Latest Depleted CMOS Sensor Developments in the CERN RD50 Collaboration

This contribution summarizes the most recent activities carried out within the CERN RD50 collaboration with regard to Depleted Monolithic Active Pixel Sensors (DMAPS). In particular, these activities have been focused on the characterization of the RD50-MPW2 prototype. RD50-MPW2 is the second DMAPS prototype developed in the 150 nm HV-CMOS technology process from LFoundry. The main characteristics of the RD50-MPW2 design will be reviewed. The leakage current, breakdown voltage and Edge Transient Current Technique (E-TCT) measurements of the RD50-MPW2 test structures will be presented. The characterization of the RD50-MPW2 active matrix and its readout electronics will be also described. Finally, the initial characteristics of the new RD50-MPW3 DMAP sensor prototype being designed at present by the CERN-RD50 collaboration will be shown

Caracterización y diagnóstico energético Congelados Farah

De acuerdo con los estudios realizados por los diferentes organismos para el desarrollo de la eficiencia energética, uno de los sectores productivos con mayor potencial de aumento de eficiencia energética y reducción de efluentes contaminantes, es el de la industria alimentaria. El objetivo del trabajo es realizar una caracterización energética que nos lleve al uso eficiente de la energía, enfocada en su mayoría en el análisis del consumo eléctrico, justificado por su rentabilidad en la reducción de costos energéticos, logrando así una mayor producción, esto por medio del diseño eléctrico para el cálculo adecuado de conductores según las cargas existentes y detección de pérdidas por medio de punto calientes en equipos y conductoresIncluye bibliografía, anexo

Tests for Waterproofing Materials, Made of Opuntia ficus-indica

Cacti are thoroughly found all across the Mexican Territory. In the mountain ranges, and sierras. The cactus known as Opuntia ficus-indica grows naturally in the State of Mexico. Cacti have been used for millennia for multiple purposes. From culinary, to art involving other materials such as calcium oxide and salt. There are about 300 different species of cacti around the globe. About 100 are found in Mexico. Extensive research has been made and often, new and innovative uses are discovered. This paper features another use for Opuntia ficus-indica: Waterproofing on building surfaces exposed to the elements (i.e. Sunlight and humidity). This paper shows the process involving six stages using Opuntia ficus-indica combined with different natural materials were experimented with, and tested by evaluating their unique performance.Mexican cacti have captivated the scientific community due their extraordinary characteristics and benefits.This research established a new way to use this ancestral plant as a substitute for other construction materials that given their industrial and technological processes have -in several cases- skyrocketed their costs, besides of being a constant hazard for the environment. Thus, by looking back how ancestors used to solve their construction needs, it would ultimately allow us to find better ways to protect the environment. Production process is analyzed; experimented with it; and its prominent characteristics analyzed derived from Opuntia ficus-indica extract combined with other natural materials to be then used it as a waterproofing material

Feature density as an uncertainty estimator method in the binary classification mammography images task for a supervised deep learning model

Labeled medical datasets may include a limited number of observations for each class, while unlabeled datasets may include observations from patients with pathologies other than those observed in the labeled dataset. This negatively influences the performance of the prediction algorithms. Including out-of-distribution data in the unlabeled dataset can lead to varying degrees of performance degradation, or even improvement, by using a distance to measure how out-of-distribution a piece of data is. This work aims to propose an approach that allows estimating the predictive uncertainty of supervised algorithms, improving the behaviour when atypical samples are presented to the distribution of the dataset. In particular, we have used this approach to mammograms X-ray images applied to binary classification tasks. The proposal makes use of Feature Density, which consists of estimating the density of features from the calculation of a histogram. The obtained results report slight differences when different neural network architectures and uncertainty estimators are usedUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Primer registro de la cojolita (Penelope purpurascens) en el estado de Guanajuato, México

-Aquí se informa sobre el registro de la cojolita en la Reserva de Biosfera Sierra Gorda de Guanajuato, el cual es el registro más central para esa latitud y el primero para el estado. Esta especie fue registrada fotográfícamente en un bosque de encino. La presencia de esta especie enfatiza la necesidad de continuar realizando inventarios biológicos en esta Reserva de la Biosfer

