que incluye el lento modelado dimensional. El desarrollo continuo de escáneres láser terrestres aumenta la exactitud, la comodidad y la velocidad del trabajo topográfico en construcciones de tejados. Las nubes de puntos resultantes permiten la visualización detallada de las construcciones representadas por puntos o mallas poligonales, pero de hecho no contienen información sobre el sistema estructural y los elementos del travesaño. El flujo de trabajo desarrollado contiene varias etapas de procesamiento en el conjunto de datos de la nube de puntos. Los más importantes son el cálculo del vector normal, la segmentación de puntos que extraen caras planas, la clasificación de segmentos planos que detectan las caras laterales del travesaño y, finalmente, el modelado paramétrico de los travesaños en función de los segmentos clasificados. Esto permite una transición altamente automatizada de los datos de la nube de puntos brutos a un modelo geométrico que contiene los travesaños del sistema estructural. El modelo geométrico, así como la información adicional sobre las propiedades estructurales de las vigas de madera involucradas y de sus juntas, es información necesaria de entrada para el modelado estructural eventual de las construcciones de madera. Los resultados del flujo de trabajo confirman que los métodos propuestos funcionan bien en travesaños que presentan secciones transversales rectangulares y deformaciones menores. Las sombras en los escaneados y las oclusiones de los travesaños a partir de instalaciones adicionales o vigas entrelazados disminuye el rendimiento del modelado, pero en general se logra un nivel de exactitud e integridad elevado con un alto grado de automatización.Pöchtrager, M.; Styhler-Aydın, G.; Döring-Williams, M.; Pfeifer, N. (2018). Digital reconstruction of historic roof structures: developing a workflow for a highly automated analysis. Virtual Archaeology Review. 9(19):21-33. doi:10.4995/var.2018.8855SWORD2133919Attene, M., & Spagnuolo, M. (2000). Automatic surface reconstruction from point sets in space. Computer Graphics Forum, 19(3), 457-465. doi:10.1111/1467-8659.00438Baik, A., Yaagoubi, R., & Boehm, J. (2015). Integration of Jeddah historical BIM and 3D GIS for documentation and restoration of historical monument. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-5/W7, 29-34. doi:10.5194/isprsarchives-XL-5-W7-29-2015Bassier, M., Hadjidemetriou, G., Vergauwen, M., Van Roy, N., & Verstrynge, E. (2016). Implementation of Scan-to-BIM and FEM for the Documentation and Analysis of Heritage Timber Roof Structures. In M. Ioannides, E. Fink, A. Moropoulou, M. Hagedorn-Saupe, A. Fresa, G. Liestøl, . . . P. Grussenmeyer (Ed.), Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2016 (pp. 79-90). Springer, Cham. doi:10.1007/978-3-319-48496-9_7Besl, P., & McKay, N. (1992). A method for registration of 3D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-254. doi:10.1109/34.121791Chida, A., & Masuda, H. (2016). Reconstruction of polygonal prisms from point-clouds of engineering facilities. Journal of Computational Design and Engineering, 3(4), 322-329. doi:10.1016/j.jcde.2016.05.003Dore, C., & Murphy, M. (2017). Current state of the art historic building information modelling. