Measurement of the 235U(n,f) cross section relative to the 6Li(n,t) and 10B(n,a) standards from thermal to 170 keV neutron energy range at n_TOF

The 235U(n,f) cross section was measured in a wide energy range at n_TOF relative to 6Li(n,t) and 10B(n,alpha), with high resolution and in a wide energy range, with a setup based on a stack of six samples and six silicon detectors placed in the neutron beam. This allowed us to make a direct comparison of the reaction yields under the same experimental conditions, and taking into account the forward/backward emission asymmetry. A hint of an anomaly in the 10÷30 keV neutron energy range had been previously observed in other experiments, indicating a cross section systematically lower by several percent relative to major evaluations. The present results indicate that the evaluated cross section in the 9÷18 keV neutron energy range is indeed overestimated, both in the recent updates of ENDF/B-VIII.0 and of the IAEA reference data. Furthermore, these new high-resolution data confirm the existence of resonance-like structures in the keV neutron energy region. The new, high accuracy results here reported may lead to a reduction of the uncertainty in the 1÷100 keV neutron energy region. Finally, the present data provide additional confidence on the recently re-evaluated cross section integral between 7.8 and 11 eV.Preprin

RThybrid: A standardized and open-source real-time software model library for experimental neuroscience

Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.This work was supported by MINECO/FEDER DPI2015-65833-P, TIN2017-84452-R and ONRG grant N62909-14-1-N27

Discriminating irrigated and rainfed maize with diurnal fluorescence and canopy temperature airborne maps

This study evaluates the potential of airborne remote sensing images to detect water stress in maize. Visible and near infrared CASI (Itres Research Ltd., Canada) and thermal AHS-160 (Sensytech Inc., USA) data were acquired at three different times during the day on a maize field (Zea mays L.) grown with three different irrigation treatments. An intensive field campaign was also conducted concurrently with image acquisition to measure leaf ecophysiological parameters and the Leaf Area Index (LAI). The analysis of the field data showed that maize plants were experiencing moderate to severe water stress in rainfed plots and a weaker stress condition in the plots with water deficit imposed between stem elongation and flowering. Vegetation indices including the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) computed from the CASI images, sun-induced chlorophyll fluorescence and canopy temperature (Tc) showed different performances in describing the water stress during the day. During the morning overpasses NDVI was the index with the highest discriminant power. As the day progressed, processes related to heat dissipation through plant transpiration became more and more important and at midday Tc showed the best performances. Furthermore, Tc retrieved from the midday image was the only index able to distinguish all the three classes of water status. Finally, during the afternoon PRI and F760 showed the best performances. These results demonstrate the feasibility to detect water stress using thermal and optical airborne data, pointing out the importance of a careful planning of the airborne surveys as a function of the specific aims of the study.JRC.H.4 - Monitoring Agricultural Resource

La fatiga entre los estudiantes de enfermería

A fadiga entre os estudantes pode prejudicar a aprendizagem. Avaliou-se a fadiga de graduandos de enfermagem e as relações com o ano de graduação, a participação em atividades extracurriculares, com quem o aluno reside, com a depressão e o índice de massa corporal (IMC). Participaram 189 (60,2%) estudantes da EEUSP, sendo 96,2% de mulheres com idade média de 21,6 anos, 80,9% residiam com os pais, 43,9% realizavam atividades extracurriculares, 24,8% tinham IMC alterado e 22,2% apresentaram disforia ou depressão (Inventário de Depressão de Beck). A fadiga foi moderada/ intensa para 83,5% dos estudantes (Escala de Fadiga de Piper Revisada e Pictograma de Fadiga) e 59,8% relataram prejuízo moderado/intenso nas atividades habituais. A fadiga apresentou correlação positiva com ano de graduação, com o IMC e a depressão (p<0,001). A atividade acadêmica foi a principal causa de fadiga, enquanto o sono e o lazer foram as estratégias mais utilizadas para seu manejo. A fadiga foi significativa e intensa, todavia observou-se descompasso entre freqüência, magnitude e impacto da fadiga nas atividades da vida diária.Fatigue among students may harm their learning. This study evaluated the fatigue of nursing undergraduate students and its relations to their graduation year, participation in extracurricular activities, people with whom they lived, depression and their body mass index (BMI)). The study had the participation of 189 (60.2%) students from the EEUSP, from which 96.2% were women with the average age of 21.6 years old, 80.9% lived with their parents, 43.9% performed extracurricular activities, 24.8% had varied BMI and 22.2% presented dysphoria or depression (Beck Depression Inventory). Fatigue was moderate/intense for 83.5% of the students (Piper Fatigue Scale - Revised and Fatigue Pictogram) and 59.8% reported moderate/intense impairment in their habitual activities. Fatigue presented a positive correlation to the graduation year, to the BMI and to depression (p<0.001). The academic activity was the main cause of fatigue, whereas sleep and leisure were the most frequent strategies to handle it. Fatigue was significant and intense, but there was an irregularity between its frequency, magnitude and impact in the daily life activities.La fatiga en los estudiantes puede ser perjudicial para el aprendizaje. Se evaluó la fatiga en estudiantes de enfermería y sus relaciones con el año de estudio, participación en actividades extracurriculares, personas con las que el alumno reside, depresión e índice de masa corporal (IMC). Participaron 189 (60,2%) estudiantes de la EEUSP; 96,2% mujeres, edad media de 21,6 años, 80,9% residía con sus padres, 43,9% realizaba actividades extracurriculares, 24,8% exhibía alteraciones en su IMC y 22,2% presentaban disforia o depresión (Inventario de Depresión de Beck). La fatiga fue moderada/intensa para el 83,5% de los estudiantes (Escala de Fatiga de Piper Revisada y Pictograma de Fatiga), y 59,8% refirieron perjuicio moderado/intenso en las actividades habituales. La fatiga presentó correlación positiva con el año de estudio, con el IMC y con la depresión (p < 0,001). La actividad académica fue la principal causa de fatiga, sueño y recreación fueron las estrategias más utilizadas en su control. La fatiga fue significativa e intensa, aunque se observaron divergencias entre frecuencia, magnitud e impacto de la fatiga en las actividades de la vida diaria

