Proteins and metabolites as indicators of flours quality and nutritional properties of two durum wheat varieties grown in different Italian locations

Durum wheat is an important food source in Mediterranean countries, and Italy is the major producer of durum wheat in Europe. The quality of durum wheat flours depends on the type and amount of gluten proteins and starch while flour nutritional value rests on metabolite contents such as polyphenols. In this work, two Italian cultivars, Iride and Svevo, were analyzed for two years (2016–2017) in four Italian regions to explore how the environment affects: (i) reserve proteome; (ii) starch content and composition; and (iii) free, conjugated, bound phenolics and antioxidant capacity. The impact of environmental and meteorological conditions was significant for many traits. Regardless of the cultivation site, in 2017, a year with less rainfall and a higher temperature during grain filling, there was an increase in low molecular weight glutenins, in the glutenin/gliadin ratio and in the A–type starch granules size, all parameters of higher technological quality. In the same year, the cultivars showed higher amounts of polyphenols and antioxidant capacity. In conclusion, the two wheat cultivars, selected for their medium to high yield and their good quality, had higher performances in 2017 regardless of their sowing locations

Design of a Highly Portable Data Logging Embedded System for Naturalistic Motorcycle Study

According to Motorcycle Industrial Council (MIC), in USA the number of owned motorcycle increased during last few years and most likely will keep increasing. However, the number of the deadly crash accidents associated with motorcycles is on the rise. Although MIC doesn\u27t explain why the accident rate has increased, the unprotected motorcyclist gear can be one of the reasons. The most recent National Highway Traffic Safety Administration (NHTSA) annual report stated that its data analyses are based on their experiences and the best judgment is not based on solid scientific experiment [3]. Thus, building a framework for the data acquisition about the motorcyclist environment is a first step towards decreasing motorcyclist crashes. There are a few naturalistic motorcycle studies reported in the literature. The naturalistic motorcycle study also identifies the behaviors and environmental crash hazards. The primary objective of this thesis work is to design a highly portable data logging embedded system for naturalistic motorcycle study with capability of collecting many types of data such as images, speed, acceleration, time, location, distance approximation, etc. This thesis work is the first phase (of three phases) of a naturalistic motorcycle study project. The second phase is to optimize system area, form factor, and power consumption. The third phase will be concerned with aggressive low power design and energy harvesting. The proposed embedded system design is based on an Arduino microcontroller. A whole suite of Arduino based prototype boards, sensor boards, support software, and user forum is available. The system is high portable with capability to store up to eight (8) hours of text/image data during a one month study period. We have successfully designed and implemented the system and performed three trial runs. The data acquired has been validated and found to be accurate

Long-Short Term Memory for an Effective Short-Term Weather Forecasting Model Using Surface Weather Data

Part 7: Deep Learning - Convolutional ANNInternational audienceNumerical Weather Prediction (NWP) requires considerable computer power to solve complex mathematical equations to obtain a forecast based on current weather conditions. In this article, we propose a lightweight data-driven weather forecasting model by exploring state-of-the-art deep learning techniques based on Artificial Neural Network (ANN). Weather information is captured by time-series data and thus, we explore the latest Long Short-Term Memory (LSTM) layered model, which is a specialised form of Recurrent Neural Network (RNN) for weather prediction. The aim of this research is to develop and evaluate a short-term weather forecasting model using the LSTM and evaluate the accuracy compared to the well-established Weather Research and Forecasting (WRF) NWP model. The proposed deep model consists of stacked LSTM layers that uses surface weather parameters over a given period of time for weather forecasting. The model is experimented with different number of LSTM layers, optimisers, and learning rates and optimised for effective short-term weather predictions. Our experiment shows that the proposed lightweight model produces better results compared to the well-known and complex WRF model, demonstrating its potential for efficient and accurate short-term weather forecasting

Classification of nucleic acid amplification on ISFET arrays using spectrogram-based neural networks.

