1,354,505 research outputs found
Powering up Fourier valuation to any dimension
No full textEven the powerful need a hand to achieve their full potential. Laura Ballotta looks at what happens when Fourier meets Monte Carlo integration
Computational development of models and tools for the kinetic study of astrochemical gas-phase reactions
No full textThis PhD thesis focuses on the application and development of computational tools and methodologies for the modeling of the kinetics of gas-phase reactions of astrophysical interest in the interstellar medium (ISM). The complexity related to the investigation of chemical reactivity in space is mostly due to the extreme physical conditions of temperature, pressure and exposure to high-energy radiation, which in turn also lead to the formation of exotic species, like radicals and ions. Nevertheless, there is still much to be understood about the formation of molecules, the major issue being the lack of sufficient laboratory (experimental and computational) studies. A more detailed and accurate study of all the chemical processes occurring in the ISM will allow us to obtain the data necessary to simulate the chemical evolution of an interstellar cloud over time using kinetic models including thousands of reactions that involve hundreds of species. The collection of the kinetic parameters required for the relevant reactions has led to the growth of different astrochemical databases, such as KIDA and UMIST. However, the data gathered in these catalogues are incomplete, and rely extensively on crude estimations and extrapolations. These rates are of paramount importance to get a better comprehension of the relative abundances of the chemical compounds extrapolated by the astronomers from the spectral data recorded through the radio telescopes and the in-orbit devices, like the satellites. Accurate state-of-the-art computational approaches play a fundamental role in analyzing feasible reaction mechanisms and in accurately predicting the associated kinetics. Such approaches usually rely on chemical intuition where a by-hand search of the most likely pathways is performed. Unfortunately, thisprocedure can lead to overlook significant mechanisms, especially when large molecular systems are investigated. Increasing the size of a molecule can also increase the number of its possible conformers which can show a different chemical reactivity with respect to the same chemical partner. This brings to get very complex chemical reaction networks in which hundreds of chemical species are involved and thousands of chemical reactions can occur.During the last decades, a lot of effort has been done to develop computational techniques able to perform extensive and thorough investigations of complex reaction mechanisms. Such approaches rely on automated computational protocols which drastically decrease the risk of making blunders during the search for significant reaction pathways.Furthermore, the accurate characterization of the potential energy surfaces (PESs) critical points, like reactants, intermediates, transition states and products involved in the reaction mechanism, is crucial in order to carry out a reliable kinetic investigation. The kinetic analysis of an erroneous potential energy surface, would lead to gross errors in the estimation of the rate constants of the chemical species involved in the reaction.In order to avoid such errors, the combination of high-level electronic structure calculations via composite scheme can be helpful to get a more precise estimation of the energy barriers involved in the reaction mechanism. It has been proven that "cheap"[1] composite schemes can achieve subchemical accuracy without any empirical parameters and with convenient computation times, making them perfect for the purpose of this thesis.In recent decades, many efforts have been made to develop theoretical and computational methodologies to perform accurate numerical simulations of the kinetics of such complex reaction mechanisms in a wide range of thermodynamic conditions that mimic extreme reaction environmentsas for combustion systems, the atmosphere and the ISM. Such methodologies are based on the ab initio-transition-state-theory-based master equation approach, which allows the determination of rate coefficients and branching ratios of chemical species involved in complex chemical reactions. This methodology allows to make accurate predictions of the relative abundances of the reaction products for complex reactions even under conditions of temperature and pressure not experimentally accessible, such as those that characterize the ISM. Based on these premises, this dissertation has been focused on the application of a computational protocol for the ab initio-based computational modeling and kinetic investigation of gas-phase reactions which can occur in the ISM.This protocol is based on the application of validated methodologies for the automated discovery of complex reaction mechanisms by means of the AutoMeKin[2] program, the accurate calculation of the energetic of the potential energy surfaces (PESs) through the junChS and junChS-F12a "cheap" composite schemes and the kinetic investigation using the StarRate computer program specifically designed to study gas-phase reactions of astrochemical interest in conjunction with the MESS program. Furthermore, this dissertation has been also focused on the development and implementation of StarRate, a computer program for the accurate calculation of kinetics through a chemical master equation approach of multi-step chemical reactions. StarRate is an object-based program written in the so-called F language. It is structured in three main modules, namely molecules, steps and reactions, which extract the properties needed to calculate the kinetics for the single-step reactions partecipating in the overall reaction. Another module, in_out, handles program’s input and output operations. The main program,starrate, controls the sequences of the calling of the procedures contained in each of the three main modules.Through these modular structure, StarRate[3] can compute canonical and microcanonical rate coefficients taking into account for the tunneling effect and the energy-dependent and time-dependent evolution of the species concentrations involved in the reaction mechanism. Such protocol has been applied to investigate the formation reaction mechanisms of some complex interstellar polyatomic molecules, named interstellar complex organic molecules (iCOMs). More specifically, the formation of prebiotic iCOMs in space has raised considerable interest in the scientific community, because they are considered as precursors of more complex biological systems involved in the origin of life in the Universe. Debate on the origins of these biomolecular building blocks has been further stimulated by the discovery of nucleobases and amino acids in meteorites and other extraterrestrial sources. However, few insights on the chemistry which brings to the formation of such compounds is known. References: [1] Jacopo Lupi,Silvia Alessandrini,Cristina Puzzarini,and Vincenzo Barone.junchs and junchs-F12 models:Parameter-free efficient yet accurate compositeschemes for energies and structures of noncovalent complexes. Journal of Chem-ical Theory and Computation, 17(11):6974–6992, 2021. PMID: 34677974.