Software JClic como Método de Enseñanza para la Lectura

El software educativo JClic es una herramienta de apoyo pedagógico; que puede dar soluciones significativas a los docentes, ante la gran exigencia de usar una estrategia innovadora para fortalecer la lectura de los estudiantes. Este estudio tiene como propósito; Promover actividades pedagógicas para el uso del software JClic como método de enseñanza para fortalecer la lectura de los estudiantes, siendo la lectura; una de las grandes debilidades académicas en la actualidad. Con la creación de estrategias de enseñanza mediante este software didáctico, se afianzará el aprendizaje de la lectura. La direccionalidad de la investigación adopta un enfoque cualitativo, inmerso en el paradigma socio crítico, con una modalidad de investigación acción participativa, teniendo como diseño las fases de; diagnóstico, planificación, ejecución y evaluación. Para obtener información veraz, se consideraron como actores sociales a todos los docentes de aula que hacen vida en una escuela específica, y para precisar la información se tomaron como informantes clave a tres (3) docentes de aula, en virtud de que cumplen con las cualidades necesarias para apoyar teóricamente la investigación a través de la entrevista semiestructurada, a su vez, se empleó la técnica de la observación participante, obteniendo una validez descriptiva e interpretativa de la información

Saturn's icy satellites and rings investigated by Cassini - VIMS. III. Radial compositional variability

In the last few years Cassini-VIMS, the Visible and Infared Mapping Spectrometer, returned to us a comprehensive view of the Saturn's icy satellites and rings. After having analyzed the satellites' spectral properties (Filacchione et al. (2007a)) and their distribution across the satellites' hemispheres (Filacchione et al. (2010)), we proceed in this paper to investigate the radial variability of icy satellites (principal and minor) and main rings average spectral properties. This analysis is done by using 2,264 disk-integrated observations of the satellites and a 12x700 pixels-wide rings radial mosaic acquired with a spatial resolution of about 125 km/pixel. The comparative analysis of these data allows us to retrieve the amount of both water ice and red contaminant materials distributed across Saturn's system and the typical surface regolith grain sizes. These measurements highlight very striking differences in the population here analyzed, which vary from the almost uncontaminated and water ice-rich surfaces of Enceladus and Calypso to the metal/organic-rich and red surfaces of Iapetus' leading hemisphere and Phoebe. Rings spectra appear more red than the icy satellites in the visible range but show more intense 1.5-2.0 micron band depths. The correlations among spectral slopes, band depths, visual albedo and phase permit us to cluster the saturnian population in different spectral classes which are detected not only among the principal satellites and rings but among co-orbital minor moons as well. Finally, we have applied Hapke's theory to retrieve the best spectral fits to Saturn's inner regular satellites using the same methodology applied previously for Rhea data discussed in Ciarniello et al. (2011).Comment: 44 pages, 27 figures, 7 tables. Submitted to Icaru

Minimum Noise Fraction Analysis of TGO/NOMAD LNO Channel High-Resolution Nadir Spectra of Mars

NOMAD is a suite of spectrometers on the board of the ESA-Roscosmos Trace Gas Orbiter (TGO) spacecraft and is capable of investigating the Martian environment at very high spectral resolution in the ultraviolet–visible and infrared spectral ranges by means of three separate channels: UVIS (0.2–0.65 μm), LNO (2.2–3.8 μm), and SO (2.3–4.3 μm). Among all channels, LNO is the only one operating at infrared wavelengths in nadir-viewing geometry, providing information on the whole atmospheric column and on the surface. Unfortunately, the LNO data are characterized by an overall low level of signal-to-noise ratio (SNR), limiting their contribution to the scientific objectives of the TGO mission. In this study, we assess the possibility of enhancing LNO nadir data SNR by applying the Minimum Noise Fraction (MNF), a well-known algorithm based on the Principal Components technique that has the advantage of providing transform eigenvalues ordered with increasing noise. We set up a benchmark process on an ensemble of synthetic spectra in order to optimize the algorithm specifically for LNO datasets. We verify that this optimization is limited by the presence of spectral artifacts introduced by the MNF itself, and the maximum achievable SNR is dependent on the scientific purpose of the analysis. MNF application study cases are provided to LNO data subsets in the ranges 2.627–2.648 μm and 2.335–2.353 μm (spectral orders 168 and 189, respectively) covering absorption features of gaseous H2O and CO and CO2 ice, achieving a substantial enhancement in the quality of the observations, whose SNR increases up to a factor of 10. While such an enhancement is still not enough to enable the investigation of spectral features of faint trace gases (in any case featured in orders whose spectral calibration is not fully reliable, hence preventing the application of the MNF), interesting perspectives for improving retrieval of both atmospheric and surface features from LNO nadir data are implied