The COVID-19 pandemic has highlighted a significant research gap in the field of molecular diagnostics. This has brought forth the need for AI-based edge solutions that can provide quick diagnostic results whilst maintaining data privacy, security and high standards of sensitivity and specificity. This paper presents a novel proof-of-concept method to detect nucleic acid amplification using ISFET sensors and deep learning. This enables the detection of DNA and RNA on a low-cost and portable lab-on-chip platform for identifying infectious diseases and cancer biomarkers. We show that by using spectrograms to transform the signal to the time-frequency domain, image processing techniques can be applied to achieve the reliable classification of the detected chemical signals. Transformation to spectrograms is beneficial as it makes the data compatible with 2D convolutional neural networks and helps gain significant performance improvement over neural networks trained on the time domain data. The trained network achieves an accuracy of 84% with a size of 30kB making it suitable for deployment on edge devices. This facilitates a new wave of intelligent lab-on-chip platforms that combine microfluidics, CMOS-based chemical sensing arrays and AI-based edge solutions for more intelligent and rapid molecular diagnostics

Using Open Source Libraries in the Development of Control Systems Based on Machine Vision

The possibility of the boundaries detection in the images of crushed ore particles using a convolutional neural network is analyzed. The structure of the neural network is given. The construction of training and test datasets of ore particle images is described. Various modifications of the underlying neural network have been investigated. Experimental results are presented. © 2020, IFIP International Federation for Information Processing.Foundation for Assistance to Small Innovative Enterprises in Science and Technology, FASIEFunding. The work was performed under state contract 3170ΓC1/48564, grant from the FASIE

El juzgamiento de los delitos de lesa humanidad en la Argentina postdictatorial

Indice: Introducción (9) ; Garantismo y proceso a los militares: una categoría difícil para el par constituyente/constituido (13) por Hernán Bouvier; Reflexiones en torno a los fundamentos éticos y políticos de la imprescriptibilidad de los delitos de lesa humanidad. (53) por Daniela Domeniconi; El derecho a la educación de los condenados y procesados por delitos de lesa humanidad. Un análisis crítico de la Resolución del Consejo Superior de la UBA. (79) por María Valentina Risso y María Belén Gulli; Sobre el dominio territorial como requisito del elemento político en la definición de delitos de lesa humanidad. Un análisis enfocado en la calificación jurídica de los actos de la izquierda armada en Argentina. (107) Por Juan F. Iosa; Dictadura Argentina: el antagonismo en una misma sociedad (143) por Dana Antonela Loncon; Corte Interamericana de Derechos Humanos y Justicia Transicional: algunas inquietudes a partir de «Gelman» (169) por Juan M. Mocoroa ; ¿Retribución o venganza? Un problema en el marco de la justificación de los juicios por violación de derechos humanos. (209) Por Natalia ScavuzzoA 30 años del retorno de la democracia en Argentina y superado el período de clausura de responsabilidades generado por las leyes de obediencia debida y punto final durante el gobierno del presidente Alfonsín y por los indultos dictados en su momento por el presidente Menem, las instituciones argentinas han retomado el camino del juzgamiento y castigo de los máximos responsables de los delitos de lesa humanidad cometidos durante la última dictadura. Este proceso ha sido denominado «la tercera generación de juicios por violación de derechos humanos». Es altamente probable que con la adopción de esta vía institucional, y una vez avanzados los juicios y dictadas las condenas, comience a cerrarse un ciclo de la historia argentina, ciclo signado por las demandas de memoria, verdad y justicia de parte de nuestra sociedad y particularmente de los organismos de derechos humanos. Fortalece esta hipótesis la avanzada edad de la mayoría de los implicados en los delitos investigados. Las instituciones argentinas han elegido un camino que no ha carecido de cuestionamientos y que no ha sido compartido por una buena cantidad de países que vivieron procesos similares (los casos de Sudáfrica y Chile son paradigmáticos). Asimismo, las variadas cuestiones jurídico-políticas surgidas en ocasión de los juicios (imprescriptibilidad, retroactividad, perdón, castigo, alcance de las garantías procesales y de fondo para este tipo de casos, etc.) han dado lugar a posturas divergentes que aun hoy no están cerradas ni por la justicia, ni por la doctrina, ni por la sociedad en general. Bien se puede decir que el juzgamiento de estos delitos es un punto de intensidad jurídico-políticofilosófico donde se entrecruzan cuestiones de diversa naturaleza pero que comparten su centralidad para el desenvolvimiento de la democracia y la vigencia del estado de derecho en nuestro país. El presente volumen reúne una serie de ensayos que giran alrededor del juzgamiento de los delitos de lesa humanidad en la Argentina postdictatorial. Los trabajos son el producto de una investigación grupal de dos años, bajo la codirección de Juan Iosa y Hernán Bouvier, subsidiado por Secyt-UNC. Motivó este proyecto, entre otras cosas, la idea de que el juzgamiento de los hechos ocurridos entre 1976 y 1983 en Argentina requería un balance. La necesidad de este balance se imponía por múltiples razones. Entre ellas, los vaivenes políticos y jurídicos que signaron las diferentes etapas de juzgamiento, así como la percepción general de que por razones institucionales y generacionales una parte importante de los juicios estaba llegando a su culminación. Los juicios se tomaron como objeto de un estudio predominantemente (aunque no excluyentemente) normativo. Tuvo central importancia la evaluación crítica, desde los puntos de vista jurídico, moral y político, de las decisiones de los tribunales en estos casos

