Maintenance and manipulation of object sequences in working memory: a lifespan study

Many studied reported that working memory components receive remarkable changes during lifespan. In order to better investigate this, we evaluated working memory components on human subjects belonging to five groups (10 subjects each) at different ages 6, 8 and 10 years old, young adult (age) and old adult (age). Our pattern of results shows a major transition in object sequence manipulation performance between ages 8 and 10 years. If related to young adults results, both 10-year-old children and old adults differed in accuracy and RT in both maintenance and manipulation conditions. In particular, young adults and old adults differ in RTs in the manipulation condition. Our results also suggest that a change in response strategy from 6 to 8 years of age, to prioritize accuracy may be present. Our findings appear consistent with recent neuroscientific findings, and lead to novel predictions

Molecular dynamics study of the pore formation in single layer graphene oxide by a thermal reduction process

The shape/dimension of the oxidized clusters and the process temperature were found to be the main factors affecting pore formation in GO membranes produced with a thermal reduction process

Prediction of the structural and electronic properties of MoxTi1−xS2 monolayers via first principle simulations

Two-dimensional transition metal dichalcogenides have gained great attention because of their peculiar physical properties that make them interesting for a wide range of applications. Lately, alloying between different transition metal dichalcogenides has been proposed as an approach to control two-dimensional phase stability and to obtain compounds with tailored characteristics. In this theoretical study, we predict the phase diagram and the electronic properties of MoxTi1−xS2 at varying stoichiometry and show how the material is metallic, when titanium is the predominant species, while it behaves as a p-doped semiconductor, when approaching pure MoS2 composition. Correspondingly, the thermodynamically most stable phase switches from the tetragonal to the hexagonal one. Further, we present an example which shows how the proposed alloys can be used to obtain new vertical two-dimensional heterostructures achieving effective electron/hole separation

Stability and Bandgap Engineering of In1-{xGaxSe} Monolayer

Bandgap engineering of semiconductor materials represents a crucial step for their employment in optoelectronics and photonics. It offers the opportunity to tailor their electronic and optical properties, increasing the degree of freedom in designing new devices and widening the range of their possible applications. Here, we report the bandgap engineering of a layered InSe monolayer, a superior electronic and optical material, by substituting In atoms with Ga atoms. We developed a theoretical understanding of [Formula: see text] stability and electronic properties in its whole compositional range ([Formula: see text]) through first-principles density functional theory calculations, the cluster expansion method, and kinetic Monte Carlo simulations. Our findings highlight the possibility of modulating the InGaSe bandgap by ≈0.41 eV and reveal that this compound is an excellent candidate to be employed in many optoelectronic and photonic devices

High rejection stacked single-layer graphene membranes for water treatment

Nowadays, the production of pure water from saltwater and wastewater is one of the most challenging issues. Polymeric materials represent, at the moment, the best solution for membranes technology but new materials with improved functionalities are desirable to overcome the typical limitations of polymers. In this work, graphene membranes with superior filtration properties are fabricated by stacking up to three graphene layers on a porous support and exploiting the intrinsic nanopores of graphene to filter diclofenac (drug), and methylene blue (dye). The rejection improves increasing the number of the stacked graphene layers, with the best results obtained with three graphene layers. Mass diffusion properties depend on the size of the probe molecule, consistently with the existence of intrinsic nanometer-sized pores within graphene. From the results of an in depth transmission electron microscopy analysis and molecular dynamics simulations it is inferred that graphene stacking results in a decrease of effective membrane pore sizes to about 13 Å diameter which corresponds to 97% rejection for diclofenac and methylene blue after one hour filtration

Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis

Background: This study aims to evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees. Methods: Prospective observational study were conducted between 1 and 30 April 2022. Transvaginal ultrasound (TVUS) diagnosis of adenomyosis was investigated by an experienced sonographer on 100 fertile-age patients. Videoclips of the uterine corpus were recorded and sequential ultrasound images were extracted. Intermediate ultrasound-skilled trainees and DL machine were asked to make a diagnosis reviewing uterine images. We evaluated and compared the accuracy, sensitivity, positive predictive value, F1-score, specificity and negative predictive value of the DL model and the trainees for adenomyosis diagnosis. Results: Accuracy of DL and intermediate ultrasound-skilled trainees for the diagnosis of adenomyosis were 0.51 (95% CI, 0.48–0.54) and 0.70 (95% CI, 0.60–0.79), respectively. Sensitivity, specificity and F1-score of DL were 0.43 (95% CI, 0.38–0.48), 0.82 (95% CI, 0.79–0.85) and 0.46 (0.42–0.50), respectively, whereas intermediate ultrasound-skilled trainees had sensitivity of 0.72 (95% CI, 0.52–0.86), specificity of 0.69 (95% CI, 0.58–0.79) and F1-score of 0.55 (95% CI, 0.43–0.66). Conclusions: In this preliminary study DL model showed a lower accuracy but a higher specificity in diagnosing adenomyosis on ultrasonographic images compared to intermediate-skilled trainees

Creación y Simulación de Metodologías de Análisis, Clasificación e Integración de Nuevos Requerimientos a Software Propietario

La priorización de nuevos requerimientos a implementar en un software propietario es un punto fundamental para su mantenimiento, la conservación de la calidad, observación de las reglas de negocio y los estándares de la empresa. Aunque existen herramientas de priorización basadas en técnicas probadas y reconocidas, las mismas requieren una calificación previa de cada requerimiento. Si la empresa cuenta con solicitudes provenientes de varios clientes de un mismo producto, aumentan los factores que afectan a la empresa, las herramientas disponibles no contemplan estos aspectos y hacen mucho más compleja la tarea de calificación. Este trabajo de investigación abarca la realización de un relevamiento de los métodos de priorización y selección de nuevos requerimientos utilizados por empresas de la zona de Rosario, y la definición de una metodología para la selección un nuevo requerimiento, que implica el análisis y evaluación de todas las implicaciones sobre el producto de software y la empresa, respetando sus reglas de negocio. La metodología creada conduce a la definición de los procesos para la construcción de una herramienta de calificación y priorización de nuevos requerimientos en software propietario que tiene solicitudes de varios clientes al mismo tiempo, con instrumentos de calificación que consideran todos los aspectos relacionados, proveerá técnicas de priorización actuales y emitirá informes personalizados según diferentes perspectivas de la empresa.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

