L’educazione nella prima infanzia: un mosaico di successi, sfide e opportunità

Early childhood education and care have been the focus of various extensive trans-national studies over the past decade. The present article aims to describe the situation in Italy and to identify the strengths and weaknesses of the current educational system and policy in an international context.L’educazione e cura della prima infanzia è stata, negli ultimi anni, oggetto privilegiato di varie indagini internazionali. In questo contributo si vogliono delineare alcuni principi che descrivono la situazione in Italia, mettendone in luce i punti di forza e di debolezza in relazione al contesto internazionale

Imperfect quantum networks with tailored resource states

Entanglement-based quantum networks exhibit a unique flexibility in the choice of entangled resource states that are then locally manipulated by the nodes to fulfill any request in the network. Furthermore, this manipulation is not uniquely defined and thus can be optimized. We tailor the adaptation of the resource state or pre-established entanglement to achieve bipartite communication in an imperfect setting that includes time-dependent memory errors. In this same setting, we study how the flexibility of this approach can be used for the distribution of entanglement in a fully asymmetric network scenario. The considered entanglement topology is a custom one based on the minimization of the required measurements to retrieve a Bell pair. The optimization of the manipulation and the study of such a custom entanglement topology are performed using the noisy stabilizer formalism, a recently introduced method to fully track noise on graph states. We find that exploiting the flexibility of the entanglement topology, given a certain set of bipartite requests, is highly favorable in terms of the fidelity of the final state.Comment: 15 pages, 12 figure

La voce dell’immagine: Considerazioni teoriche ed esperienze pratiche nell’uso della fotografia come strumento analitico e pratico in contesti di ricerca e formazione

This contribution explores a practice of educational research, the use of visual data, as a strategy for researching and reflecting on one’s own ways of perception and analysis of educational experiences. The use of images, as in the practice of photovoice, combined with descriptive captions and group discussions is a valuable tool for developing a reflective and open gaze and a pedagogical stance of a responsible educator-researcher in documenting and analysing educational experiences. Within educational research, visual data provide access to a participatory and active dimension and, accompanied by photo captions and discussions, enable theory and practice to be held together and the relationship between context, subjects and readers to be addressed, recognising the self-educational and awareness-raising effect for those who collect and write the data.Questo contributo esplora una pratica della ricerca formativa, l’utilizzo dei dati visuali, come strategia di ricerca e di riflessione sulle proprie modalità di percezione e di lettura delle esperienze educative. L’utilizzo di immagini, come nella pratica del photovoice, combinato con didascalie descrittive e discussioni di gruppo è uno strumento prezioso per sviluppare uno sguardo riflessivo e aperto e una postura pedagogica di educatore-ricercatore responsabile nel documentare e analizzare le esperienze educative. All’interno della ricerca formativa i dati visuali danno accesso a una dimensione partecipativa e attiva e, accompagnati da didascalie e discussioni, permettono di tenere insieme teoria e pratica e di affrontare il rapporto tra contesto, soggetti e lettori riconoscendo l’effetto di autoformazione e di consapevolizzazione per chi raccoglie e scrive i dati

ReQuSim: Faithfully simulating near-term quantum repeaters

Quantum repeaters have long been established to be essential for distributing entanglement over long distances. Consequently, their experimental realization constitutes a core challenge of quantum communication. However, there are numerous open questions about implementation details for realistic, near-term experimental setups. In order to assess the performance of realistic repeater protocols, we here present ReQuSim, a comprehensive Monte-Carlo based simulation platform for quantum repeaters that faithfully includes loss and models a wide range of imperfections such as memories with time-dependent noise. Our platform allows us to perform an analysis for quantum repeater setups and strategies that go far beyond known analytic results: This refers to being able to both capture more realistic noise models and analyse more complex repeater strategies. We present a number of findings centered around the combination of strategies for improving performance, such as entanglement purification and the use of multiple repeater stations, and demonstrate that there exist complex relationships between them. We stress that numerical tools such as ours are essential to model complex quantum communication protocols aimed at contributing to the quantum internet.Comment: 13+4 pages, 10+4 figures, 0+2 tables; v2: updated presentation; v3: accepted version plus tiny changes, adds one more scenario and runtime informatio