Changes in CD4+ cells’ miRNA expression following exposure to HIV-1

Background: MiRNAs inhibit HIV-1 expression by either modulating host innate immunity or by directly interfering with viral mRNAs. Here, we investigated the miRNA profile that discriminates different classes of HIV-1 infected patients from multiple exposed uninfected individuals. Methods: The expression levels of 377 miRNAs were selectively analyzed in CD4+ cells isolated from whole blood of HIV-1 \ue9lite LTNP (\ue9LTNP), naive, and multiply exposed uninfected individuals (MEU). MiRNA extraction was performed by the mirVana miRNA Isolation Kit (Ambion) and their expression was subsequently examined by real-time PCR-based arrays. The expression of miRNAs was also determined in primary culture of CD4+T cells and monocyte-macrophages infected in vitro by R5 strains. Expression of Dicer and Drosha was evaluated by real-time PCR. Results: We only considered miRNAs that were expressed in the 70% of patients of at least one class and varied by at least 1 log10 from healthy controls. Out of 377 miRNAs, 26 were up-regulated, while 88 were down-regulated. Statistical analysis showed that 21 miRNAs significantly differentiated \ue9LTNP from MEU and 23 miRNAs distinguished naive from MEU, while only 1 (miR-155) discriminated \ue9LTNP from naive. By hierarchical clustering of the miRNAs according to patient class, \ue9LTNP clustered with naive whereas all MEU subjects grouped together. The Dicer and Drosha expression in the patient classes correlated with miRNA profile changes. Among miRNAs differentially expressed in patient classes, 32 were detected in in vitro infection model: the most of the up-regulated miRNAs were expressed in monocyte-macrophages, whereas the most of the down-regulated miRNAs were expressed in T lymphocytes. Conclusions: These findings support that miRNA profile could be the result not only of a productive infection, but also of the exposure to HIV products that leave a signature in immune cells. These data provide some intriguing issues relative to the development of HIV vaccines targeting viral proteins

TORC1 Determines Fab1 Lipid Kinase Function at Signaling Endosomes and Vacuoles

Organelles of the endomembrane system maintain their identity and integrity during growth or stress conditions by homeostatic mechanisms that regulate membrane flux and biogenesis. At lysosomes and endosomes, the Fab1 lipid kinase complex and the nutrient-regulated target of rapamycin complex 1 (TORC1) control the integrity of the endolysosomal homeostasis and cellular metabolism. Both complexes are functionally connected as Fab1-dependent generation of PI(3,5)P2 supports TORC1 activity. Here, we identify Fab1 as a target of TORC1 on signaling endosomes, which are distinct from multivesicular bodies, and provide mechanistic insight into their crosstalk. Accordingly, TORC1 can phosphorylate Fab1 proximal to its PI3P-interacting FYVE domain, which causes Fab1 to shift to signaling endosomes, where it generates PI(3,5)P2. This, in turn, regulates (1) vacuole morphology, (2) recruitment of TORC1 and the TORC1-regulatory Rag GTPase-containing EGO complex to signaling endosomes, and (3) TORC1 activity. Thus, our study unravels a regulatory feedback loop between TORC1 and the Fab1 complex that controls signaling at endolysosomes