Preface: AgriVoltaics World Conference 2022

In 2020, the AgriVoltaics conference was “launched” and the small community, working to develop innovative solutions to combine agricultural production and PV energy, met for the first time. It was great and surprising to see that this community was actually not so small; it was spread over all five continents, and united by the belief that agrivoltaics is perfectly suited to a sustainable energy transition. We all know that there is no one solution to suit all, and that we have a long road ahead to further understand and improve agrivoltaic systems. It is in this time, when sustainable solution are urgently needed, that our community must collaborate to accelerate the availability of sound agrivoltaic systems. Exchange of information and experiences was at the core of Agrivoltaics2021, where the importance of “connecting” agrivoltaics worldwide was highlighted, and despite it being held online it was a great success! The growth of agrivoltaics is exponential, as indicated by the ever-increasing number of scientific publications on the topic, by the number of new agrivoltaic systems installed and last but not least, by the interest that large energy players and governments have paid to agrivoltaics. Our community now has a great opportunity, but also a responsibility to develop and bring forward true agrivoltaic systems where the production of PV electricity is necessarily coupled to agricultural production. While we work to optimise AV systems, we must also make sure that the policies supporting their implementation will prevent agrivoltaic projects from being abandoned, and becoming nothing more than ground mounted PV systems. This should be our concern when “bringing agrivoltaics forward”. Bringing agrivoltaics forward was therefore the theme and focus of AgriVoltaics2022 Conference, and with 488 participants from 46 countries (and more than half on-site) it was a great success. The program embraced a broad spectrum of topics ranging from policy making, economics and social acceptance to technical and scientific aspects related to the modelling and validation of crop production under agrivoltaics and technological advances in agrivoltaic systems. The need for a sustainable integration of agrivoltaics systems into the landscape was also addressed in many presentations. In addition, a Sustainable Agrivoltaic Integration Challenge was organised and a Student Award was granted. These proceedings provide a comprehensive overview of all the topics presented at AgriVoltaics2022 and are a testimony to the growing contribution that the international scientific community is making to bring agrivoltaics forward.   Stefano Amaducci Università Cattolica del Sacro Cuore Conference Chair AgriVoltaics202

Inhalation therapy in the next decade : Determinants of adherence to treatment in asthma and COPD

Peer reviewedPublisher PD

Reduced order modelling of combustion using convolutional neural network

It is well known that CFD simulations of a complex combustion system, such as Moderate or Intense Low-oxygen Dilution (MILD) combustion, requires consid- erable computational resources. This precludes various applications including the use of CFD in real time control systems. The idea of a reduced order model (ROM) was born from the desire to overcome this obstacle. A ROM, if properly instructed, returns the output of a requested CFD simulation in extremely short time. This one is an ideal mechanism with two basic gears: the input size reduction technique and the interpolation method. This project proposes a study on the applicability of convolutional neural network (CNN) as a dimensionality reduction technique. The code written for this purpose will be presented in detail, as well as pre and post processing. A sensibility analysis will be carry out to find out which parame- ters to adjust and how in order to achieve the optimum. Finally, the network will be compared in its peculiarity and its results with Principal Component Analysis (PCA), the technique used by the BURN group of Libre University of Bruxelles for the same purpose. Moreover with the desire to improve, we went further by trying to overcome the limits dictated by the rules of a legitimate comparation between PCA and CNN. Lastly, the author considers necessary to provide the theoretical basis in order to enrich and support what has just been described. Therefore, you will also find introductions / insights on MILD combustion, CFD of a combustion system, neural networks and the aspects related to them