Machine Learning for Long-Distance Quantum Communication

Machine learning can help us in solving problems in the context of big-data analysis and classification, as well as in playing complex games such as Go. But can it also be used to find novel protocols and algorithms for applications such as large-scale quantum communication? Here we show that machine learning can be used to identify central quantum protocols, including teleportation, entanglement purification, and the quantum repeater. These schemes are of importance in long-distance quantum communication, and their discovery has shaped the field of quantum information processing. However, the usefulness of learning agents goes beyond the mere reproduction of known protocols; the same approach allows one to find improved solutions to long-distance communication problems, in particular when dealing with asymmetric situations where the channel noise and segment distance are nonuniform. Our findings are based on the use of projective simulation, a model of a learning agent that combines reinforcement learning and decision making in a physically motivated framework. The learning agent is provided with a universal gate set, and the desired task is specified via a reward scheme. From a technical perspective, the learning agent has to deal with stochastic environments and reactions. We utilize an idea reminiscent of hierarchical skill acquisition, where solutions to subproblems are learned and reused in the overall scheme. This is of particular importance in the development of long-distance communication schemes, and opens the way to using machine learning in the design and implementation of quantum networks

Simulating quantum repeater strategies for multiple satellites

A global quantum repeater network involving satellite based links is likely to have advantages over fiber based networks in terms of long distance communication, since the photon losses in vacuum scale only polynomially with the distance compared to the exponential losses in optical fibers. To simulate the performance of such networks, we have introduced a scheme of large scale event based Monte Carlo simulation of quantum repeaters with multiple memories that can faithfully represent loss and imperfections in these memories. In this work, we identify the quantum key distribution rates achievable in various satellite and ground station geometries for feasible experimental parameters. The power and flexibility of the simulation toolbox allows us to explore various strategies and parameters, some of which only arise in these more complex, multi satellite repeater scenarios. As a primary result, we conclude that key rates in the kHz range are reasonably attainable for intercontinental quantum communication with three satellites, only one of which carries a quantum memor

The SZT2 Interactome Unravels New Functions of the KICSTOR Complex

Seizure threshold 2 (SZT2) is a component of the KICSTOR complex which, under catabolic conditions, functions as a negative regulator in the amino acid-sensing branch of mTORC1. Mutations in this gene cause a severe neurodevelopmental and epileptic encephalopathy whose main symptoms include epilepsy, intellectual disability, and macrocephaly. As SZT2 remains one of the least characterized regulators of mTORC1, in this work we performed a systematic interactome analysis under catabolic and anabolic conditions. Besides numerous mTORC1 and AMPK signaling components, we identified clusters of proteins related to autophagy, ciliogenesis regulation, neurogenesis, and neurodegenerative processes. Moreover, analysis of SZT2 ablated cells revealed increased mTORC1 signaling activation that could be reversed by Rapamycin or Torin treatments. Strikingly, SZT2 KO cells also exhibited higher levels of autophagic components, independent of the physiological conditions tested. These results are consistent with our interactome data, in which we detected an enriched pool of selective autophagy receptors/regulators. Moreover, preliminary analyses indicated that SZT2 alters ciliogenesis. Overall, the data presented form the basis to comprehensively investigate the physiological functions of SZT2 that could explain major molecular events in the pathophysiology of developmental and epileptic encephalopathy in patients with SZT2 mutations

Maximising Synergy among Tropical Plant Systematists, Ecologists, and Evolutionary Biologists

Closer collaboration among ecologists, systematists, and evolutionary biologists working in tropical forests, centred on studies within long-term permanent plots, would be highly beneficial for their respective fields. With a key unifying theme of the importance of vouchered collection and precise identification of species, especially rare ones, we identify four priority areas where improving links between these communities could achieve significant progress in biodiversity and conservation science: (i) increasing the pace of species discovery; (ii) documenting species turnover across space and time; (iii) improving models of ecosystem change; and (iv) understanding the evolutionary assembly of communities and biomes