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W5, 185-192. doi:10.5194/isprsarchives-XLII-2-W5-185-2017Dorninger, P., Nothegger, C., & Rasztovits, S. (2013). Efficient 3-D documentation of Neptune fountain in the park of Schönbrunn palace at millimeter scale. Proceedings XXIV International CIPA Symposium, ISPRS Annals, II, 5/W1, 103-108. doi:10.5194/isprsannals-II-5-W1-103-2013Eßer, G., Styhler-Aydın, G., & Hochreiner, G. (2016a). Construction history and structural assessment of historic roofs - An interdisciplinary approach. In K. Van Balen, & E. Verstrynge (Eds.), Structural analysis of historical constructions. Anamnesis, diagnosis, therapy, controls (pp. 790-795). London, GB.Eßer, G., Styhler-Aydın, G., & Hochreiner, G. (2016b). The historic roof structures of the Vienna Hofburg: An innovative interdisciplinary approach in architectural sciences laying ground for structural modeling. In J. Eberhardsteiner, W. Winter, A. Fadai, & M. Pöll (Eds.), WCTE 2016. World conference on timber engineering (pp. 3039-3047). Wien, Austria.Fischler, M., & Bolles, R. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381-395. doi:10.1145/358669.358692Glira, P., Pfeifer, N., Briese, C., & Ressl, C. (2015). A Correspondence Framework for ALS Strip Adjustments based on Variants of the ICP Algorithm. Photogrammetrie, Fernerkundung, Geoinformation, 4, 275-289. doi:10.1127/pfg/2015/0270Hochreiner, G., Eßer, G., & Styhler-Aydın, G. (2016). Modern timber engineering methods in the context of historical timber structures. In J. Eberhardsteiner, W. Winter, A. Fadai, & M. Pöll (Eds.), WCTE 2016. World conference on timber engineering (pp. 4830-4838). Wien, Austria.Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., & Stuetzle, W. (1992). Surface reconstruction from unorganized points. SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques. ACM SIGGRAPH Computer Graphics, 26(2), 71-78. doi:10.1145/142920.134011International Organization for Standardization. (2016). Industrial automation systems and integration -- Product data representation and exchange -- Part 21: Implementation methods: Clear text encoding of the exchange Structure. ISO/DIS Standard No. 10303-21. Retrieved from https://www.iso.org/standard/63141.html.Jung, J., Hong, S., Jeong, S., Kim, S., Cho, H., Hong, S., & Heo, J. (2014). Productive modeling for development of asbuilt BIM of existing indoor structures. Automation in Construction, 42, 68-77. doi:10.1016/j.autcon.2014.02.021Kazhdan, M., Bolitho, M., & Hoppe, H. (2006). Poisson surface reconstruction. Symposium on Geometry Processing (pp. 61-70). The Eurographics Association. doi:10.2312/SGP/SGP06/061-070Lee, J., Son, H., Kim, C., & Kim, C. (2013). Skeleton-based 3-D reconstruction of as-built pipelines from laser-scan data. Automation in Reconstruction, 35, 199-207. doi:10.1061/9780784412343.0031Li, W., Goodchild, M., & Church, R. (2013). An efficient measure of compactness for two-dimensional shapes and its application in regionalization problems. International Journal of Geographical Information Science, 1227-1250. doi:10.1080/13658816.2012.752093Nothegger, C., & Dorninger, P. (2009). 