On the Formal Verification of Diffusion Phenomena in Open Dynamic Agent Networks

International audienceThe paper is a contribution at the interface of social network theory and multi-agent systems. As realistic models of multi-agent systems, we assume agent networks to be open, that is, agents may join or leave the network at run-time, and dynamic, that is, the network structure may change as a result of agents actions. We provide a formal model of open dynamic agent networks (ODAN) in terms of interpreted systems, and define the problem of model checking properties of diffusion phenomena, such as the spread of information or diseases, expressed in a first-order version of computation-tree logic. We establish the decidability of the model checking problem by showing that, under specific conditions, the verification of infinite-state ODAN can be reduced to model checking finite bisimulations

Finite Abstractions for the Verification of Epistemic Properties in Open Multi-Agent Systems

We develop a methodology to model and verify open multi-agent systems (OMAS), where agents may join in or leave at run time. Further, we specify properties of interest on OMAS in a variant of first-order temporal-epistemic logic, whose characteris-ing features include epistemic modalities indexed to individual terms, interpreted on agents appear-ing at a given state. This formalism notably allows to express group knowledge dynamically. We study the verification problem of these systems and show that, under specific conditions, finite bisimilar ab-stractions can be obtained

Essays on the Italian electricity market

The thesis is a collection of three empirical essays focussing on the Italian electricity market. The first chapter, titled “Assessing market power in the Italian electricity market: a synthetic supply approach”, is a joint work with Prof. Luigi Grossi and Prof. Michael. G. Pollitt and was published among the Energy Policy Research Group Working Papers (no. 1930). This chapter investigates the bidding behaviour of the leading firms in the Italian electricity market, in particular on the Italian day-ahead market. The methodology adopted is synthetic supply, proposed by Ciarreta et al (2010), which consists in a two-step procedure, i.e. 1) power plants association and 2) hourly bidding schedule “translation”. Thanks to synthetic supply it is possible to create hourly counterfactual supply curves and see if there are differences between actual and synthetic equilibria. In other words, the idea is to investigate the difference in mark-up between the bidding schedules of power plants with very similar features. For this reason, power plants were associated with very strict criteria: technology, energy efficiency and many others. Furthermore, an algorithm in R was developed to compute hourly equilibria in the day-ahead market. This way, it is possible to assess if there are any differences between the bidding behaviour of the leading operators and the bidding behaviour of smaller generators. The findings suggest that during the years under examination (2015-2018), the market underwent higher prices and a non-negligible consumer surplus loss, especially during the months when above average heating and cooling were required. The second chapter, titled “Detecting strategic capacity withholding through a synthetic supply approach - Cui Prodest?”, puts forward a new methodology in the field of market monitoring. The methodology of synthetic supply and the R code are employed. However, the way synthetic supply is used in this chapter is completely new. A four-step procedure is proposed to investigate strategic capacity withholding, i.e. 1) hourly supply curves are created and extra capacity is artificially added to the supply schedule, 2) synthetic and actual prices are compared and anomalous price spikes detected, 3) synthetic and actual revenues are compared, to see if any market operator could have obtained more revenues from a scenario where some capacity was withheld, 4) the SSCW index is proposed to better interpret the results. The chapter carries out an empirical analysis of the Italian day-ahead market in 2018. This approach is a significant contribution to the literature because it enables the analysis of manipulative behaviour with a different perspective compared to the methodology currently available. The third chapter, titled “Covid-19 and the Italian electricity market: impacts, developments and implications”, investigates the effects of the restrictive measures employed by the Italian Government in response to Covid-19 on the Italian electricity market. This chapter presents a data description of the main market variables of the electricity market and uses an econometric model to estimate the effects of geographical and production lockdowns on the zonal quantities purchased and on the PUN (nationwide unit price). Data suggests that both quantity purchased, and prices were affected by the lockdowns, especially in the bidding areas of Northern Italy. The bidding zones of Southern Italy seem to be considerably less affected by restrictive measures. This is also confirmed by the econometric model. In addition, fall in demand led to a smaller quantity purchased, compared to the corresponding weeks in previous years, leading to substantial changes in the mix of energy sources. This chapter proposes a complete description of the evolution of the electricity market during the pandemic and provides useful policy recommendations on how financial resources should be allocated to relieve the Italian economy