[2] Emilio Martínez-Núñez, George L. Barnes, David R. Glowacki, Sabine Kopec,Daniel Peláez, Aurelio Rodríguez, Roberto Rodríguez-Fernández, Robin J. Shan-non, James J. P. Stewart, Pablo G. Tahoces, and Saulo A. Vazquez.Au-tomekin2021: An open-source program for automated reaction discovery. Journalof Computational Chemistry, 42(28):2036–2048, 2021.[3] Surajit Nandi, Bernardo Ballotta, Sergio Rampino, and Vincenzo Barone.Ageneral user-friendly tool for kinetic calculations of multi-step reactions withinthe virtual multifrequency spectrometer project. Applied Sciences, 10(5), 2020
A Gentle Introduction to Value at Risk
No full textThis paper is an introduction to the measurement of market risk in financial markets, with examples drawn mainly from commodity markets. In particular, we present the concept of VaR, its limits, the problems related to its estimation and backtesting. This is done at single asset and at portfolio level. Issues related to estimation error, measurement of portfolio risk contribution and how to cope with derivative positions are also considered. Other important issues like liquidity, operational and credit risk will not be dealt here. For a Gentle introduction to the measurement of counterparty credit risk see the companion paper by Ballotta, Fusai and Marena always available on the SSRN web site
Immediate and late clinical outcomes of carotid artery stenting in patients with symptomatic and asymptomatic carotid artery stenosis: a 5-year prospective analysis.
No full textMultivariate Lévy Models by Linear Combination: Estimation
No full textIn this paper we propose a simple and effective two-step procedure to estimate the multivariate Lévy model introduced by Ballotta and Bonfiglioli (2012). We assess our estimation approach via simulations, comparing the results with those obtained through a standard but more computationally intensive one-step maximum likelihood estimation. The proposed method is then applied to the computation of the intra-horizon Value at Risk for a portfolio of assets following the model under consideration
Counterparty credit risk in a multivariate structural model with jumps
No full textWe present a multivariate version of a structural default model with jumps and use it in order to quantify the bilateral credit value adjustment and the bilateral debt value adjustment for equity contracts, such as forwards, in a Merton-type default setting. In particular, we explore the impact of changing correlation between names on these adjustments and study the effect of wrong-way and right-way risk
Eliciting Implicit Awareness in Alzheimer’s Disease and Mild Cognitive Impairment: A Task-Based Functional MRI Study
No full textBackground: Recent models of anosognosia in dementia have suggested the existence of an implicit component of self-awareness about one’s cognitive impairment that may remain preserved and continue to regulate behavioral, affective, and cognitive responses even in people who do not show an explicit awareness of their difficulties. Behavioral studies have used different strategies to demonstrate implicit awareness in patients with anosognosia, but no neuroimaging studies have yet investigated its neural bases. Methods: Patients with amnestic mild cognitive impairment and dementia due to Alzheimer’s disease underwent functional magnetic resonance imaging (fMRI) during the execution of a color-naming task in which they were presented with neutral, negative, and dementia-related words (Dementia-Related Emotional Stroop). Results: Twenty-one patients were recruited: 12 were classified as aware and 9 as unaware according to anosognosia scales (based on clinical judgment and patient-caregiver discrepancy). Behavioral results showed that aware patients took the longest time to process dementia-related words, although differences between word types were not significant, limiting interpretation of behavioral results. Imaging results showed that patients with preserved explicit awareness had a small positive differential activation of the posterior cingulate cortex (PCC) for the dementia-related words condition compared to the negative words, suggesting attribution of emotional valence to both conditions. PCC differential activation was instead negative in unaware patients, i.e., lower for dementia-related words relative to negative-words. In addition, the more negative the differential activation, the lower was the Stroop effect measuring implicit awareness. Conclusion: Posterior cingulate cortex preserved response to dementia-related stimuli may be a marker of preserved implicit self-awareness
On fundamental trade-offs and architecture design in Networked Control Systems
No full textIt can be legitimately said that Networked Control Systems represent one of the biggest
breakthroughs in engineering over the latest decades. Stemming from the intertwining
among control, computer engineering, and telecommunications, these powerful systems
received the legacy of classical communication and computer networks, but leveled it
up by virtue of autonomy of each involved unit. Nowadays, examples of Networked
Control Systems are smart power grids, smart homes and buildings, Industry 4.0 and
Industrial Internet of Things, and smart agriculture, to mention a few. Even more
futuristic applications, such as networks of autonomous vehicles or search-and-rescue
robotic teams, are predicted to be available on the market in a matter of time.
