Projecte de reconstrucció del col•lector d'aigües pluvials i millora de la zona del meandre de sortida al riu Llobregat entre Cornellà i el Prat de Llobregat

Aquest projecte està motivat per l'existència d'esvorancs i enfonsaments de terres al camí paral·lel a la mota de terres existent originats per l'estat precari que presenta el tub de desguàs d'aigües pluvials de l'antic meandre de sortida al riu Llobregat. L'objecte del present projecte consisteix en la definició dels treballs de restitució del tram de 50 m de col·lector afectat i estructures annexes a fi de restablir-ne la seva funcionalitat. També hi estan contemplats els treballs de millora del tram entre la sortida del tub i la llera del riu Llobregat així com la reposició de camins i revegetació de la zona afectada

Detecció de defectes en cel·les fotovoltaiques sobre imatges obtingudes via electroluminescència mitjançant xarxes neuronals convolucionals (CNN)

Aquest projecte consisteix en el tractament d’imatges de cel·les fotovoltaiques obtingudes via electroluminescència per a generar un model mitjançant Xarxes Neuronals Convolucionals capaç de classificar cada imatge segons el seu percentatge de defectuositat. L’objectiu principal és automatitzar el control de qualitat del procés de fabricació. El banc d’imatges amb el que s’ha treballat s’anomena “elpv-dataset-master”, és públic i consta de 2.624 imatges de 300x300 píxels en escala de grisos de cèl·lules solars funcionals i defectuoses amb un grau variable de degradacions, extretes de 44 mòduls solars diferents. Els defectes de les imatges anotades són de tipus intrínsec o extrínsec i se sap que redueixen l’eficiència energètica dels mòduls solars. Al llarg d’aquest projecte es tracta i analitza la base de dades original, es generen diferents xarxes neuronals per observar-ne el rendiment de referència (‘Benchmark”) i finalment s’enfoca l’estudi a la correcció del desequilibri entre classes del banc d’imatges utilitzant diferents tècniques com: “Data Augmentation”, “Transfer Learning” entre models, rebalanceig de pesos inicials del model i “Oversampling” (generació de més imatges per a les classes minoritàries).Este proyecto consiste en el tratamiento de imágenes de células fotovoltaicas obtenidas vía electroluminiscencia para generar un modelo mediante Redes Neuronales Convolucionales capaz de clasificar cada imagen según su porcentaje de defectuosidad. El objetivo principal es automatizar el control de calidad del proceso de fabricación. El banco de imágenes con el que se ha trabajado se denomina "elpv-dataset-master", es público y consta de 2.624 imágenes de 300x300 píxeles y en escala de grises de células solares funcionales y defectuosas con un grado variable de degradaciones, extraídas de 44 módulos solares diferentes. Los defectos de las imágenes anotadas son de tipo intrínseco o extrínseco y se sabe que reducen la eficiencia energética de los módulos solares. A lo largo de este proyecto se trata y analiza la base de datos original, se generan diferentes redes neuronales para observar el rendimiento de referencia ( “Benchmark ") y finalmente se enfoca el estudio a la corrección del desequilibrio entre clases del banco de imágenes utilizando diferentes técnicas como: "Data Augmentation", "Transfer Learning" entre modelos, rebalanceo de pesos iniciales del modelo y "oversampling" (generación de más imágenes para las clases minoritarias).This project consists on the treatment of images of photovoltaic cells obtained via electroluminescence to generate a Convolutional Neural Network model capable of classifying each image on its defect percentage. The main goal is to automatize the quality control of the manufacturing process. The dataset studied is called “elpv-dataset-master”, it is public and contains 2,624 samples of 300x300 pixels grayscale images of functional and defective solar cells with varying degree of degradations extracted from 44 different solar modules. The defects in the annotated images are either of intrinsic or extrinsic type and are known to reduce the power efficiency of solar modules. Throughout this project, the original database is explored and analysed, different neural networks are generated to observe its Benchmark performance and finally the study focuses on the correction of the imbalance between classes of the dataset using different techniques such as: “Data Augmentation”, “Transfer Learning” between models, rebalance of initial weights of the model and “Oversampling”

