In processu iurisfirmae Diputatorum Regni por Luys Arrago contra Luys Pollina Rector de Buarz y Torreblanca

Texto a doble col.Copia digital : Diputación Provincial de Zaragoza. Servicio de Archivos y Bibliotecas, 2010Sign.: A\p4\sInic. grab. xil. en p.

Fruit splitting in 'Nova' hybrid mandarin in relation to the anatomy of the fruit and fruit set treatments

Fruil splining in the mandarin orange cultivar ‘Nova’ is related lo lhe prescnce of an open stylar end in lhe fruit This opening arises from a cavily present at lhe base of lhe style, and is formed in a varjable proportion of fruits. The edis at lhe boltom of lhis styie cavily form a rind-lilce lissue which develop into a navel struclure. The size ofthis nave! is larger in open-slylar end bearing fruits and, according!y, ia sp!it fruil. The number of split fruil per tree is unrelaled to lhe number of fruit set. The application of gibberel!ic acid (GA,) has a variable effect on set and splitting depending on its timing. This hormone increases fruit sp!ilting when app!ied aI flowering, bel reduces it when applied shortly afler lhe end of lhe June drop. Ilhas on!y a minor effect on fruit seI

Effect of 2.4-d exogenous application on the abscission and fruit growth in sweet orange. var. salustiana.

The effect of 2.4-D applications in full bloom on the abscission and fruit growth process was studied on sweet orange fruit in 20-year-old trees of Citrus sinensis (L.) Osbeck cv. Salustiana with a high flowering level. Abscission was determined on the whole tree and on the leafy inflorescences. Growth variables of the fruit were characterized (diameter, fresh and dry weight). 2.4-D application (20 mg L-1, 3.6 L per tree) increased the growth rate of the fruits and fruits size at maturity, however reduced the number of fruits which kept constant the yield at harvest. Differences between the diameter of the control fruits and the fruits treated with 2.4-D were observed during the early fruitlet development and until day 43 after anthesis. These differences increased with time following a linear relationship. For all the studied variables the diary increase level reaches the maximum by day 53, when the cell expansion of the vesicles starts

Probabilistic Evaluation of 3D Surfaces Using Statistical Shape Models (SSM)

