A multilayer approach for price dynamics in financial markets

We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dy- namics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.Comment: 12 pages, 6 figure

ScaRR: Scalable Runtime Remote Attestation for Complex Systems

The introduction of remote attestation (RA) schemes has allowed academia and industry to enhance the security of their systems. The commercial products currently available enable only the validation of static properties, such as applications fingerprint, and do not handle runtime properties, such as control-flow correctness. This limitation pushed researchers towards the identification of new approaches, called runtime RA. However, those mainly work on embedded devices, which share very few common features with complex systems, such as virtual machines in a cloud. A naive deployment of runtime RA schemes for embedded devices on complex systems faces scalability problems, such as the representation of complex control-flows or slow verification phase. In this work, we present ScaRR: the first Scalable Runtime Remote attestation schema for complex systems. Thanks to its novel control-flow model, ScaRR enables the deployment of runtime RA on any application regardless of its complexity, by also achieving good performance. We implemented ScaRR and tested it on the benchmark suite SPEC CPU 2017. We show that ScaRR can validate on average 2M control-flow events per second, definitely outperforming existing solutions.Comment: 14 page

What a thousand children tell us about grammatical complexity and working memory: A cross-sectional analysis on the comprehension of clitics and passives in Italian

Published online: 28 November 2023Data from 996 Italian-speaking children were collected and analyzed to assess whether a movement-based notion of grammatical complexity is adequate to capture the developmental trend of clitics and passives in Italian. A second goal of the study was to address the relationship between working memory and syntactic development, exploring the hypothesis that higher digit span values predict better comprehension of complex matrix sentences. The results confirm the validity of a ranking of grammatical structures based on constituent movement, with both clitics and passives developing in parallel and later than canonical SVO sentences. Working memory also shows an effect on sentence comprehension in general, but standard measures (digit span forward/backward) do not show a selective advantage in handling complex constructions such as clitics and passives

Synthesis and Evaluation of Saccharide-Based Aliphatic and Aromatic Esters as Antimicrobial and Antibiofilm Agents

A small library of sugar-based (i.e., glucose, mannose and lactose) monoesters containing hydrophobic aliphatic or aromatic tails were synthesized and tested. The antimicrobial activity of the compounds against a target panel of Gram-positive, Gram-negative and fungi was assessed. Based on this preliminary screening, the antibiofilm activity of the most promising molecules was evaluated at different development times of selected food-borne pathogens (E. coli, L. monocytogenes, S. aureus, S. enteritidis). The antibiofilm activity during biofilm formation resulted in the following: mannose C10 > lactose biphenylacetate > glucose C10 > lactose C10. Among them, mannose C10 and lactose biphenylacetate showed an inhibition for E. coli 97% and 92%, respectively. At MICs values, no toxicity was observed on Caco-2 cell line for all the examined compounds. Overall, based on these results, all the sugar-based monoesters showed an interesting profile as safe antimicrobial agents. In particular, mannose C10 and lactose biphenylacetate are the most promising as possible biocompatible and safe preservatives for pharmaceutical and food applications

Exploring the Role of Interdisciplinarity in Physics: Success, Talent and Luck

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counter-intuitive effect indicating that the most talented authors are not necessarily the most successful ones.Comment: 21 pages, 19 figure

The Paradox of Talent: how Chance affects Success in Tennis Tournaments

Individual sports competitions provide a natural setting for examining the relative importance of talent and luck/chance in achieving success. The belief that success is primarily due to individual abilities and hard work rather than external factors is particularly strong in this context. In this study, we test this belief using tennis as a case study, due to its popularity and competition structure in direct-elimination tournaments. Our dataset covers the decade 2010-2019 of main events in the ATP circuit and consists of tourney results and annual rankings for professional male players. After a preliminary data analysis, we introduce an agent-based model able to accurately simulate the tennis players' dynamics along several seasons. We show that, once calibrated on the dataset, the model is able to reproduce the main stylized facts observed in real data, including the results of single tournaments and the development of players' careers in the ATP community. The strength of our approach lies in its simplicity: it requires only one free parameter a to determine the importance of talent in scoring every single point: a = 1, if only talent matters; a = 0, if the outcome of each point is entirely due to chance. We find the best agreement between real data and simulation results when talent weights substantially less than luck, i.e. when a is between 0.20 and 0.30. A further comparison between data and simulations, based on the analysis of the direct networks of all the matches, confirms the previous finding. A posteriori, we notice that this surprisingly important role of chance in tennis tournaments is not an exception. On the contrary, it can be explained by a more general paradoxical effect that characterizes highly competitive environments, particularly in individual sports. In other words, when the difference in talent between top players is minimal, chance becomes determinant.Comment: 19 pages,17 figure