The importance of organizational variables in treatment time for patients with ST-elevation acute myocardial infarction improve delays in STEMI

Background: The time between arrival at the emergency department (ED) and balloon (D2B) in STEMI is one of the best indicators of the quality of care. Our aim is to describe treatment times and evaluate the causes of delay. Methods: This is an observational retrospective study, including all consecutive STEMI code patients ≥18 years old treated in the ED from 2013 to 2016.All the patients were stratified into two groups: delayed group with D2B > 70 min and non-delayed ≤70. The primary variable was D2B time. Findings: In total 327 patients were included, stratified according to their D2B as follows: 166 (67·48%) in the delayed group and 80 (32·52%) in the non-delayed group. The delayed group was older (p = 0·005), with more females (p = 0·060) and more atypical electrocardiogram (ECG) STEMI signs or symptoms (p = 0·058) (p = 0·087). Predictors of shorter D2B time were: typical STEMI ECG signs and short training sessions for nurses on identifying STEMI patients. Interpretation: There are delays particularly in specific groups with atypical clinical presentations. Short training sessions aimed at emergency nurses correlate with shorter delay. This suggests that continuing training for emergency nurses, along with organizational strategies, can contribute to increasing the quality of care. Clinical trial number: NCT0433338

Transforming Growth Factor β Promotes Neuronal Cell Fate of Mouse Cortical and Hippocampal Progenitors In Vitro and In Vivo: Identification of Nedd9 as an Essential Signaling Component

Transforming Growth Factor β (Tgfβ) and associated signaling effectors are expressed in the forebrain, but little is known about the role of this multifunctional cytokine during forebrain development. Using hippocampal and cortical primary cell cultures of developing mouse brains, this study identified Tgfβ-regulated genes not only associated with cell cycle exit of progenitors but also with adoption of neuronal cell fate. Accordingly, we observed not only an antimitotic effect of Tgfβ on progenitors but also an increased expression of neuronal markers in Tgfβ treated cultures. This effect was dependent upon Smad4. Furthermore, in vivo loss-of-function analyses using Tgfβ2−/−/Tgfβ3−/− double mutant mice showed the opposite effect of increased cell proliferation and fewer neurons in the cerebral cortex and hippocampus. Gata2, Runx1, and Nedd9 were candidate genes regulated by Tgfβ and known to be involved in developmental processes of neuronal progenitors. Using siRNA-mediated knockdown, we identified Nedd9 as an essential signaling component for the Tgfβ-dependent increase in neuronal cell fate. Expression of this scaffolding protein, which is mainly described as a signaling molecule of the β1-integrin pathway, was not only induced after Tgfβ treatment but was also associated with morphological changes of the Nestin-positive progenitor pool observed upon exposure to Tgfβ

Identification of spinal circuits involved in touch-evoked dynamic mechanical pain

Mechanical hypersensitivity is a debilitating symptom associated with millions of chronic pain patients. It exists in distinct forms, including brush-evoked dynamic and filament-evoked punctate. Here we report that dynamic mechanical hypersensitivity induced by nerve injury or inflammation was compromised in mice with ablation of spinal VT3Lbx1 neurons defined by coexpression of VGLUT3Cre and Lbx1Flpo, as indicated by the loss of brush-evoked nocifensive responses and conditional place aversion. Electrophysiological recordings show that VT3Lbx1 neurons form morphine-resistant polysynaptic pathways relaying inputs from low-threshold Aβ mechanoreceptors to lamina I output neurons. Meanwhile, the subset of somatostatin (SOM) lineage neurons preserved in VT3Lbx1 neuron-ablated mice is largely sufficient to mediate von Frey filament-evoked punctate mechanical hypersensitivity, including both morphine-sensitive and morphine-resistant forms. Furthermore, acute silencing of VT3Lbx1 neurons attenuated pre-established dynamic mechanical hypersensitivity induced by nerve injury, suggesting these neurons as a potential cellular target for treating this form of neuropathic pain

Dbx1 Precursor Cells Are a Source of Inspiratory XII Premotoneurons.

