Estudios de estructura y composición de heteroestructuras In(N)/InGaN/Si para tecnología solar basada en nuevos conceptos

Se presenta el estudio de cinco heteroestructuras InGaN/Si mediante Microscopía Electrónica de Transmisión (TEM) y otras técnicas asociadas, centrándose en dos aspectos concretos de las mismas: se realizará una caracterización de la intercapa a nivel atómico, así como de las capas de InGaN que se han crecido sobre substratos de silicio y que contienen fracciones molares progresivamente superiores de nitruro de indio. Esto se ha realizado en base a diferentes técnicas de análisis estructural y composicional que servirán para evaluar la calidad cristalina y homogeneidad composicional de las muestras bajo estudio. En función de la muestra estudiada, se encuentran diferentes heteroestructuras InN/InGaN que han sido crecidas mediante una novedosa técnica recientemente documentada por investigadores del ISOM-UPM. Los resultados de estas investigaciones darán pie al futuro desarrollo de nuevos materiales semiconductores, especialmente en su aplicación en energía solar fotovoltaica y en optoelectrónica

Ingeniería de aleaciones de InGaN monofásicas para optoelectrónica

Se presenta el estudio de dos heteroestructuras InGaN/Si mediante Microscopía Electrónica de Transmisión (TEM) y otras técnicas asociadas, centrándose en la caracterización de la intercara a nivel atómico, en la homogeneidad estructural y composicional de la capa de InGaN, y en sus características ópticas, y en las propiedades de conducción eléctrica de la unión. La novedosa técnica para crecer estas estructuras fue recientemente documentada, al igual que lo han sido en publicaciones y congresos internacionales, los hallazgos realizados en estos materiales, gracias en parte a las propias investigaciones del grupo

Characterization of pores in polished low temperature co-fired glass-ceramic composites for optimization of their micromachining

Pores are intrinsic defects of ceramic composites and influence their functional properties significantly. Their characterization is therefore a pivotal task in material and process optimization. It is demonstrated that polished section analysis allows for obtaining precise information on pore size, shape, area fraction, and homogeneous distribution. It is proven that laser scanning microscopy provides accurate height maps and is thus an appropriate technique for assessing surface features. Such data is used to compare areas with good and poor polishing results, and various surface parameters are evaluated in terms of their informative value and data processing effort. The material under investigation is a low temperature co-fired ceramic composite. Through statistical analysis of the data, the inclination angle was identified as an appropriate parameter to describe the polishing result. By using masked data, direct conclusions can be drawn about the leveling of load-bearing surface areas, which are crucial in photolithographic processing steps and bonding technology. A broad discussion of different defects based on the results contributes to a critical analysis of the potentials and obstacles of micromachining of low temperature cofired ceramic substrates.15 página

Multilayer Spiking Neural Network for Audio Samples Classification Using SpiNNaker

Audio classification has always been an interesting subject of research inside the neuromorphic engineering field. Tools like Nengo or Brian, and hardware platforms like the SpiNNaker board are rapidly increasing in popularity in the neuromorphic community due to the ease of modelling spiking neural networks with them. In this manuscript a multilayer spiking neural network for audio samples classification using SpiNNaker is presented. The network consists of different leaky integrate-and-fire neuron layers. The connections between them are trained using novel firing rate based algorithms and tested using sets of pure tones with frequencies that range from 130.813 to 1396.91 Hz. The hit rate percentage values are obtained after adding a random noise signal to the original pure tone signal. The results show very good classification results (above 85 % hit rate) for each class when the Signal-to-noise ratio is above 3 decibels, validating the robustness of the network configuration and the training step.Ministerio de Economía y Competitividad TEC2012-37868-C04-02Junta de Andalucía P12-TIC-130

A Sensor Fusion Horse Gait Classification by a Spiking Neural Network on SpiNNaker

