Electrical analysis of new all-plastic electrochromic devices

New all-plastic electrochromic devices have been manufactured using commercial PEDOT foils and classical polymer electrolyte electrodeposition techniques. Several devices with different areas have been electrically characterized by using an impedance spectroscopy technique. After a brief description of the manufacturing process, we discuss electrical properties with the size of the device. Real and imaginary parts of the impedance have been plotted as a function of frequency. Some interesting conclusions have been derived from those plots, and some improvements in manufacturing process of this kind of devices are also proposed.Publicad

Modelling and electro-optical testing of suspended particle devices

Some smart windows make use of suspended particle devices (SPDs) which are made of charged rod-shape particles that change their orientation in an applied electric field, thereby allowing transmittance control. In this work, the electro-optical behaviour of a commercial SPD is analyzed. Impedance analysis shows characteristics similar to those of a Randles circuit, and a modified equivalent circuit is proposed and experimentally validated. Intermediate levels of transmittance are obtained using a customized field programmable gate array (FPGA)-based electrical circuit. Finally, measurements are taken to check the applicability of the SPD device and control system in smart glazing or photonic applications.Universidad Carlos III de MadridThis research was partially supported by funds from the Spanish Ministry of Science and Technology (Project PTR95-0940.01.OP), and by Comunidad de Madrid (Project FACTOTEMCM:S-0505/ESP/000417).Publicad

Spanish validation of the pure procrastination scale: dimensional structure, internal consistency, temporal stability, gender invariance, and relationships with personality and satisfaction with life

The objective of the current study was to adapt and validate the pure procrastination scale (PPS) for the Spanish adult population. Procrastination can have numerous consequences in daily life, making it essential to have reliable and valid instruments for measuring procrastination. Thus, this study was conducted to address this need. The sample consisted of 596 adults aged 18–83 years (M = 35.25, SD = 13.75). In addition to the PPS, participants completed two procrastination measures, namely the irrational procrastination scale and the decisional procrastination questionnaire, alongside the Big Five inventory and the satisfaction with life scale. The results of the confirmatory factor analysis revealed a three-factor structure of the PPS. The examination of the reliability of scores in terms of internal consistency and temporal stability showed satisfactory results for the PPS scores. Moreover, gender invariance was observed at the scalar level. Finally, the PPS scores correlated with other measures of procrastination, personality traits, and satisfaction with life in the expected direction and magnitude. In conclusion, the Spanish PPS offers valid and reliable scores when administered to adult population

Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks

[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was trained with five challenging and heterogeneous MR prostate datasets (and two US datasets), with segmentations from many different experts with varying segmentation criteria. The model achieves a consistently strong performance in all datasets independently (mean Dice Similarity Coefficient -DSC- above 0.91 for all datasets except for one), outperforming the inter-expert variability significantly in MR (mean DSC of 0.9099 vs. 0.8794). When evaluated on the publicly available Promise12 challenge dataset, it attains a similar performance to the best entries. In summary, the model has the potential of having a significant impact on current prostate procedures, undercutting, and even eliminating, the need of manual segmentations through improvements in terms of robustness, generalizability and output resolutionThis work has been partially supported by a doctoral grant of the Spanish Ministry of Innovation and Science, with reference FPU17/01993Pellicer-Valero, OJ.; González-Pérez, V.; Casanova Ramón-Borja, JL.; Martín García, I.; Barrios Benito, M.; Pelechano Gómez, P.; Rubio-Briones, J.... (2021). Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks. Applied Sciences. 11(2):1-17. https://doi.org/10.3390/app11020844S117112Marra, G., Ploussard, G., Futterer, J., & Valerio, M. (2019). Controversies in MR targeted biopsy: alone or combined, cognitive versus software-based fusion, transrectal versus transperineal approach? World Journal of Urology, 37(2), 277-287. doi:10.1007/s00345-018-02622-5Ahdoot, M., Lebastchi, A. H., Turkbey, B., Wood, B., & Pinto, P. A. (2019). Contemporary treatments in prostate cancer focal therapy. Current Opinion in Oncology, 31(3), 200-206. doi:10.1097/cco.0000000000000515Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017). ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60(6), 84-90. doi:10.1145/3065386Allen, P. D., Graham, J., Williamson, D. C., & Hutchinson, C. E. (s. f.). Differential Segmentation of the Prostate in MR Images Using Combined 3D Shape Modelling and Voxel Classification. 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006. doi:10.1109/isbi.2006.1624940Freedman, D., Radke, R. J., Tao Zhang, Yongwon Jeong, Lovelock, D. M., & Chen, G. T. Y. (2005). Model-based segmentation of medical imagery by matching distributions. IEEE Transactions on Medical Imaging, 24(3), 281-292. doi:10.1109/tmi.2004.841228Klein, S., van der Heide, U. A., Lips, I. M., van Vulpen, M., Staring, M., & Pluim, J. P. W. (2008). Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. Medical Physics, 35(4), 1407-1417. doi:10.1118/1.2842076Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, 234-241. doi:10.1007/978-3-319-24574-4_28He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. 2017 IEEE International Conference on Computer Vision (ICCV). doi:10.1109/iccv.2017.322Shelhamer, E., Long, J., & Darrell, T. (2017). Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), 640-651. doi:10.1109/tpami.2016.2572683He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2016.90Milletari, F., Navab, N., & Ahmadi, S.-A. (2016). V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. 2016 Fourth International Conference on 3D Vision (3DV). doi:10.1109/3dv.2016.79Zhu, Q., Du, B., Turkbey, B., Choyke, P. L., & Yan, P. (2017). Deeply-supervised CNN for prostate segmentation. 2017 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/ijcnn.2017.7965852To, M. N. N., Vu, D. Q., Turkbey, B., Choyke, P. L., & Kwak, J. T. (2018). Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging. International Journal of Computer Assisted Radiology and Surgery, 13(11), 1687-1696. doi:10.1007/s11548-018-1841-4Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely Connected Convolutional Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2017.243Zhu, Y., Wei, R., Gao, G., Ding, L., Zhang, X., Wang, X., & Zhang, J. (2018). Fully automatic segmentation on prostate MR images based on cascaded fully convolution network. Journal of Magnetic Resonance Imaging, 49(4), 1149-1156. doi:10.1002/jmri.26337Wang, Y., Ni, D., Dou, H., Hu, X., Zhu, L., Yang, X., … Wang, T. (2019). Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound. IEEE Transactions on Medical Imaging, 38(12), 2768-2778. doi:10.1109/tmi.2019.2913184Lemaître, G., Martí, R., Freixenet, J., Vilanova, J. C., Walker, P. M., & Meriaudeau, F. (2015). Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review. Computers in Biology and Medicine, 60, 8-31. doi:10.1016/j.compbiomed.2015.02.009Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., … Madabhushi, A. (2014). Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge. Medical Image Analysis, 18(2), 359-373. doi:10.1016/j.media.2013.12.002Zhu, Q., Du, B., & Yan, P. (2020). Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation. IEEE Transactions on Medical Imaging, 39(3), 753-763. doi:10.1109/tmi.2019.2935018He, K., Zhang, X., Ren, S., & Sun, J. (2015). Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. 2015 IEEE International Conference on Computer Vision (ICCV). doi:10.1109/iccv.2015.123Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359. doi:10.1109/tkde.2009.191Smith, L. N. (2017). Cyclical Learning Rates for Training Neural Networks. 2017 IEEE Winter Conference on Applications of Computer Vision (WACV). doi:10.1109/wacv.2017.58Abraham, N., & Khan, N. M. (2019). A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). doi:10.1109/isbi.2019.8759329Lei, Y., Tian, S., He, X., Wang, T., Wang, B., Patel, P., … Yang, X. (2019). Ultrasound prostate segmentation based on multidirectional deeply supervised V‐Net. Medical Physics, 46(7), 3194-3206. doi:10.1002/mp.13577Orlando, N., Gillies, D. J., Gyacskov, I., Romagnoli, C., D’Souza, D., & Fenster, A. (2020). Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images. Medical Physics, 47(6), 2413-2426. doi:10.1002/mp.14134Karimi, D., Zeng, Q., Mathur, P., Avinash, A., Mahdavi, S., Spadinger, I., … Salcudean, S. E. (2019). Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images. Medical Image Analysis, 57, 186-196. doi:10.1016/j.media.2019.07.005PROMISE12 Resultshttps://promise12.grand-challenge.org/Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., & Maier-Hein, K. H. (2020). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature Methods, 18(2), 203-211. doi:10.1038/s41592-020-01008-

Label-free optical biosensing with slot-waveguides.

