854 research outputs found
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
On optimal three-impulse Earth–Moon transfers in a four-body model
Within the emerging age of lunar exploration, optimizing transfer trajectories is a fundamental measure toward achieving more economical and efficient lunar missions. This study addresses the possibility of reducing the fuel cost of two-impulse Earth–Moon transfers in a four-body model with the Earth, the Moon, and the Sun as primaries. Lawden’s primer vector theory is applied within this framework to derive a set of necessary conditions for a fuel-optimal trajectory. These conditions are used to identify which trajectories from an existing database could benefit from the insertion of an additional intermediate impulse. More than 10,000 three-impulse transfers are computed with a direct numerical optimization method. These solutions contribute to enriching the database of impulsive trajectories, useful to perform trade-off analyses. While the majority of trajectories exhibit only marginal improvements, a significant breakthrough emerges for transfers featuring an initial gravity assist at the Moon. Implementing a corrective maneuver after the lunar encounter yields substantial reductions in fuel costs
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
An international survey exploring the management of pilonidal disease
AIM: Pilonidal disease (PD) is a common debilitating condition frequently seen in surgical practice. Several available treatments carry different benefit/risk balances. The aim of this study was to snapshot the current management of PD across European countries.METHOD: Members affiliated to the European Society of Coloproctology were invited to join the survey. An invitation was extended to others via social media. The predictive power of respondents' and hospitals' demographics on the change of therapeutic approach was explored.RESULTS: Respondents (n = 452) were mostly men (77%), aged 26-60 years, practising in both academic and public hospitals and with fair distribution between colorectal (51%) and general (48%) surgeons. A total of 331 (73%) respondents recommended surgery at first presentation of the disease. Up to 80% of them recommended antibiotic therapy and 95% did not use any classification of PD. A primary closure technique was the preferred procedure (29%), followed by open technique (22%), flap creation (7%), sinusectomy (7%) and marsupialization (7%). Approximately 27% of subjects would choose the same surgical technique even after a failure. Almost half (46%) perform surgery as office based. A conservative approach was negatively associated with acutely presenting PD (p < 0.001). Respondents who were not considering tailored surgery based on patient presentation tended to change their approach in the case of a failed procedure.CONCLUSION: With the caveat of a heterogeneous number of respondents across countries, the results of our snapshot survey may inform the development of future guidelines.</p
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