Martian CO₂ Ice Observation at High Spectral Resolution With ExoMars/TGO NOMAD

The Nadir and Occultation for MArs Discovery (NOMAD) instrument suite aboard ExoMars/Trace Gas Orbiter spacecraft is mainly conceived for the study of minor atmospheric species, but it also offers the opportunity to investigate surface composition and aerosols properties. We investigate the information content of the Limb, Nadir, and Occultation (LNO) infrared channel of NOMAD and demonstrate how spectral orders 169, 189, and 190 can be exploited to detect surface CO2 ice. We study the strong CO2 ice absorption band at 2.7 μm and the shallower band at 2.35 μm taking advantage of observations across Martian Years 34 and 35 (March 2018 to February 2020), straddling a global dust storm. We obtain latitudinal‐seasonal maps for CO2 ice in both polar regions, in overall agreement with predictions by a general climate model and with the Mars Express/OMEGA spectrometer Martian Years 27 and 28 observations. We find that the narrow 2.35 μm absorption band, spectrally well covered by LNO order 189, offers the most promising potential for the retrieval of CO2 ice microphysical properties. Occurrences of CO2 ice spectra are also detected at low latitudes and we discuss about their interpretation as daytime high altitude CO2 ice clouds as opposed to surface frost. We find that the clouds hypothesis is preferable on the basis of surface temperature, local time and grain size considerations, resulting in the first detection of CO2 ice clouds through the study of this spectral range. Through radiative transfer considerations on these detections we find that the 2.35 μm absorption feature of CO2 ice clouds is possibly sensitive to nm‐sized ice grains

Evidence for transient morning water frost deposits on the Tharsis volcanoes of Mars

The present-day water cycle on Mars has implications for habitability and future human exploration. Water ice clouds and water vapour have been detected above the Tharsis volcanic province, suggesting the active exchange of water between regolith and atmosphere. Here we report observational evidence for extensive transient morning frost deposits on the calderas of the Tharsis volcanoes (Olympus, Arsia and Ascraeus Montes, and Ceraunius Tholus) using high-resolution colour images from the Colour and Stereo Surface Imaging System on board the European Space Agency’s Trace Gas Orbiter. The transient bluish deposits appear on the caldera floor and rim in the morning during the colder Martian seasons but are not present by afternoon. The presence of water frost is supported by spectral observations, as well as independent imagery from the European Space Agency’s Mars Express orbiter. Climate model simulations further suggest that early-morning surface temperatures at the high altitudes of the volcano calderas are sufficiently low to support the daily condensation of water—but not CO2 —frost. Given the unlikely seasonal nature of volcanic outgassing, we suggest the observed frost is atmospheric in origin, implying the role of microclimate in local frost formation and a contribution to the broader Mars water cycle

L'Italia come modello per l'Europa e per il mondo nelle politiche sanitarie per il trattamento dell'epatite cronica da HCV

The World Health Organization foresees the elimination of HCV infection by 2030. In light of this and the curre nt, nearly worldwide, restriction in direct-acting agents (DAA) accessibility due to their high price, we aimed to evaluate the cost-effectiveness of two alternative DAA treatment policies: Policy 1 (universal): treat all patients, regardless of the fibrosis stage; Policy 2 (prioritized): treat only priori tized patients and delay treatment of the remaining patients until reaching stage F3. T he model was based on patient’s data from the PITER cohort. We demonstrated that extending HC V treatment of patients in any fibrosis stage improves health outcomes and is cost-effective

