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Showing papers by "Roma Tre University published in 2022"


Journal ArticleDOI
TL;DR: In this paper, the authors present a dashboard that can be used at various spatial levels to guide the agri-food sector toward a more sustainable development model in line with the principles of the circular economy (CE).
Abstract: The agri-food sector is one of the key sectors where the action is needed to ensure the transition to a more sustainable development model in line with the principles of the circular economy (CE). The use of indicators to monitor progress and areas for action is a key element in the shift of companies, regions, and countries toward a circular model. This study aims to create a dashboard that can be used at various spatial levels to guide the agri-food sector toward a CE and sustainable development. Starting with the relevant literature, we identified 102 indicators classified according to three areas of sustainability (environmental, economic and social) and spatial dimensions (macro‑meso-micro) within 8 scopes. The dashboard provides a toolbox for directing decision-making processes and strategies through the targeted use of indicators with respect to the context in which the CE is applied. In addition, the dashboard allows us to highlight missing aspects related to (1) new indicators not covered by the tool; (2) new scopes not yet explored in the literature; and (3) the need to adopt cross-sectional indicators. For this last aspect, the analysis revealed only 17 such indicators. A future step is to define the most suitable configurations among the indicators in which CE is generated, starting from the test of the indicators at the micro level to validate their applicability and consider the impacts they may have at the macro or meso levels.

36 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigated the role of vegetation as a plastic trap and the possible detrimental effects of plastic on the plant health status in 8 central Italian rivers. And they found that the highest plastic density was found on the shrubby type suggesting that a tree shape retains plastics more easily than all other vegetated and unvegetated types.

26 citations


Journal ArticleDOI
TL;DR: In this paper , the authors investigated the role of vegetation as a plastic trap and the possible detrimental effects of plastic on the plant health status in 8 central Italian rivers. And they found that the highest plastic density was found on the shrubby type suggesting that a tree shape retains plastics more easily than all other vegetated and unvegetated types.

26 citations


Journal ArticleDOI
TL;DR: In this paper , the causal links among export diversification, per capita income, and energy demand for 20 Asia-Pacific Economic Cooperation (APEC) countries were investigated by using sequential Artificial Neural Networks.

22 citations


Journal ArticleDOI
TL;DR: In this article , the authors give a geometric characterization of minimal linear codes and derive some bounds on the length and distance of minimal codes, according to their dimension and the underlying field size.
Abstract: <p style='text-indent:20px;'>In this paper, we give a geometric characterization of minimal linear codes. In particular, we relate minimal linear codes to cutting blocking sets, introduced in a recent paper by Bonini and Borello. Using this characterization, we derive some bounds on the length and the distance of minimal codes, according to their dimension and the underlying field size. Furthermore, we show that the family of minimal codes is asymptotically good. Finally, we provide some geometrical constructions of minimal codes as cutting blocking sets.</p>

13 citations


Journal ArticleDOI
TL;DR: In this article , the authors deal with the development of surrogate models suitable for the simulation of aerodynamic performance and acoustic emission in terms of tonal components of multi-propeller systems like those applicable in urban air-mobility vehicles.

13 citations


Journal ArticleDOI
TL;DR: In this article , a new Artificial Neural Networks (ANNs) algorithm is adopted in a multivariate framework to investigate the dynamic interactions among a range of Logistics Performance Indexes (LPI), the demand for oil products, and carbon dioxide (CO2) emissions from fuel combustion in the transport sector.

13 citations


Journal ArticleDOI
TL;DR: In this article , the authors explore the nexus among CO 2 emissions, energy use, and GDP in Russia using annual data ranging from 1970 to 2017, and demonstrate the existence of causal links in sub-permanent states among these variables.
Abstract: Abstract The aim of this study is to explore the nexus among CO 2 emissions, energy use, and GDP in Russia using annual data ranging from 1970 to 2017. We first conduct time-series analyses (stationarity, structural breaks, and cointegration tests). Then, we present a new D2C algorithm, and we run a Machine Learning experiment. Comparing the results of the two approaches, we conclude that economic growth causes energy use and CO 2 emissions. However, the critical analysis underlines how the variance decomposition justifies the qualitative approach of using economic growth to immediately implement expenses for the use of alternative energies able to reduce polluting emissions. Finally, robustness checks to validate the results through a new D2C algorithm are performed. In essence, we demonstrate the existence of causal links in sub-permanent states among these variables.