The study and monitoring of the behavior of wildlife has always been a subject of great interest. Although many systems can track animal positions using GPS systems, the behavior classification is not a common task. For this work, a multi-sensory wearable device has been designed and implemented to be used in the Doñana National Park in order to control and monitor wild and semiwild life animals. The data obtained with these sensors is processed using a Spiking Neural Network (SNN), with Address-Event-Representation (AER) coding, and it is classified between some fixed activity behaviors. This works presents the full infrastructure deployed in Doñana to collect the data, the wearable device, the SNN implementation in SpiNNaker and the classification results.Ministerio de Economía y Competitividad TEC2012-37868-C04-02Junta de Andalucía P12-TIC-130

Event-based Row-by-Row Multi-convolution engine for Dynamic-Vision Feature Extraction on FPGA

Neural networks algorithms are commonly used to recognize patterns from different data sources such as audio or vision. In image recognition, Convolutional Neural Networks are one of the most effective techniques due to the high accuracy they achieve. This kind of algorithms require billions of addition and multiplication operations over all pixels of an image. However, it is possible to reduce the number of operations using other computer vision techniques rather than frame-based ones, e.g. neuromorphic frame-free techniques. There exists many neuromorphic vision sensors that detect pixels that have changed their luminosity. In this study, an event-based convolution engine for FPGA is presented. This engine models an array of leaky integrate and fire neurons. It is able to apply different kernel sizes, from 1x1 to 7x7, which are computed row by row, with a maximum number of 64 different convolution kernels. The design presented is able to process 64 feature maps of 7x7 with a latency of 8.98 s.Ministerio de Economía y Competitividad TEC2016-77785-

Accuracy Improvement of Neural Networks Through Self-Organizing-Maps over Training Datasets

Although it is not a novel topic, pattern recognition has become very popular and relevant in the last years. Different classification systems like neural networks, support vector machines or even complex statistical methods have been used for this purpose. Several works have used these systems to classify animal behavior, mainly in an offline way. Their main problem is usually the data pre-processing step, because the better input data are, the higher may be the accuracy of the classification system. In previous papers by the authors an embedded implementation of a neural network was deployed on a portable device that was placed on animals. This approach allows the classification to be done online and in real time. This is one of the aims of the research project MINERVA, which is focused on monitoring wildlife in Do˜nana National Park using low power devices. Many difficulties were faced when pre-processing methods quality needed to be evaluated. In this work, a novel pre-processing evaluation system based on self-organizing maps (SOM) to measure the quality of the neural network training dataset is presented. The paper is focused on a three different horse gaits classification study. Preliminary results show that a better SOM output map matches with the embedded ANN classification hit improvement.Junta de Andalucía P12-TIC-1300Ministerio de Economía y Competitividad TEC2016-77785-

Sensorimotor tongue evaluation and rehabilitation in patients with sleep-disordered breathing: a novel approach

We acknowledge the work of Professor O’Connor-Reina who designed and produced the Airway Gym® app for his patients and whose work was central to this research.Study objectives: To evaluate tone, apraxia and stereognosis dysfunctions in patients with SDB compared with healthy controls, and to monitor the effectiveness of Airway Gym® as an easy-to- use myofunctional therapy (MT) modality in terms of the tongue's motor and sensory responses, comparing results before and after therapy. Methods: This was a prospective, non-randomised pilot study of 25 patients with moderate to severe obstructive sleep apnoea-hypopnoea syndrome (OSAHS), 25 patients with primary snoring (PS) and 20 healthy controls. Qualitative and quantitative instruments—Iowa Oral Performance Instrument (IOPI), lingual apraxia and stereognosis tests were used to assess tongue sensorimotor function. Results: 22 patients with PS, 21 with OSAHS and all 20 controls ended the therapy. In OSAHS, the Epworth Sleepiness Scale score decreased from 16 ± 7.3 to 12 ± 4.5 after therapy (p = 0.53). In PS and OSAHS groups, the IOPI scores increased significantly. These measures did not change significantly in the controls. Lingual apraxia testing showed that controls performed all the manoeuvres, whereas PS 5.6 ± 1.4 and OSAHS 4.5 ± 1.9 (p = 0.14). In the stereognosis test, the mean number of figures recognised was 2.6 ± 2.2 in OSAHS, 3.3±1.2 in PS and 5.7±0.9 in control group (p < 0.05). Patients with OSAHS recognised circles and ovals less often. Conclusion: Using the Airway Gym®app produced improvements in sensorimotor tongue function in patients with SDB, due to continuous stimulation of the brain based on proprioceptive training required to localise responses when doing the exercises