[EN] Inspecting a 3D object which shape has elastic manufacturing tolerances in order to find defects is a challenging and time-consuming task. This task usually involves humans, either in the specification stage followed by some automatic measurements, or in other points along the process. Even when a detailed inspection is performed, the measurements are limited to a few dimensions instead of a complete examination of the object. In this work, a probabilistic method to evaluate 3D surfaces is presented. This algorithm relies on a training stage to learn the shape of the object building a statistical shape model. Making use of this model, any inspected object can be evaluated obtaining a probability that the whole object or any of its dimensions are compatible with the model, thus allowing to easily find defective objects. Results in simulated and real environments are presented and compared to two different alternatives.This work was partially funded by Generalitat Valenciana through IVACE (Valencian Institute of Business Competitiveness) distributed nominatively to Valencian technological innovation centres under project expedient IMAMCN/2020/1.Pérez, J.; Guardiola Garcia, JL.; Pérez Jiménez, AJ.; Perez-Cortes, J. (2020). Probabilistic Evaluation of 3D Surfaces Using Statistical Shape Models (SSM). Sensors. 20(22):1-16. https://doi.org/10.3390/s20226554S1162022Brosed, F. J., Aguilar, J. J., Guillomía, D., & Santolaria, J. (2010). 3D Geometrical Inspection of Complex Geometry Parts Using a Novel Laser Triangulation Sensor and a Robot. Sensors, 11(1), 90-110. doi:10.3390/s110100090Perez-Cortes, J.-C., Perez, A., Saez-Barona, S., Guardiola, J.-L., & Salvador, I. (2018). A System for In-Line 3D Inspection without Hidden Surfaces. Sensors, 18(9), 2993. doi:10.3390/s18092993Bi, Z. M., & Wang, L. (2010). Advances in 3D data acquisition and processing for industrial applications. Robotics and Computer-Integrated Manufacturing, 26(5), 403-413. doi:10.1016/j.rcim.2010.03.003Fu, K., Peng, J., He, Q., & Zhang, H. (2020). Single image 3D object reconstruction based on deep learning: A review. Multimedia Tools and Applications, 80(1), 463-498. doi:10.1007/s11042-020-09722-8Pichat, J., Iglesias, J. E., Yousry, T., Ourselin, S., & Modat, M. (2018). A Survey of Methods for 3D Histology Reconstruction. Medical Image Analysis, 46, 73-105. doi:10.1016/j.media.2018.02.004Pathak, V. K., Singh, A. K., Sivadasan, M., & Singh, N. K. (2016). Framework for Automated GD&T Inspection Using 3D Scanner. Journal of The Institution of Engineers (India): Series C, 99(2), 197-205. doi:10.1007/s40032-016-0337-7Bustos, B., Keim, D. A., Saupe, D., Schreck, T., & Vranić, D. V. (2005). Feature-based similarity search in 3D object databases. ACM Computing Surveys, 37(4), 345-387. doi:10.1145/1118890.1118893Mian, A., Bennamoun, M., & Owens, R. (2009). On the Repeatability and Quality of Keypoints for Local Feature-based 3D Object Retrieval from Cluttered Scenes. International Journal of Computer Vision, 89(2-3), 348-361. doi:10.1007/s11263-009-0296-zLiu, Z., Zhao, C., Wu, X., & Chen, W. (2017). An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors. Sensors, 17(3), 451. doi:10.3390/s17030451Barra, V., & Biasotti, S. (2013). 3D shape retrieval using Kernels on Extended Reeb Graphs. Pattern Recognition, 46(11), 2985-2999. doi:10.1016/j.patcog.2013.03.019Xie, J., Dai, G., Zhu, F., Wong, E. K., & Fang, Y. (2017). DeepShape: Deep-Learned Shape Descriptor for 3D Shape Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(7), 1335-1345. doi:10.1109/tpami.2016.2596722Lague, D., Brodu, N., & Leroux, J. (2013). Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z). ISPRS Journal of Photogrammetry and Remote Sensing, 82, 10-26. doi:10.1016/j.isprsjprs.2013.04.009Cook, K. L. (2017). An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology, 278, 195-208. doi:10.1016/j.geomorph.2016.11.009Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F.-J., García-Ferrer, A., & Pérez-Porras, F.-J. (2018). Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International Journal of Applied Earth Observation and Geoinformation, 72, 1-10. doi:10.1016/j.jag.2018.05.015Burdziakowski, P., Specht, C., Dabrowski, P. S., Specht, M., Lewicka, O., & Makar, A. (2020). Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project. Sensors, 20(14), 4000. doi:10.3390/s20144000MARDIA, K. V., & DRYDEN, I. L. (1989). The statistical analysis of shape data. Biometrika, 76(2), 271-281. doi:10.1093/biomet/76.2.271Heimann, T., & Meinzer, H.-P. (2009). Statistical shape models for 3D medical image segmentation: A review. Medical Image Analysis, 13(4), 543-563. doi:10.1016/j.media.2009.05.004Ambellan, F., Tack, A., Ehlke, M., & Zachow, S. (2019). Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative. Medical Image Analysis, 52, 109-118. doi:10.1016/j.media.2018.11.009Avendi, M. R., Kheradvar, A., & Jafarkhani, H. (2016). A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI. Medical Image Analysis, 30, 108-119. doi:10.1016/j.media.2016.01.005Booth, J., Roussos, A., Ponniah, A., Dunaway, D., & Zafeiriou, S. (2017). Large Scale 3D Morphable Models. International Journal of Computer Vision, 126(2-4), 233-254. doi:10.1007/s11263-017-1009-7Erus, G., Zacharaki, E. I., & Davatzikos, C. (2014). Individualized statistical learning from medical image databases: Application to identification of brain lesions. Medical Image Analysis, 18(3), 542-554. doi:10.1016/j.media.2014.02.00