12 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigated the link existing between structural and functional properties of TiCu(Ag) thin films deposited by physical vapor deposition magnetron sputtering (MS-PVD) on Si substrates.

12 citations


Journal ArticleDOI
TL;DR: In this article , a computer-vision-based methodology for structural health monitoring was applied to a shake table investigation, where three rubble stone masonry walls, one unreinforced and two reinforced, were tested under natural earthquake base inputs, progressively scaled up to collapse.
Abstract: Detecting the onset of structural damage and its progressive evolution is crucial for the assessment and maintenance of the built environment. This paper describes the application of a computer-vision-based methodology for structural health monitoring to a shake table investigation. Three rubble stone masonry walls, one unreinforced and two reinforced, were tested under natural earthquake base inputs, progressively scaled up to collapse. White noise signals were also applied for dynamic identification purposes. Throughout the experiments, videos were recorded, under both white noise excitation and environmental vibrations, with the table at rest. The videos were preprocessed with motion magnification algorithms and analyzed through a principal component analysis. The natural frequencies of the walls were detected and their progressive decay was associated with damage accumulation. Results agreed with those obtained from another measurement system available in the laboratory and were consistent with the crack pattern development surveyed during the tests. The proposed approach proved useful to derive information on the progressive deterioration of the structural properties, showing the feasibility of this methodology for real field applications.

12 citations


Journal ArticleDOI
TL;DR: In this article , the authors developed a machine learning experiment to assess the effects of vaccination on the fatality rate of the COVID-19 pandemic, where data from 192 countries were analyzed to explain the phenomena under study.
Abstract: Abstract The coronavirus disease 2019 (COVID-19), with new variants, continues to be a constant pandemic threat that is generating socio-economic and health issues in manifold countries. The principal goal of this study is to develop a machine learning experiment to assess the effects of vaccination on the fatality rate of the COVID-19 pandemic. Data from 192 countries are analysed to explain the phenomena under study. This new algorithm selected two targets: the number of deaths and the fatality rate. Results suggest that, based on the respective vaccination plan, the turnout in the participation in the vaccination campaign, and the doses administered, countries under study suddenly have a reduction in the fatality rate of COVID-19 precisely at the point where the cut effect is generated in the neural network. This result is significant for the international scientific community. It would demonstrate the effective impact of the vaccination campaign on the fatality rate of COVID-19, whatever the country considered. In fact, once the vaccination has started (for vaccines that require a booster, we refer to at least the first dose), the antibody response of people seems to prevent the probability of death related to COVID-19. In short, at a certain point, the fatality rate collapses with increasing doses administered. All these results here can help decisions of policymakers to prepare optimal strategies, based on effective vaccination plans, to lessen the negative effects of the COVID-19 pandemic crisis in socioeconomic and health systems.

Journal ArticleDOI
TL;DR: In this paper , it was shown that perchlorates and chlorides brines exhibit a strong dielectric response at much lower temperatures than other materials and therefore do not generate strong basal reflections at MARSIS frequencies and Martian temperatures.

Journal ArticleDOI
Marco Vitti1
TL;DR: In this paper , the virtual corrections to gg → HH and gg→ ZH are analytically evaluated combining an expansion in the small transverse momentum of the final particles with an expansion valid at high energies.
Abstract: A bstract The virtual corrections to gg → HH and gg → ZH are analytically evaluated combining an expansion in the small transverse momentum of the final particles with an expansion valid at high energies. The two expansion methods describe complementary regions of the phase space and we merge their results, extending the range of validity of both expansions using Padé approximants. We show that this approach can reproduce the available numerical results retaining the exact top quark mass dependence with an accuracy below the 1% level. Our results allow a fast and flexible evaluation of the virtual corrections of the considered processes. Furthermore, they are available in different renormalisation schemes of the top quark mass.