Pathogenesis of the obstetric antiphospholipid syndrome: the key role of beta 2 glycoprotein I

Antiphospholipid syndrome (APS) is defined by recurrent pregnancy morbidity and/or vascular thrombosis associated with the persistent presence of antibodies against anionic phospholipid-binding proteins. Beta 2 glycoprotein I (β2GPI) and prothrombin (PT) are the major antigens for antiphospholipid antibodies (aPL) detectable by functional coagulation [lupus anticoagulant (LA)] or solid-phase assays [anti-β2GPI-dependent cardiolipin (aCL) and anti-β2GPI]. β2GPI-dependent aPL are responsible for the positivity of the three classification laboratory criteria. While medium/high titers of antibodies against β2GPI are risk factors for both the vascular and the obstetric manifestations of APS, persistent low titers are also associated with pregnancy complications. There is evidence from animal models of aPL-dependent fetal loss and from in vitro systems that β2GPI-dependent aPL can be pathogenic. β2GPI is physiologically found in large quantities at the placental level being available for the specific antibodies circulating in the maternal blood. Once bound to the protein, the antibodies trigger a local inflammation via the activation of the complement cascade and affect trophoblast and decidual function. The final result is represented by defective placentation, while thrombotic events are apparently less important. β2GPI is a pleiotropic molecule with scavenging properties towards several molecules including apoptotic material and displays anti-oxidant activity. These functions may explain the β2GPI placental localization in an area of intensive tissue remodeling and low oxygen tension. Since β2GPI interacts also with the complement and the coagulation cascade, its binding with specific antibodies may affect the physiology of placentation in several ways

Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning

Exploiting the properties of quantum information to the benefit of machine learning models is perhaps the most active field of research in quantum computation. This interest has supported the development of a multitude of software frameworks (e.g. Qiskit, Pennylane, Braket) to implement, simulate, and execute quantum algorithms. Most of them allow us to define quantum circuits, run basic quantum algorithms, and access low-level primitives depending on the hardware such software is supposed to run. For most experiments, these frameworks have to be manually integrated within a larger machine learning software pipeline. The researcher is in charge of knowing different software packages, integrating them through the development of long code scripts, analyzing the results, and generating the plots. Long code often leads to erroneous applications, due to the average number of bugs growing proportional with respect to the program length. Moreover, other researchers will struggle to understand and reproduce the experiment, due to the need to be familiar with all the different software frameworks involved in the code script. We propose QuASK, an open-source quantum machine learning framework written in Python that aids the researcher in performing their experiments, with particular attention to quantum kernel techniques. QuASK can be used as a command-line tool to download datasets, pre-process them, quantum machine learning routines, analyze and visualize the results. QuASK implements most state-of-the-art algorithms to analyze the data through quantum kernels, with the possibility to use projected kernels, (gradient-descent) trainable quantum kernels, and structure-optimized quantum kernels. Our framework can also be used as a library and integrated into pre-existing software, maximizing code reuse.Comment: Close to the published versio

Is Cyprideis agrigentina Decima a good palaeosalinometer 1 for the Messinian Salinity Crisis? 2 Morphometrical and geochemical analyses from the Eraclea Minoa section (Sicily)