3D filtering of high-resolution terrestrial laser scanner point clouds for cultural heritage documentation. Photogrammetrie, Fernerkundung, Geoinformation, 1, 53-63. doi:10.1127/0935-1221/2009/0006Pfeifer, N., & Winterhalder, D. (2004). Modelling of tree cross sections from terrestrial laser scanning data with free-form curves. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(8/W2), 76-81.Pfeifer, N., Mandlburger, G., Otepka, J., & Karel, W. (2014). OPALS - A framework for Airborne Laser Scanning data analysis. Computers, Environment and Urban Systems, 45, 125-136. doi:10.1016/j.compenvurbsys.2013.11.002Pöchtrager, M., Styhler-Aydın, G., Döring-Williams, M., & Pfeifer, N. (2017). Automated Reconstruction of Historic Roof Structures from Point Clouds - Development and Examples. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2-W2, 195-202. doi:10.5194/isprs-annals-IV-2-W2-195-2017Rabbani, T., Dijkman, S., Van den Heuvel, F., & Vosselman, G. (2007). An integrated approach for modelling and global registration of point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 61(6), 355-370. doi:10.1016/j.isprsjprs.2006.09.006Raumonen, P., Kaasalainen, M., Åkerblom, M., Kaasalainen, S., Kaartinen, H., Vastaranta, M., . . . Lewis, P. (2013). Fast automatic precision tree models from terrestrial laser scanner data. Remote Sensing, 5(2), 491-520. doi:10.3390/rs5020491Stylianidis, E., & Remondino, F. (2016). 3D Recording, Documentation and Management of Cultural Heritage. Caithness, UK: Whittles Publishing.Thies, M., Pfeifer, N., Winterhalder, D., & Gorte, B. (2004). Three-dimensional reconstruction of stems for assessment of taper, sweep and lean based on laser scanning of standing trees. Scandinavian Journal of Forest Research, 19(6), 571-581. doi:10.1080/02827580410019562Thomson, C., & Boehm, J. (2015). Automatic geometry generation from point clouds for BIM. Remote Sensing, 7(9), 11753-11775. doi:10.3390/rs70911753Vosselman, G., & Maas, H.-G. (2010). Airborne and Terrestrial Laser Scanning. Caithness, UK: Whittles Publishing.Wang, D., Hollaus, M., Puttonen, E., & Pfeifer, N. (2016). Automatic and self-adaptive stem reconstruction in landslide-affected forests. Remote Sensing, 8(12), p. 974. doi:10.3390/rs8120974Wang, D., Kankare, V., Puttonen, E., Hollaus, M., & Pfeifer, N. (2016). Reconstructing stem cross section shapes from terrestrial laser scanning. IEEE Geoscience and Remote Sensing Letters, 14(2), 272-276. doi:10.1109/LGRS.2016.2638738Xiong, X., Adan, A., Akinci, B., & Huber, D. (2013). Automatic creation of semantically rich 3D building models from laser scanner data. Automation in Construction, 31, S. 325-337. doi:10.1016/j.autcon.2012.10.006Yang, X., Koehl, M., & Grussenmeyer, P. (2017). Parametric modelling of as-built beam framed structure in BIM environment. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W3, 651-657. doi:10.5194/isprs-archives-XLII-2-W3-651-2017Zhang, R., & Zakhor, A. (2014). Automatic identification of window regions on indoor point clouds using LiDAR and cameras. Applications of Computer Vision (WACV), 2014 IEEE Winter Conference, 107-114. doi:10.1109/WACV.2014.683611