Journal ArticleDOI
TL;DR: In this article , a multi-objective optimization model for portfolio selection is proposed, where the authors add to the classical mean-variance analysis a third non-financial goal represented by the ESG scores.
Abstract: Over the last few decades, growing attention to the topic of social responsibility has affected financial markets and institutional authorities. Indeed, recent environmental, social, and financial crises have inevitably led regulators and investors to take into account the sustainable investing issue; however, the question of how Environmental, Social, and Governance (ESG) criteria impact financial portfolio performances is still open. In this work, we examine a multi-objective optimization model for portfolio selection, where we add to the classical Mean-Variance analysis a third non-financial goal represented by the ESG scores. The resulting optimization problem, formulated as a convex quadratic programming, consists of minimizing the portfolio variance with parametric lower bounds on the levels of the portfolio expected return and ESG. We provide here an extensive empirical analysis on five datasets involving real-world capital market indexes from major stock markets. Our empirical findings typically reveal the presence of two behavioral patterns for the 16 Mean-Variance-ESG portfolios analyzed. Indeed, over the last fifteen years we can distinguish two non-overlapping time windows on which the inclusion of portfolio ESG targets leads to different regimes in terms of portfolio profitability. Furthermore, on the most recent time window, we observe that, for the US markets, imposing a high ESG target tends to select portfolios that show better financial performances than other strategies, whereas for the European markets the ESG constraint does not seem to improve the portfolio profitability.

Journal ArticleDOI
TL;DR: In this paper , the authors derive a framework from which they obtain practical variants of all relevant information set decoding algorithms including the most recent improvements, and derive formulas for the practical attack costs.
Abstract: The selection of secure parameter sets requires an estimation of the attack cost to break the respective cryptographic scheme instantiated under these parameters. The current NIST standardization process for post-quantum schemes makes this an urgent task, especially considering the announcement to select final candidates by the end of 2021. For code-based schemes, recent estimates seemed to contradict the claimed security of most proposals, leading to a certain doubt about the correctness of those estimates. Furthermore, none of the available estimates include most recent algorithmic improvements on decoding linear codes, which are based on information set decoding (ISD) in combination with nearest neighbor search. In this work we observe that all major ISD improvements are build on nearest neighbor search, explicitly or implicitly. This allows us to derive a framework from which we obtain practical variants of all relevant ISD algorithms including the most recent improvements. We derive formulas for the practical attack costs and make those online available in an easy to use estimator tool written in python and C. Eventually, we provide classical and quantum estimates for the bit security of all parameter sets of current code-based NIST proposals.

Journal ArticleDOI
01 Jan 2022
TL;DR: In this article, the authors present a smart coordination mechanism between UAVs and ground vehicles (GVs), which sense information like body temperature and breathing rate of people, in order to support a variety of monitoring applications, including discovering the presence of infectious diseases.
Abstract: The massive increase in population density in cities has led to several urban problems, such as an increment of air pollution, traffic congestion, and a faster spread of infectious diseases. With the rapid innovation in the intelligent sensors technology, and its integration into smart vehicles and Unmanned Aerial Vehicles (UAVs), a novel sensing paradigm has been promoted, namely vehicular crowdsensing, which leverages on-board sensors to capture information from the surrounding environment. Collected data are then analyzed to take proper countermeasures. In this paper, we present a smart coordination mechanism between UAVs and ground vehicles (GVs), which sense information like body temperature and breathing rate of people, in order to support a variety of monitoring applications, including discovering the presence of infectious diseases. In our framework, namely GUAVA, aerial and ground vehicles are equipped with GPS devices and thermal cameras to monitor specific geographic areas, detect humans’ vital parameters and, at the same time, discover duplicate data by identifying matching faces in thermal video sequences with the GaussianFace algorithm. The sensing tasks in hard-to-reach places are assigned to UAVs, with the ability to power up wirelessly from the nearest GV and offload the collected monitoring images to it. Simulation results have assessed our proposed framework, showing good performance in terms of distinct Quality of Service (QoS) metrics.