All behaviors require coordinated activation of motoneurons from central command and premotor networks. The genetic identities of premotoneurons providing behaviorally relevant excitation to any pool of respiratory motoneurons remain unknown. Recently, we established in vitro that Dbx1-derived pre-Bo¨ tzinger complex neurons are critical for rhythm generation and that a subpopulation serves a premotor function (Wang et al., 2014). Here, we further show that a subpopulation of Dbx1-derived intermediate reticular (IRt) neurons are rhythmically active during inspiration and project to the hypoglossal (XII) nucleus that contains motoneurons important for maintaining airway patency. Laser ablation of Dbx1 IRt neurons, 57% of which are glutamatergic, decreased ipsilateral inspiratory motor output without affecting frequency. We conclude that a subset of Dbx1 IRt neurons is a source of premotor excitatory drive, contributing to the inspiratory behavior of XII motoneurons, as well as a key component of the airway control network whose dysfunction contributes to sleep apnea

Fast optical source for quantum key distribution based on semiconductor optical amplifiers

A novel integrated optical source capable of emitting faint pulses with different polarization states and with different intensity levels at 100 MHz has been developed. The source relies on a single laser diode followed by four semiconductor optical amplifiers and thin film polarizers, connected through a fiber network. The use of a single laser ensures high level of indistinguishability in time and spectrum of the pulses for the four different polarizations and three different levels of intensity. The applicability of the source is demonstrated in the lab through a free space quantum key distribution experiment which makes use of the decoy state BB84 protocol. We achieved a lower bound secure key rate of the order of 3.64 Mbps and a quantum bit error ratio as low as $1.14\times 10^{-2}$ while the lower bound secure key rate became 187 bps for an equivalent attenuation of 35 dB. To our knowledge, this is the fastest polarization encoded QKD system which has been reported so far. The performance, reduced size, low power consumption and the fact that the components used can be space qualified make the source particularly suitable for secure satellite communication

Interview with the Guest Editor—Ille C. Gebeshuber

Ille C. Gebeshuber is Professor of Physics at the Institute of Applied Physics at the Vienna University of Technology, Austria, where she graduated and completed her Ph.D. on technical biophysics of the inner ear in 1998. In 1999, she undertook postdoctoral training in scanning probe microscopy and biomimetics at the University of California, Santa Barbara, CA, USA, and soon after she returned to Austria to her home university to work on ion surface interactions, tribology and (bio-)nanotechnology. From 2009 to 2015, she joined the Institute of Microengineering and Nanoelectronics at the National University of Malaysia. During her expeditions, together with her students from cultural diverse backgrounds and expertise, she learned from the rainforest how nature develops well-adapted structures and materials, inspiring her to apply these principles to solve technological problems for humans to face global challenges in a safe and sustainable way. Her research focuses on nanotechnology and biomimetics, and takes a multidisciplinary approach, from biology and engineering to the fine arts and the social sciences. In 2017, she was elected Austrian of the Year in the “Research” category. We asked Ille about her career, her thoughts about the potential of biomimetic nanotechnology, and her experience during her editorship with Biomimetics

Next Generation—Sébastien R. Mouchet

Next Generation is a series of interviews with the awardees of the Biomimetics Travel Awards aimed at supporting early-career researchers and helping them promote their work. Sébastien R. Mouchet is a postdoctoral fellow in the Natural Photonics group led by Prof. Pete Vukusic at the University of Exeter, UK, working in collaboration with his former Ph.D. supervisor, Prof. Olivier Deparis, at the University of Namur, Belgium. His research focuses on fluorescence emission and coloration changes in photonic structures of insects induced by contact with fluids aiming to develop bioinspired technological solutions for chemical sensing and biosensing