vasa is required for GURKEN accumulation in the oocyte, and is involved in oocyte differentiation and germline cyst development

Skip to Next Section The Drosophila gene vasa is required for pole plasm assembly and function, and also for completion of oogenesis. To investigate the role of vasa in oocyte development, we generated a new null mutation of vasa, which deletes the entire coding region. Analysis of vasa-null ovaries revealed that the gene is involved in the growth of germline cysts. In vasa-null ovaries, germaria are atrophied, and contain far fewer developing cysts than do wild-type germaria; a phenotype similar to, but less severe than, that of a null nanos allele. The null mutant also revealed roles for vasa in oocyte differentiation, anterior-posterior egg chamber patterning, and dorsal-ventral follicle patterning, in addition to its better-characterized functions in posterior embryonic patterning and pole cell specification. The anterior-posterior and dorsal-ventral patterning phenotypes resemble those observed in gurken mutants. vasa-null oocytes fail to efficiently accumulate many localized RNAs, such as Bicaudal-D, orb, oskar, and nanos, but still accumulate gurken RNA. However, GRK accumulation in the oocyte is severely reduced in the absence of vasa function, suggesting a function for VASA in activating gurken translation in wild-type ovaries

AUTOMATED RECONSTRUCTION OF HISTORIC ROOF STRUCTURES FROM POINT CLOUDS – DEVELOPMENT AND EXAMPLES

The analysis of historic roof constructions is an important task for planning the adaptive reuse of buildings or for maintenance and restoration issues. Current approaches to modeling roof constructions consist of several consecutive operations that need to be done manually or using semi-automatic routines. To increase efficiency and allow the focus to be on analysis rather than on data processing, a set of methods was developed for the fully automated analysis of the roof constructions, including integration of architectural and structural modeling. Terrestrial laser scanning permits high-detail surveying of large-scale structures within a short time. Whereas 3-D laser scan data consist of millions of single points on the object surface, we need a geometric description of structural elements in order to obtain a structural model consisting of beam axis and connections. Preliminary results showed that the developed methods work well for beams in flawless condition with a quadratic cross section and no bending. Deformations or damages such as cracks and cuts on the wooden beams can lead to incomplete representations in the model. Overall, a high degree of automation was achieved

SOLO: a meiotic protein required for centromere cohesion, coorientation, and SMC1 localization in Drosophila melanogaster

Sisters on the loose (SOLO) protein functions as a meiotic cohesin component critical for correct chromosome segregation in Drosophila

cDNA Cloning and Expression Analysis of Gustavus Gene in the Oriental River Prawn Macrobrachium nipponense

The gustavus gene is required for localizing pole plasm and specifying germ cells. Research on gustavus gene expression will advance our understanding of the biological function of gustavus in animals. A cDNA encoding gustavus protein was identified and termed MnGus in the oriental river prawn Macrobrachium nipponense. Bioinformatic analyses showed that this gene encoded a protein of 262 amino acids and the protein belongs to the Spsb1 family. Real-time quantitative PCR analyses revealed that the expression level of MnGus in prawn embryos was slightly higher at the cleavage stage than at the blastula stage, and reached the maximum level during the zoea stage of embryos. The minimum level of MnGus expression occurred during the perinucleolus stage in the ovary, while the maximum was at the oil globule stage, and then the level of MnGus expression gradually decreased with the advancement of ovarian development. The expression level of MnGus in muscle was much higher than that in other tissues in mature prawn. The gustavus cDNA sequence was firstly cloned from the oriental river prawn and the pattern of gene expression was described during oocyte maturation, embryonic development, and in other tissues. The differential expression patterns of MnGus in the embryo, ovary and other somatic tissues suggest that the gustavus gene performs multiple physiological functions in the oriental river prawn

The Meiotic Recombination Checkpoint Suppresses NHK-1 Kinase to Prevent Reorganisation of the Oocyte Nucleus in Drosophila

The meiotic recombination checkpoint is a signalling pathway that blocks meiotic progression when the repair of DNA breaks formed during recombination is delayed. In comparison to the signalling pathway itself, however, the molecular targets of the checkpoint that control meiotic progression are not well understood in metazoans. In Drosophila, activation of the meiotic checkpoint is known to prevent formation of the karyosome, a meiosis-specific organisation of chromosomes, but the molecular pathway by which this occurs remains to be identified. Here we show that the conserved kinase NHK-1 (Drosophila Vrk-1) is a crucial meiotic regulator controlled by the meiotic checkpoint. An nhk-1 mutation, whilst resulting in karyosome defects, does so independent of meiotic checkpoint activation. Rather, we find unrepaired DNA breaks formed during recombination suppress NHK-1 activity (inferred from the phosphorylation level of one of its substrates) through the meiotic checkpoint. Additionally DNA breaks induced by X-rays in cultured cells also suppress NHK-1 kinase activity. Unrepaired DNA breaks in oocytes also delay other NHK-1 dependent nuclear events, such as synaptonemal complex disassembly and condensin loading onto chromosomes. Therefore we propose that NHK-1 is a crucial regulator of meiosis and that the meiotic checkpoint suppresses NHK-1 activity to prevent oocyte nuclear reorganisation until DNA breaks are repaired

The SPRY domain–containing SOCS box protein SPSB2 targets iNOS for proteasomal degradation

Macrophages lacking SPSB2 have increased NO production and enhanced pathogen-killing capabilities due to decreased ubiquitin-mediated destruction of iNOS