Journal ArticleDOI
TL;DR: In this article , the authors investigated the use of adaptive metamodels based on radial basis functions (RBFs) for aeroacoustic applications of highly innovative configurations and showed that using surrogate models, i.e., metamodes, significantly reduces computing costs, especially in view of a robust approach to the optimised design.
Abstract: The present work reports an investigation on the use of adaptive metamodels based on radial basis functions (RBFs) for aeroacoustic applications of highly innovative configurations. The relevance of the topic lies on the paramount importance of metamodelling techniques within the design optimisation process of disruptive aircraft layouts. Indeed, the air traffic growth, consequently the hard environmental constraints imposed by regulations, will make a technological breakthrough, an imperative need within few years. As a consequence, the engineering community is paying particular attention to the development of innovative techniques for the design of unconventional configurations. For this class of applications, the designer cannot successfully rely on historical data or low-fidelity models, and the expensive direct simulations remain the only valuable design strategy. In this regard, it can be demonstrated that the use of surrogate models, i.e., metamodels, significantly reduces the computing costs, especially in view of a robust approach to the optimised design. In order to further improve the efficiency of metamodel-based techniques, dynamic approaches based on hyperparameter optimisation and adaptive sampling procedures have been recently developed. The case study presented here pertains the exploiting of dynamic RBF-based metamodels for noise shielding applications. The analysis of the metamodel performances and its convergence properties shows how the final number of direct simulations is significantly reduced by the hyperparameter optimisation algorithm, still strongly depending on the choice of the RBF kernel function.


Journal ArticleDOI
TL;DR: In this paper , the authors proposed a novel approach to indoor tracking that can represent a promising and non-expensive solution for some of the critical issues that remain, which can assist visitors during the fruition of cultural and artistic resources.
Abstract: Nowadays, technology makes it possible to admire objects and artworks exhibited all over the world remotely. We have been able to appreciate this convenience even more in the last period, in which the pandemic has forced us into our homes for a long time. However, visiting art sites in person remains a truly unique experience. Even during on-site visits, technology can help make them much more satisfactory, by assisting visitors during the fruition of cultural and artistic resources. To this aim, it is necessary to monitor the active user for acquiring information about their behavior. We, therefore, need systems able to monitor and analyze visitor behavior. The literature proposes several techniques for the timing and tracking of museum visitors. In this article, we propose a novel approach to indoor tracking that can represent a promising and non-expensive solution for some of the critical issues that remain. In particular, the system we propose relies on low-cost equipment (i.e., simple badges and off-the-shelf RGB cameras) and harnesses one of the most recent deep neural networks (i.e., Faster R-CNN) for detecting specific objects in an image or a video sequence with high accuracy. An experimental evaluation performed in a real scenario, namely, the “Exhibition of Fake Art” at Roma Tre University, allowed us to test our system on site. The collected data has proven to be accurate and helpful for gathering insightful information on visitor behavior.

Journal ArticleDOI
TL;DR: In this paper, the authors applied micro-FTIR spectroscopy to investigate the chemical modifications in the tumor stroma and found that the stroma chemical modifications are more indicative of malignancy compared to the epithelium.

Book ChapterDOI
01 Jan 2022
TL;DR: In this paper , the generalized torsion point attacks were generalized to SIDH-type schemes and a new adaptive attack vector was introduced, where the access to a key exchange oracle was used to recover the action of the secret isogeny on larger subgroups.
Abstract: The SIDH key exchange is the main building block of SIKE, the only isogeny based scheme involved in the NIST standardization process. In 2016, Galbraith et al. presented an adaptive attack on SIDH. In this attack, a malicious party manipulates the torsion points in his public key in order to recover an honest party’s static secret key, when having access to a key exchange oracle. In 2017, Petit designed a passive attack (which was improved by de Quehen et al. in 2020) that exploits the torsion point information available in SIDH public key to recover the secret isogeny when the endomorphism ring of the starting curve is known. In this paper, firstly, we generalize the torsion point attacks by de Quehen et al. Secondly, we introduce a new adaptive attack vector on SIDH-type schemes. Our attack uses the access to a key exchange oracle to recover the action of the secret isogeny on larger subgroups. This leads to an unbalanced SIDH instance for which the secret isogeny can be recovered in polynomial time using the generalized torsion point attacks. Our attack is different from the GPST adaptive attack and constitutes a new cryptanalytic tool for isogeny based cryptography. This result proves that the torsion point attacks are relevant to SIDH (Disclaimer: this result is applicable to SIDH-type schemes only, not to SIKE.) parameters in an adaptive attack setting. We suggest attack parameters for some SIDH primes and discuss some countermeasures.