Software JClic como Método de Enseñanza para la Lectura

JClic educational software is a pedagogical support tool; that can give meaningful solutions to teachers, before the great demand to use an innovative strategy to strengthen the reading of students. This study is for the purpose; Promote pedagogical activities for the use of JClic software as a teaching method to improve student Reading, being reading; one of the great academic weaknesses today, with the creation of teaching strategies through this didactic software, the learning of reading will be strengthened. The directionality of the research adopts a qualitative approach, immersed in the critical partner paradigm, with a modality of participatory action research, having as design the phases of; diagnosis, planning, execution and evaluation. To obtain truthful information, all the classroom teachers who live in a specific school were considered as social actors, and to clarify the information, three (3) classroom teachers were taken as key informants, by virtue of fulfilling the necessary qualities to theoretically support research through the semi-structured interview, at the same time, the technique of participant observation was used, obtaining a descriptive and interpretative validity of the information. Determining, that this software; acts as a teaching medium of great scope for the teacher in their teaching methods for reading.El software educativo JClic es una herramienta de apoyo pedagógico; que puede dar soluciones significativas a los docentes, ante la gran exigencia de usar una estrategia innovadora para fortalecer la lectura de los estudiantes. Este estudio tiene como propósito; Promover actividades pedagógicas para el uso del software JClic como método de enseñanza para fortalecer la lectura de los estudiantes, siendo la lectura; una de las grandes debilidades académicas en la actualidad. Con la creación de estrategias de enseñanza mediante este software didáctico, se afianzará el aprendizaje de la lectura. La direccionalidad de la investigación adopta un enfoque cualitativo, inmerso en el paradigma socio crítico, con una modalidad de investigación acción participativa, teniendo como diseño las fases de; diagnóstico, planificación, ejecución y evaluación. Para obtener información veraz, se consideraron como actores sociales a todos los docentes de aula que hacen vida en una escuela específica, y para precisar la información se tomaron como informantes clave a tres (3) docentes de aula, en virtud de que cumplen con las cualidades necesarias para apoyar teóricamente la investigación a través de la entrevista semiestructurada, a su vez, se empleó la técnica de la observación participante, obteniendo una validez descriptiva e interpretativa de la información

Leveraging Spatio-Temporal Autocorrelation to Improve the Forecasting of the Energy Consumption in Smart Grids

Smart grids are networks that distribute electricity by relying on advanced communication technologies, sensor measurements, and predictive methods, to quickly adapt the network behavior to different possible scenarios. In this context, the adoption of machine learning approaches to forecast the customer energy consumption is essential to optimize network planning operations, avoid unnecessary energy production, and minimize power shortages. However, classical forecasting methods are not able to take into account spatial and temporal auto-correlation phenomena, naturally introduced by the spatial proximity of consumers, and by the seasonality of the energy consumption trends.In this paper, we investigate the adoption of several solutions to take into account spatio-temporal autocorrelation phenomena. Specifically, we investigate the contribution provided by the explicit representation of temporal i-nformation related to historical measurements using multiple strategies, as well as that of simultaneously predicting multiple future consumption measurements in a multi-step predictive setting. Finally, we investigate the effectiveness of injecting descriptive features to make the learning methods aware of the spatial closeness among the consumers.The experimental evaluation performed on a real-world electrical network demonstrated the positive contribution of making the models aware of spatio-temporal autocorrelation phenomena, and proved the overall superiority of models based on the multi-step predictive setting

Non-invasive Prenatal Testing Using Fetal DNA

Non-invasive prenatal diagnosis (NIPD) is based on fetal DNA analysis starting from a simple peripheral blood sample, thus avoiding risks associated with conventional invasive techniques. During pregnancy, the fetal DNA increases to approximately 3–13% of the total circulating free DNA in maternal plasma. The very low amount of circulating cell-free fetal DNA (ccffDNA) in maternal plasma is a crucial issue, and requires specific and optimized techniques for ccffDNA purification from maternal plasma. In addition, highly sensitive detection approaches are required. In recent years, advanced ccffDNA investigation approaches have allowed the application of non-invasive prenatal testing (NIPT) to determine fetal sex, fetal rhesus D (RhD) genotyping, aneuploidies, micro-deletions and the detection of paternally inherited monogenic disorders. Finally, complex and innovative technologies such as digital polymerase chain reaction (dPCR) and next-generation sequencing (NGS) (exhibiting higher sensitivity and/or the capability to read the entire fetal genome from maternal plasma DNA) are expected to allow the detection, in the near future, of maternally inherited mutations that cause genetic diseases. The aim of this review is to introduce the principal ccffDNA characteristics and their applications as the basis of current and novel NIPT