Metal–metal oxide nanostructure supported on graphene oxide as a multifunctional electro-catalyst for simultaneous detection of hydrazine and hydroxylamine

A ruthenium/iridium/iridium oxide nanohybrid supported on graphene oxide (RuIrOx_GO) was prepared via a new protocol. The activity of the nanohybrid towards the simultaneous detection of hydrazine (HY) and hydroxylamine (HA) was evaluated in phosphate-buffered saline solution (pH 7.0). Differential pulse voltammetry was used for the measurements, with a pulse amplitude of 50 mV and a scan rate of 0.04 V s−1. Using the modified electrode, the oxidation peak potentials for HY and HA can be easily distinguished, with a large peak separation of 0.36 V. Very low LOD values of 2.1 μM and 1.6 μM were found for HY and HA, respectively. The selectivity of the electrode and its stability were also studied The tolerance limits in the presence of different interfering compounds were evaluated. After five weeks, a deviation from the expected results of ~2% was observed for both HA and HY determinations. Keywords: Ir and Ru active phases, New synthesis protocol, Hydrazine, Hydroxylamine, Low detection limi

Active and stable graphene supporting trimetallic alloy-based electrocatalyst for hydrogen evolution by seawater splitting

The hydrogen evolution reaction (HER), adopting seawater as an electrolyte solution, is a promising and more sustainable alternative for the production of hydrogen, yet requiring more economic, highly efficient and stable electrocatalysts than the current ones. Herein, the synthesis of a Ni, Ru, Ir-based and graphene-supported nano-structured catalyst through an easily scalable, cost-effective, surfactant-free approach has been proposed. XRD, SEM, TEM images and EDX maps showed the formation of trimetallic NiRuIr alloy nanoparticles (average diameter: 8 nm) supported on a few-layer graphene. After characterization, the HER stability and activity of the sample were tested in a 0.5 M H2SO4, in a KCl neutral solution as well as in real seawater. In the acidic electrolyte environment a 0.06 V overpotential was maintained even after 11,000 cycles and the Tafel slope recorded was very low (28 mV/dec). In the neutral solution a very low overpotential (0.10 V) and a low Tafel slope (72 mV/dec) were also obtained. Furthermore, in real seawater the sample exhibits a Tafel slope of 48 mV/dec, maintains a low overpotential of 0.08 V for 250 cycles and a constant current density for 200 h of test without significant losses and with almost a 100% hydrogen production efficiency. The results obtained proved the remarkable HER performance of the synthesized electrocatalyst, especially in real seawater in virtue of synergistic alloying effects and the presence of the graphene support. Keywords: Trimetallic alloy, NiRuIr alloy, Seawater, Hydrogen evolution reaction, High stability, High H2 productio

Place cognition and active perception: a study with evolved robots

A study of place cognition and 'place units' in robots produced via artificial evolution is described. Previous studies have investigated the possible role of place cells as building blocks for 'cognitive maps' representing place, distance and direction. Studies also show, however, that when animals are restrained, the spatial selectivity of place cells is partially or completely lost. This suggests that the role of place cells in spatial cognition depends not only on the place cells themselves, but also on representations of the animal's physical interactions with its environment. This hypothesis is tested in a population of evolved robots. The results suggest that successful place cognition requires not only the ability to process spatial information, but also the ability to select the environmental stimuli to which the agent is exposed. If this is so, theories of active perception can make a useful contribution to explaining the role of place cells in spatial cognition

Theoretical Perspectives of Hands-On Educational Practices — From a Review of Psychological Theories to Block Magic and INF@NZIA DIGI.Tales 3.6 Projects

In this chapter, the main theories related to cognitive development are discussed, starting from psychological discussion up to theories application to training, pedagogical and formation sciences issues

Monitoring kidney optical properties during cold storage preservation with spatial frequency domain imaging.

Transplantation of kidneys results in delayed graft function in as many as 40% of cases. During the organ transplantation process, donor kidneys undergo a period of cold ischemic time (CIT), where the organ is preserved with a cold storage solution to maintain tissue viability. Some complications observed after grafting may be due to damage sustained to the kidney during CIT. However, the effects due to this damage are not apparent until well after transplant surgery has concluded. To this end, we have used spatial frequency domain imaging (SFDI) to measure spatially resolved optical properties of porcine kidneys over the course of 80-h CIT. During this time, we observed an increase in both reduced scattering (μs&') and absorption (μa) coefficients. The measured scattering b parameter increased until 24 h of CIT, then returned toward baseline during the remaining duration of the imaging sequence. These results show that the optical properties of kidney tissue change with increasing CIT and suggest that continued investigation into the application of SFDI to kidneys under CIT may lead to the development of a noninvasive method for assessing graft viability

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Educational Robotics to Foster and Assess Social Relations in Students' Groups

Robotics has gained, in recent years, a significant role in educational processes that take place in formal, non-formal, and informal contexts, mainly in the subjects related to STEM (science, technology, engineering, and mathematics). Indeed, educational robotics (ER) can be fruitfully applied also to soft skills, as it allows promoting social links between students, if it is proposed as a group activity. Working in a group to solve a problem or to accomplish a task in the robotics field allows fostering new relations and overcoming the constraints of the established links associated to the school context. Together with this aspect, ER offers an environment where it is possible to assess group dynamics by means of sociometric tools. In this paper, we will describe an example of how ER can be used to foster and assess social relations in students' group. In particular, we report a study that compares: (1) a laboratory with robots, (2) a laboratory with Scratch for coding, and (3) a control group. This study involved Italian students attending middle school. As the focus of this experiment was to study relations in students' group, we used the sociometric tools proposed by Moreno. Results show that involving students in a robotics lab can effectively foster relations between students and, jointly with sociometric tools, can be employed to portrait group dynamics in a synthetic and manageable way

A computational model of the evolution of antipredator behavior in situations with temporal variation of danger using simulated robots

The threat-sensitive predator avoidance hypothesis states that preys are able to assess the level of danger of the environment by using direct and in-direct predator cues. The existence of a neural system which determines this ability has been studied in many animal species like minnows, mosquitoes and wood frogs. What is still under debate is the role of evolution and learning for the emergence of this assessment system. We propose a bio-inspired computing model of how risk management can arise as a result of both factors and prove its impact on fitness in simulated robotic agents equipped with recurrent neural networks and evolved with genetic algorithm. The agents are trained and tested in environments with different level of danger and their performances are ana-lyzed and compared

Inf@nzia Digi.Tales 3.6: un’esperienza di introduzione di strumenti innovativi per l’apprendimento nella fascia di età 3-6 anni

Inf@nzia Digi.Tales 3.6 è un progetto che ha avuto l’obiettivo di sviluppare metodologie e tecnologie di apprendimento innovative a supporto delle attività educative curriculari nella scuola dell’infanzia e nel primo anno della scuola primaria, come l’esplorazione spontanea o guidata, che sfrutta il ruolo centrale del tatto, della manipolazione e di tutti e cinque i sensi. Il progetto ha affrontato l’apprendimento al di fuori del contesto scolastico: ha stabilito un continuum scuola-famiglia-città, valorizzando il contesto socioculturale e territoriale; ha inoltre coinvolto amministrazioni scolastiche, docenti e famiglie, sviluppando metodologie partecipative, per accrescere il senso di corresponsabilità educativa, e promuovendo azioni per migliorare la qualità dei servizi amministrativi