Physical processes and materials in memristive devices: a theoretical study

Memristors are ideal devices able to switch among different resistive states and to retain the most recent one even if the input voltage is removed. With such a characteristic memristors would be able to mimic the brain functions or to behave as universal memory device. The existence of the memristor was theorized by Leon Chua in 1971 but only in 2008 a first prototype device based on the use of an oxide layer was realized, later addressed as a redox-based resistance (switching) random access memory (RRAM). Since its discovery, scientists have been working to understand the mechanism behind the device switching and to eliminate the intrinsic device failures and poor reproducibility, that differentiate the real RRAM from the ideal memristor and that prevent its application in circuitry. There exist two main memristor designs, the valence change memory cell (VCM) and the electrochemical metallization memory cell (ECM). These devices rely both on the switching between a high resistance state (HRS) and a low resistance state (LRS) through the application of a high voltage. Along the same two electric terminals that led to the switching, the resistance state is measured by means of a low voltage. Aim of thesis is to study the yet unclear RRAM physical processes and switching mechanisms in order to pave the way for overcoming existing device weak points. In particular, in the first part we focused on understanding the mechanism of the most basic realization of a VCM memristor, i.e. the thin-film based one. Afterwards, we explained some controversial experimental results on more advanced ECM memristors, namely nanowire-based devices, revising the applicability of currently established conventional theories and proposing an alternative operational mechanism. Finally, we presented the stability and the electrical properties of a new two-dimensional material, i.e. MoS2, which could be applied in the memristive field. In thin-film based VCM devices, it is argued that the resistance switching occurs due to the motion of crystallographic defects under the effect of an electric field. These defects locally dope the insulating oxide increasing its conductivity. Once a filament of stacked defects connects the two electrodes an abrupt change in current is measured externally. Nevertheless, not much it is known about the atomistic nature of the switching, even less about its link with measurable external quantities such as total current. In this thesis work, we proposed a mixed continuum and Kinetic Monte Carlo (KMC) simulation to take into account both atomic-level properties, like defect diffusivity, and macroscopic quantities like internal temperature and overall device current. Thanks to this combination of computational methods, temperature can dynamically change during the course of the simulation. Results show how the height of defect diffusion barrier influences the switching mechanism. When the barriers are low (≈0.4 eV) the defects move as soon as the voltage is applied and correspondingly the device switching is fast, however at room temperature the resistance state is volatile. By contrast, if the barriers are relatively high (≈1.1 eV) the oxide has first to heat up in order for the defects to have enough energy to overcome the barriers. Therefore the temperature, although not generally controlled or explicitly considered in the experiments, plays a fundamental role in the switching. Such a heating stage provides the required state retention for practical applications. ECM devices are asymmetric structures composed by an electrochemically active electrode like Cu, a thin film that functions as an electrolyte, either a transition metal oxide or a germanium chalcogenide, and an inactive electrode, such as Pt. The switching from HRS to LRS is thought to take place when, due to the high electric field established by the external bias, atoms of the electrochemically active contact dissolve into the insulating oxide or chalcogenide thin film to form a conductive filament with the opposite contact. Recently, nanomaterials, particularly micrometer-long nanowires, have been applied as an insulating layer between the metallic electrodes thanks to the improved endurance and LRS/HRS ratio that they ensure. Surprisingly, in these devices the LRS is achieved even if no continuous filament was detected. By means of Density Functional Theory simulations, we proposed a mechanism valid for Cu/ZnO-NW/Pt devices in which atoms belonging to the electrochemically active electrode (Cu), rather than aggregating into a filament, spread on the surface. Particularly when in form of adatom, the adsorbed Cu dope the NW surface creating a conductive channel. Copper adatoms are easily dragged by electric field once the diffusion barrier is overcome thanks to the polarizing effect of the surface. In absence of an external voltage clustering is hindered by the same barrier. As opposed to this, the atoms from the inactive electrode (Pt), although they are as mobile as the Cu atoms on the NW surface, are extremely hard to extract from the contact therefore they do not participate in the switching process. Finally, in collaboration with Prof. Jeffrey Grossman at Massachusetts Institute of Technology, we focused our attention on one of the materials that lately has been applied in numerous fields including resistive switching memories: MoS2. Due to its phase-dependent conductivity MoS2 could be applied to RRAM once the control on its phases is achieved. To this aim we proposed a new technique for the stabilization of the metastable metallic MoS2 T-phase over the stable semiconducting MoS2 H-phase by alloying with another metal dichalcogenide, SnS2, existing in the T-phase only. A combined Cluster Expansion and DFT approach was exploited to theoretically predict the phase diagram of MoxSn1-xS2 compounds. Our results show that the addition of impurities efficiently lowers the energetic cost of the MoS2 T-phase, and that alloying is an effective way to tune the TMD electronic properties. In a RRAM made with a MoxSn1-xS2 sheet the electric field may alter the local distribution of substitutional atoms so to induce a phase change only in a small portion of the material and alter the overall resistance state. Additionally, the reported intra-phase metal-semiconductor transition occurring for a slightly doped material could be useful for memristive applications

Does platinum play a role in the resistance switching of ZnO nanowire-based devices?

Platinum is a largely employed material as electrode in resistive switching devices. However, it is not known if it might play an active role in the switching of Pt/ZnO/Cu devices when ZnO nanowires are employed as active layer. Here, we study theoretically if platinum can lead to a variation of the total resistance in such devices by inspecting how platinum adatoms behave on a ZnO nanowire surface. We show that, even though Pt can travel on ZnO under the effect of an electric field and, in principle, it can form a conductive filament, the large energy required to extract Pt atoms from the contact makes, in practice, impossible for platinum to be involved in changing the device resistance state. Platinum is then better suited as counter-electrode in RRAM coupled with a more active metal like copper