Answering confucius: The reason why we complicate

Learning is a level-progressing process. In any field of study, one must master basic concepts to understand more complex ones. Thus, it is important that during the learning process learners are presented and challenged with knowledge which they are able to comprehend (not a level below, not a level too high). In this work we focus on language learners. By gradually improving (complicating) texts, readers are challenged to learn new vocabulary. To achieve such goals, in this paper we propose and evaluate the 'complicator' that translates given sentences to a chosen level of higher degree of difficulty. The 'complicator' is based on natural language processing and information retrieval approaches that perform lexical replacements. 30 native English speakers participated in a user study evaluating our methods on an expert-tailored dataset of children books. Results show that our tool can be of great utility for language learners who are willing to improve their vocabulary. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40814-4_45.TERENCEEC/FP

RF Acquisition System Based on μTCA for Testing of High-Gradient Acceleration Cavities

The radio frequency (RF) laboratory hosted in the Corpuscular Physics Institute (IFIC) of the University of Valencia is designed to house a high-power and high-repetition-rate facility to test normal conduction RF accelerator cavities in the S-Band (2.9985 GHz) in order to perform R&D activities related to particle accelerator cavities. The system, which manages the entire process of RF signal generation, data acquisition and closed-loop control of the laboratory, is currently based on a modular and compact PXI platform system. This contribution details the development of a platform with similar features, but which is based on open architecture standards at both the hardware and software level. For this purpose, a complete system based on the μTCA platform has been developed. This new system must be able to work with accelerator cavities at other operating frequencies, such as 750 MHz, as well as to explore different options at firmware and software levels based on open-source codes

Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Applied immunology; Predictive markers; Viral infectionImmunologia aplicada; Marcadors predictius; Infecció viralInmunología aplicada; Marcadores predictivos; Infección viralQuantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient’s immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy.This work was supported by Health Holland LSHM20056 grant (PDK), in part from the European Union’s Horizon 2020 research and innovation program under grant agreement No 779295 (PDK), in part supported by the Erasmus foundation (BJAR), grant PI20/00416 from the Instituto de Salud Carlos III (RPB) and the European Regional Development Fund (ERDF) (RPB)

Biological Activities of Extracts from Aerial Parts of Salvia pachyphylla Epling Ex Munz

Abstract: The antioxidant, antimicrobial, antiproliferative, and enzyme inhibitory properties of five extracts from aerial parts of Salvia pachyphylla Epling ex Munz were examined to assess the prospective of this plant as a source of natural products with therapeutic potential. These properties were analyzed by performing a set of standard assays. The extract obtained with dichloromethane showed the most variety of components, as they yielded promising results in all completed assays. Furthermore,theextractobtainedwithethylacetateexhibitedthegreatestantioxidantactivity,aswell as the best xanthine oxidase inhibitory activity. Remarkably, both extracts obtained with n-hexane or dichloromethane revealed significant antimicrobial activity against the Gram-positive bacteria; additionally, they showed greater antiproliferative activity against three representative cell lines of the most common types of cancers in women worldwide, and against a cell line that exemplifies cancers that typically develop drug resistance. Despite that, other extracts were less active, such as the methanolic or aqueous; their results are promising for the isolation and identification of novel bioactive molecules

Synthesis, Biological Evaluation and Docking Studies of Chalcone and Flavone Analogs as Antioxidants and Acetylcholinesterase Inhibitors

Several oxidative processes are related to a wide range of human chronic and degenerative diseases, like Alzheimer’s disease, which also has been related to cholinergic processes. Therefore, search for new or improved antioxidant molecules with acetylcholinesterase activity is essential to offer alternative chemotherapeutic agents to support current drug therapies. A series of chalcone (2a–2k) and flavone (3a–3k) analogs were synthesized, characterized, and evaluated as acetylcholinesterase (AChE) inhibitors, and antioxidant agents using 1,1-diphenyl-2-picrylhydrazyl (DPPH•), 2-20-azino-bis-(3-ethylbenzothiazoline-6-sulfonate) (ABTS•), and β-carotene/linoleic acid bleaching assay. Compounds more active were 3j and 2k in DPPH with EC50 of 1 × 10−8 and 5.4 × 10−3 µg/mL, respectively; 2g and 3i in ABTS (1.14 × 10−2 and 1.9 × 10−3 µg/mL); 2e, 2f, 3f, 2j, and 3j exceeded the α-tocopherol control in the β-carotene assay (98–99% of antioxidant activity). At acetylcholinesterase inhibition assay, flavones were more active than chalcones; the best results were compounds 2d and 3d (IC50 21.5 and 26.8 µg/mL, respectively), suggesting that the presence of the nitro group enhances the inhibitory activity. The docking of these two structures were made to understand their interactions with the AChE receptor. Although further in vivo testing must be performed, our results represent an important step towards the identification of improved antioxidants and acetylcholinesterase inhibitors