Study of a hybrid solar absorption-cooling and flash-desalination system

Producción CientíficaIn this work, the analysis of a hybrid LiBr/H2O absorption-cooling and flash-desalination system, using solar thermal energy as heat source, is presented. An absorption open-cycle with three pressure levels is used in combination with a single-stage flash-desalination process to use the coolant as product water, resulting in an increase in cooling and desalination efficiency. For the application, a 20-room coastal hotel complex in San Felipe, Baja California, Mexico, is taken as a case study and the sizing of the solar collection and storage system is carried out for the operation of the proposed hybrid system, during the summer operative period. The operational dynamics during the week with the highest ambient temperatures are presented. The dimensioning of the solar collector’s area and the energy storage resulted in a collection area of 620 m2 with 30 m3, respectively, reaching a solar fraction of 69%. The absorption-cooling subprocess showed an increase of 13.88% in the average coefficient of performance (COP) compared to conventional LiBr/H2O absorption systems. Also, considering that the system provides cooling and desalination simultaneously, the average COPG is 1.64, which is 2.27 times higher than the COP of conventional LiBr/H2O single-effect absorption units. During the critical week, the system presented a desalinated water production of 16.94 m3 with an average performance ratio (PR) of 0.83, while the average daily water production was 2406 kg/day; enough to satisfy the daily water requirements of four people in a coastal hotel in Mexico or to cover the basic services of 24 people according to the World Health Organization

The coming age of flavonoids in the treatment of diabetic complications

Diabetes mellitus (DM), and its micro and macrovascular complications, is one of the biggest challenges for world public health. Despite overall improvement in prevention, diagnosis and treatment, its incidence is expected to continue increasing over the next years. Nowadays, finding therapies to prevent or retard the progression of diabetic complications remains an unmet need due to the complexity of mechanisms involved, which include inflammation, oxidative stress and angiogenesis, among others. Flavonoids are natural antioxidant compounds that have been shown to possess anti-diabetic properties. Moreover, increasing scientific evidence has demonstrated their potential anti-inflammatory and anti-oxidant effects. Consequently, the use of these compounds as anti-diabetic drugs has generated growing interest, as is reflected in the numerous in vitro and in vivo studies related to this field. Therefore, the aim of this review is to assess the recent pre-clinical and clinical research about the potential effect of flavonoids in the amelioration of diabetic complications. In brief, we provide updated information concerning the discrepancy between the numerous experimental studies supporting the eficacy of flavonoids on diabetic complications and the lack of appropriate and well-designed clinical trials. Due to the well-described beneficial effects on different mechanisms involved in diabetic complications, the excellent tolerability and low cost, future randomized controlled studies with compounds that have adequate bioavailability should be evaluated as add-on therapy on well-established anti-diabetic drugsThis paper was not funded. The authors work has been supported by FEDER-ISCIII Funds (PI17/00130, PI17/01495), Spanish Ministry of Economy and Competitiveness (RTI2018-098788-B-100, DTS17/00203, DTS19/00093, RYC-2017-22369), Spanish Society of Cardiology (SEC), Spanish Society of Nephrology (SEN) and Spanish Society of Atherosclerosis (SEA). TCO is an employee of FAES Pharma. The authors (except JAM) have an ongoing research project in common with FAES Pharma on Flavonoids in diabetic complications under the auspices of the joint-RETOS Collaborations Project 2017 (RTC-2017-6089-1), program supported by Spanish Ministry of Economy and Competitiveness