The living euryhaline species Cyprideis torosa (Jones) undergoes morphometric variations in size, noding and sieve-pore shape linked to the environmental salinity. In particular it is known that salinity values around 8-9 psu represent the osmoregulation threshold and also the turning point between smaller and greater valve dimensions and prevailingly noded against un-noded valves. The variation of the percentage of round-, elongate- and irregular-shaped sieve-pores on the valves has shown an empiric logarithmic correlation with the water salinity from 0 to 100 psu. Due to this ecologically cued polymorphism, C. torosa represents 28 an invaluable palaeosalinometer for the Quaternary brackish basins. In this paper we attempt to verify whether the ecophenotypical behaviour of the post-evaporitic Messinian species Cyprideis agrigentina Decima was comparable with that of C. torosa. To reach this goal, three morphometric characters have been analysed: 1) size variability; 2) noding and ornamentation; 3) variability of the percentage of the sieve-pore shapes. The palaeoenvironmental interpretation was made using synecological and geochemical approaches [stable isotopes, trace elements, Sr-isotopes and natural radioactivity (NRD)]. For this study, the 250 m-thick Messinian Lago-Mare succession of Eraclea Minoa (Agrigento, Sicily) was chosen for the presence of monotypic assemblages made only by C. agrigentina for around 70 m of thickness. The results of the morphometric analyses showed that: 1) size variations are not related to the salinity changes recognized both from synecological and geochemical analyses; 2) no noded specimens have been recovered along the section; 3) the salinities calculated on the basis of the percentage of the sieve-pore shape are not correlated with the salinities inferred from the synecological and geochemical analyses. Thus in this paper we conclude that C. agrigentina cannot be considered a palaeosalinometer for the Messinian Salinity Crisis. There is a correlation of the 13 C and NRD data with the percentages of sieve-pore shapes, linking them to the oxygen availability at the bottom of the basin

Survival benefit with adjuvant chemotherapy in stage III microsatellite-high/deficient mismatch repair colon cancer: a systematic review and meta-analysis

Clinical observations have demonstrated that microsatellite instability-high (MSI-H) and/or deficient MMR (dMMR) status are associated with favorable prognosis and no benefit from 5-Fluorouracil (5-FU)-based adjuvant chemotherapy in patients with resected stage II colorectal cancer (CRC). This study represents a systematic review and meta-analysis exploring the predictive role of MSI-H status in stage III CRC undergoing or not adjuvant chemotherapy. Published articles that evaluated the role of adjuvant chemotherapy in resected stage III CRC from inception to September 2020 were identified by searching the PubMed, EMBASE, and Cochrane Library databases. The random-effects model was conducted to estimate the pooled effect size of OS and DFS. The primary outcome of interest was OS. 21,590 patients with MSI-H/dMMR stage III CRC, from n = 17 retrospective studies, were analyzed. Overall, OS was improved with any adjuvant chemotherapy vs. any control arm (single-agent 5-FU or surgery alone): HR 0.42, 95% CI 0.26-0.66; P < 0.01. Conversely, DFS was not significantly improved (HR 0.7, 95% CI 0.45-1.09; P = 0.11). In patients with stage III MSI-H/dMMR CRC, adjuvant chemotherapy is associated with a significant OS improvement. Thus, MSI-H/dMMR status does represent a predictive factor for postoperative chemotherapy benefit in stage III CRC beyond its prognostic role

The Polyamine Pathway as a Potential Target for Vascular Diseases: Focus on Restenosis

Polyamines are organic polycations expressed by all living organisms, which are known to play an essential role in cell proliferation and differentiation. Recent studies revealed their involvement also in cell contractility and migration and in programmed cell death. These processes are known to contribute to restenosis, a pathophysiological process occurring in 10-20% of patients submitted to revascularization procedures. The advent of bare metal stents and of drug-eluting stents has significantly reduced but not eliminated the incidence of restenosis, which thus remains a clinically relevant problem. Despite the potential role of the polyamine pathway as a therapeutic target due to its involvement in proliferation, apoptosis and migration of vascular cells, experimental inhibition of polyamine synthesis and/or uptake has been poorly investigated in animal models of vascular disease. Here we review the current knowledge about molecular mechanisms related to polyamine functions, with particular reference to the role played by polyamines in vascular cell pathophysiology, together with experimental evidence obtained so far in animal models of (re) stenosis. We also evaluate the advantages of different routes of administration of polyamine synthesis/transport inhibitors and polyamine analogue molecules. Increasing knowledge about the molecular mechanisms and functions of polyamines is expected to shed new light on their potential role as a therapeutic target for restenosis reduction