Despite the exponential growth of such systems both in industrial applications and in
research, one main reason why the current development is somewhat refrained on several aspects
is that designing a Networked Control System is challenging in nature. In fact, not
only blending different engineering fields raises novel issues, but also the interdependence
of individual subsystems makes it hard to design control and, in general, decision-making
procedures at local level, whereas design at global level is not only undesired but sometimes
even unfeasible. To mention just one example of design complexity, while it is well known
that the optimal Linear Quadratic controller for a single system can be found by solving
a (relatively simple) algebraic matrix equation, it is also known that solving the same
problem for a distributed controller is NP hard.
Because engineered systems must work in real life, the lack of strong theoretical
results is typically replaced with ad-hoc and heuristic methods, that try to take the
best of both worlds of human experience and available mathematical tools. While such
solutions have already yielded impressive applications, relying on intuition might not
always be the best strategy, and theoretical advancement is needed to unleash the full
potential of Networked Control Systems. For example, recently introduced Multi-Agent
Reinforcement Learning, even though it has proved powerful in some scenarios, still
leaves open room for improvement before it can be safely deployed in the real world.
This thesis investigates, and possibly questions, the role that conventional wisdom
plays in design of Networked Control Systems. Specifically, the aim is to explore
situations where common design beliefs might not match the
real nature of the system to be designed, possibly causing loss in performance. Three
conventions will be examined: more sensors improve estimation; more communication
links increase control performance; more collaboration enhances cooperative tasks. While
such conventions seem indeed reasonable, results exposed in this thesis will show that
it is not always so: in fact, more sensors may hinder estimation under computational delays;
more communication links may degrade control performance under communication delays;
more collaboration may be dangerous under misbehaving agents.
Even though most results are limited to analysis, and practical design indications
are still preliminary, the hope with this piece of research is to offer high-level guidelines
and insights that can improve classical conventions and possibly pave the way to novel
research directions, to be exploited in the design of high-performing Networked Control
Systems.It can be legitimately said that Networked Control Systems represent one of the biggest
breakthroughs in engineering over the latest decades. Stemming from the intertwining
among control, computer engineering, and telecommunications, these powerful systems
received the legacy of classical communication and computer networks, but leveled it
up by virtue of autonomy of each involved unit. Nowadays, examples of Networked
Control Systems are smart power grids, smart homes and buildings, Industry 4.0 and
Industrial Internet of Things, and smart agriculture, to mention a few. Even more
futuristic applications, such as networks of autonomous vehicles or search-and-rescue
robotic teams, are predicted to be available on the market in a matter of time.
Despite the exponential growth of such systems both in industrial applications and in
research, one main reason why the current development is somewhat refrained on several aspects
is that designing a Networked Control System is challenging in nature. In fact, not
only blending different engineering fields raises novel issues, but also the interdependence
of individual subsystems makes it hard to design control and, in general, decision-making
procedures at local level, whereas design at global level is not only undesired but sometimes
even unfeasible. To mention just one example of design complexity, while it is well known
that the optimal Linear Quadratic controller for a single system can be found by solving
a (relatively simple) algebraic matrix equation, it is also known that solving the same
problem for a distributed controller is NP hard.
Because engineered systems must work in real life, the lack of strong theoretical
results is typically replaced with ad-hoc and heuristic methods, that try to take the
best of both worlds of human experience and available mathematical tools. While such
solutions have already yielded impressive applications, relying on intuition might not
always be the best strategy, and theoretical advancement is needed to unleash the full
potential of Networked Control Systems. For example, recently introduced Multi-Agent
Reinforcement Learning, even though it has proved powerful in some scenarios, still
leaves open room for improvement before it can be safely deployed in the real world.
This thesis investigates, and possibly questions, the role that conventional wisdom
plays in design of Networked Control Systems. Specifically, the aim is to explore
situations where common design beliefs might not match the
real nature of the system to be designed, possibly causing loss in performance. Three
conventions will be examined: more sensors improve estimation; more communication
links increase control performance; more collaboration enhances cooperative tasks. While
such conventions seem indeed reasonable, results exposed in this thesis will show that
it is not always so: in fact, more sensors may hinder estimation under computational delays;
more communication links may degrade control performance under communication delays;
more collaboration may be dangerous under misbehaving agents.
Even though most results are limited to analysis, and practical design indications
are still preliminary, the hope with this piece of research is to offer high-level guidelines
and insights that can improve classical conventions and possibly pave the way to novel
research directions, to be exploited in the design of high-performing Networked Control
Systems
Prevention of enteric erosion by vascular prostheses.
No full textAortoenteric fistula is an uncommon but disastrous complication of aortic reconstruction with a prosthetic graft. Prevention ofenteric erosion when using a vascular prosthesis must be a foremost consideration. For these occasions, greater omentum may be used to cover the graft. However, when use of the greater omentum is not possible, the interposition ofa prosthetic patch is a means of preventing duodenal erosion. We review the usual procedures for reperitonealization and report on an original method of using a prosthetic patch to prevent erosion
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