We demonstrate label-free molecule detection by using an integrated biosensor based on a Si3N4 /SiO2 slotwaveguide microring resonator. Bovine serum albumin (BSA) and anti-BSA molecular binding events on the sensor surface are monitored through the measurement of resonant wavelength shifts with varying biomolecule concentrations. The biosensor exhibited sensitivities of 1.8 and 3.2 nm/ _ng/mm2_ for the detection of anti-BSA and BSA, respectively. The estimated detection limits are 28 and 16 pg/mm2 for anti-BSA and BSA, respectively, limited by wavelength resolutio

El juego como factor motivador en la enseñanza de la anatomía humana

Introducción. Con la llegada a la universidad de una nueva generación de alumnos, la ‘generación Z’, considerada como la primera generación nativa digital, se hace necesario implantar nuevas metodologías docentes en el ámbito universitario para mejorar el proceso de enseñanza-aprendizaje y conseguir una mayor motivación en el alumno. Para ello, el uso de nuevas tecnologías de la información y de la comunicación ha permitido dinamizar estos procesos y aumentar la motivación del alumnado en todos los niveles educativos, incluyendo la docencia universitaria. Sujetos y métodos. Utilización de la aplicación educativa Kahoot a través de dispositivos móviles, con los alumnos matriculados de la asignatura de ‘Anatomía Humana II (Esplacnología)’, de segundo curso del Grado de Medicina en la Universidad de Zaragoza. Resultados. El impacto que la experiencia ha causado en los estudiantes se ha medido a través de encuestas de valoración cualitativas, analizando sus resultados de aprendizaje. Estos resultados han sido valorados de manera muy positiva por el alumnado, tanto en lo referente a utilidad en la enseñanza-aprendizaje como a motivación. Conclusión. Kahoot es una herramienta digital interactiva, gratuita y de manejo sencillo tanto para el docente como para los alumnos, que permite que éstos mejoren en su aprendizaje haciendo uso de nuevas tecnologías y se sientan así más motivados

Análisis biomecánico de la epifisiolisis de la cabeza femoral: comparación entre fémures sanos y enfermos

En este trabajo se desarrolla un análisis por elementos finitos cuyo objetivo principal es determinar las diferencias de tensiones en la placa de crecimiento que se producen entre fémures sanos, con epifisiolisis unilateral y con epifisiolisis bilateral, para evaluar sus posibles causas. Se elaboraron los modelos de elementos finitos correspondientes a 45 pacientes. Los resultados mostraron un patrón de esfuerzos similar en todos los grupos de fémures y, además, la aparición de tensiones mayores en el grupo con epifisiolisis con respecto al grupo control. Se observó también que el valor del ángulo axial-fisis dependía significativamente del tipo de fémur analizado, y, además, una mayor influencia de los factores geométricos en la incidencia de la enfermedad, en comparación con la del índice de masa corporal.In this work, a finite element analysis (FEA) is accomplished to study the differences of stresses in the growth plate, that are produced in healthy and unhealthy femurs, and to evaluate the possible causes of this illness. Finite element models of 45 patients were developed. The results demonstrated a similar pattern of stresses in all the groups of femurs and also the appearance of greater stresses in the group with slipped capital femoral epiphysis than in the control group. It was also observed a strong dependency on the value of the axial-fisis angle from the group of femur analyzed and a bigger influence of the geometric factors than of the body mass index, in the incidence of the illness

Ultrahigh Sensitivity Slot-Waveguide Biosensor on a Highly Integrated Chip for Simultaneous Diagnosis of Multiple

SABIO is a multidisciplinary project involving the emerging fields of micro-nanotechnology, photonics, fluidics and bio-chemistry, targeting a contribution to the development of intelligent diagnostic equipment through the demonstration of a compact polymer based and silicon-based CMOS-compatible micro-nano system. It integrates optical biosensors for label-free biomolecular recognition based on a novel photonic structure named slot-waveguide with immobilized bimolecular receptors on its surface. The slot-waveguides provide high optical intensity in a sub wavelength-size low refractive index region (slot-region) sandwiched between two high refractive index strips (rails) [1] leading to an enhanced interaction between the optical probe and biomolecular complexes (antibody-antigen). As such a biosensor is predicted to exhibit a surface concentration detection-limit lower than 1 pg/mm2, state-of-the-art in label free integrated optical biosensors, as well as the possibility of multiplexed assay, which, together with reduced reaction volumes, leads to the ability to perform rapid multi-analytesensing and comprehensive tests. This offers the further advantageous possibility of assaying several parameters simultaneously and consequently, statistical analysis of these results can potentially increase the reliability and reduce the measurement uncertainty of a diagnostic over single-parameter assays. In addition, the SABIO micro-nano system device applied to its novel protein-based diagnostic technology has the potential to be fast and easy to use, making routine screening or monitoring of diseases more cost-effective

Del color de los ojos al interior del genoma. Nuevas tecnologías aplicadas a la educación: una experiencia en la enseñanza de la Genética

Depto. de Genética, Fisiología y MicrobiologíaFac. de Ciencias BiológicasFALSEsubmitte