A family of complex potentials with real spectrum

We consider a two-parameter non-Hermitian quantum mechanical Hamiltonian operator that is invariant under the combined effects of parity and time reversal transformations. Numerical investigation shows that for some values of the potential parameters the Hamiltonian operator supports real eigenvalues and localized eigenfunctions. In contrast with other parity times time reversal symmetric models which require special integration paths in the complex plane, our model is integrable along a line parallel to the real axis.Centro de Química Inorgánic

3D groundwater flow and deformation modelling of Madrid aquifer

A novel methodological approach to calibrate and validate three-dimensional (3D) finite element (FE) groundwater flow and geomechanical models has been implemented using Advanced Differential Interferometric SAR (A-DInSAR) data. In particular, we show how A-DInSAR data can be effectively used to (1) constrain the model set-up in evaluating the areal influence of the wellfield and (2) characterise the aquifer system, specifically the storage coefficient values, which represents a fundamental step in managing groundwater resources. The procedure has been tested to reconstruct the surface vertical and horizontal movements caused by the Manzanares-Jarama wellfield located northwest of Madrid (Spain). The wellfield was used to supply freshwater during major droughts over the period between 1994 and 2010. Previous A-DInSAR outcomes obtained by ERS-1/2 and ENVISAT acquisitions clearly revealed the seasonality of the land displacements associated to the withdrawal and recovery cycles that characterized the wellfield development. A time-lag of about one month, which is in the order of the time span between two SAR acquisitions, between the hydraulic head changes and the displacements has been detected in this site by a wavelet analysis of A-DInSAR and piezometer time series. The negligible delay between the forcing factor and the system response and the complete subsidence recovery when piezometric head recovers supported the understanding of a minor role played by the pore pressure propagation within clay layers and the almost perfectly elastic behavior of the system (viscosity is negligible), respectively. The developed geomechanical model satisfactorily reproduces the pumping-induced deformations with a Root Mean Square Error (RMSE) between observed and simulated land displacements in the order of 0.1-0.3 mm. The results give insights about the approach benefits in deeply understanding the spatio-temporal aquifer-system response to the management of this strategic water resource for Madrid.The activity has been developed within the scientific collaboration established in the framework of the UNESCO Land Subsidence International Initiative (LaSII - https://www.landsubsidence-unesco.org/). The research was funded by University of Pavia in the framework of a research grant award “assegno di tipo A premiale” for research activities at the Dept. of Earth and Environmental Sciences, within the research project entitled “Sustainable groundwater resources management by integrating A-DInSAR derived monitoring and flow modeling results” assigned to Roberta Bonì in March 2019. This research was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI), and the European Funds for Regional Development (FEDER) under project TEC2017-85244-C2-1-P

Affinity Paths and Information Diffusion in Social Networks

Widespread interest in the diffusion of information through social networks has produced a large number of Social Dynamics models. A majority of them use theoretical hypothesis to explain their diffusion mechanisms while the few empirically based ones average out their measures over many messages of different content. Our empirical research tracking the step-by-step email propagation of an invariable viral marketing message delves into the content impact and has discovered new and striking features. The topology and dynamics of the propagation cascades display patterns not inherited from the email networks carrying the message. Their disconnected, low transitivity, tree-like cascades present positive correlation between their nodes probability to forward the message and the average number of neighbors they target and show increased participants' involvement as the propagation paths length grows. Such patterns not described before, nor replicated by any of the existing models of information diffusion, can be explained if participants make their pass-along decisions based uniquely on local knowledge of their network neighbors affinity with the message content. We prove the plausibility of such mechanism through a stylized, agent-based model that replicates the \emph{Affinity Paths} observed in real information diffusion cascades.Comment: 11 pages, 7 figure

Understanding the dynamic behaviour for the Madrid aquifer (Spain): insights from the integration of A-DInSAR and 3-D groundwater flow and geomechanical models

Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques and 3-D groundwater flow and geomechanical models are integrated to improve our knowledge about the Tertiary detritic aquifer of Madrid (TDAM). In particular, the attention is focused on the Manzanares-Jarama well field, located to the northwest of Madrid, which experienced five cycles of extensive groundwater withdrawal followed by natural recovery, to cope with the droughts occurred in summer 1995, 1999, 2002, 2006, and 2009. Piezometric records and A-DInSAR data acquired by ERS-1/2 and ENVISAT satellites during the periods 1992–2000 and 2002–2010, respectively, have been used to calibrate the groundwater flow and the geomechanical models. A time-lag of about one month between the hydraulic head changes and the displacements of the land surface has been detected by a joint wavelet analysis of A-DInSAR and piezometer head time series. Overall, the results show the effectiveness of the proposed integrated approach composed of A-DInSAR and 3-D geomechanical model to characterize the aquifer-system response during and after the groundwater withdrawal.This research has been supported by the Università degli Studi di Pavia (Assegno di tipo A premiale: “Sustainable groundwater resources management by integrating A-DInSAR derived monitoring and flow modeling results” assigned to Roberta Bonì in March 2019) and the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI), and the European Funds for Regional Development (FEDER) (grant no. TEC2017-85244-C2-1-P)

Wavelet analysis of land subsidence time-series: Madrid Tertiary aquifer case study

Interpretation of land subsidence time-series to understand the evolution of the phenomenon and the existing relationships between triggers and measured displacements is a great challenge. Continuous wavelet transform (CWT) is a powerful signal processing method mainly suitable for the analysis of individual nonstationary time-series. CWT expands time-series into the time-frequency space allowing identification of localized nonstationary periodicities. Complementarily, Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) methods allow the comparison of two time-series that may be expected to be related in order to identify regions in the time-frequency domain that exhibit large common cross-power and wavelet coherence, respectively, and therefore are evocative of causality. In this work we use CWT, XWT and WTC to analyze piezometric and InSAR (interferometric synthetic aperture radar) time-series from the Tertiary aquifer of Madrid (Spain) to illustrate their capabilities for interpreting land subsidence and piezometric time-series information.This research has been supported by the Spanish Ministry of Economy and Competitiveness, the State Agency of Research and the European Funds for Regional Development (grant no. TEC2017-85244-C2-1-P)

A System for In-Line 3D Inspection without Hidden Surfaces

[EN] This work presents a 3D scanner able to reconstruct a complete object without occlusions, including its surface appearance. The technique presents a number of differences in relation to current scanners: it does not require mechanical handling like robot arms or spinning plates, it is free of occlusions since the scanned part is not resting on any surface and, unlike stereo-based methods, the object does not need to have visual singularities on its surface. This system, among other applications, allows its integration in production lines that require the inspection of a large volume of parts or products, especially if there is an important variability of the objects to be inspected, since there is no mechanical manipulation. The scanner consists of a variable number of industrial quality cameras conveniently distributed so that they can capture all the surfaces of the object without any blind spot. The object is dropped through the common visual field of all the cameras, so no surface or tool occludes the views that are captured simultaneously when the part is in the center of the visible volume. A carving procedure that uses the silhouettes segmented from each image gives rise to a volumetric representation and, by means of isosurface generation techniques, to a 3D model. These techniques have certain limitations on the reconstruction of object regions with particular geometric configurations. Estimating the inherent maximum error in each area is important to bound the precision of the reconstruction. A number of experiments are presented reporting the differences between ideal and reconstructed objects in the system.This work was partially funded by Generalitat Valenciana through I+D IVACE (Valencian Institute of Business Competitiveness) and FEDER (European Regional Developement Fund) supports under project IMDEEA/2018/115.Perez-Cortes, J.; Pérez Jiménez, AJ.; Sáez Barona, S.; Guardiola Garcia, JL.; Salvador Igual, I. (2018). A System for In-Line 3D Inspection without Hidden Surfaces. Sensors. 18(9):1-25. https://doi.org/10.3390/s18092993S12518