Journal ArticleDOI
TL;DR: In this article , a high-power diode laser joining process of aluminum films coated with a polyester resin with polypropylene (PP) films was investigated. And the results indicated that the high potential of laser systems in the joining process for aluminum and PP films for food packaging applications.
Abstract: Abstract The present work deals with the high-power diode laser joining process of aluminum films coated with a polyester resin with polypropylene (PP) films. The first part of the work focused on analyzing the coating process of aluminum films with a polyester resin, using an automatic applicator. The second part of the work was focused on the analysis of the laser joining process of coated aluminum films with plastic counterparts made of PP. Different thicknesses and colors of the PP parts were tested in order to analyze the joining process under a wide range of different conditions. The experimental plan involved the study of the influence of the laser joining parameters, in particular the scanning speed and beam power, on the joints. The joints between aluminum and PP films were subsequently tested by means of tensile and peel-off tests. All the joints between aluminum and PP are obtained through the so-called laser transmission welding (LTW) mechanism. Analysis of the mechanical response of the welded joints allowed to identify the optimal processing window, that is, the choice of the operational parameters that leads to satisfactory welded joints, stating the high potential of laser systems in the joining process of aluminum and PP films for food packaging applications.

Book ChapterDOI
01 Jan 2022
TL;DR: In this article, the authors describe a more complex dynamical behavior when compared to the bulk water, which can be described by two mechanisms characterized by two well distinct time scales: α-relaxation typical of supercooled bulk water and other glass forming liquids, and a much slower relaxation that is present only in hydration water and coupled with the biomolecule dynamics.
Abstract: Water hydrating biomolecules shows a more complex dynamical behavior when compared to the bulk. Its translational slow dynamics can be described by two mechanisms characterized by two well distinct time scales. One mechanism is the \(\alpha\)-relaxation typical of supercooled bulk water and other glass forming liquids. Upon cooling, this relaxation shows a fragile-to-strong crossover due to the activation of hopping phenomena which permits to the water molecules in the hydration layer to escape from nearest neighbors cage. The second mechanism is a much slower relaxation that is present only in hydration water and it is coupled with the biomolecule dynamics. This long-relaxation shows upon cooling a strong-to-strong crossover in coincidence with the well-known Protein Dynamical Transition. Structural rearrangements of biomolecules can trap hydration water molecules over length-scale larger than nearest neighbors distances. This causes a new hopping regime specific only of hydration water and already active at high temperature.

Journal ArticleDOI
01 Jan 2022-Energy
TL;DR: In this article, an experimental campaign is conducted on two test rooms, and the measured data are used to generate equivalent homogeneous walls through an inverse approach, finding the equivalent thermo-physical properties able to best reproduce the thermal behaviors of the original walls and calculating the model efficiency index (EF).

Journal ArticleDOI
TL;DR: In the context of a two-Higgs doublet model, supplemented by an additional light pseudoscalar Higgs boson and a stable isosinglet fermion, this paper considered the possibility of addressing simultaneously the discrepancy from the standard expectation of the anomalous magnetic moment of the muon recently measured at Fermilab and the longstanding problem of the dark matter in the universe which can be accounted for by a thermal weakly interacting massive particle.

Journal ArticleDOI
Marco Vitti1
TL;DR: In this paper , the authors compute the QCD corrections at next-to-leading order for the process $gg \rightarrow ZH, including both the virtual two-loop terms and real-emission contributions.
Abstract: We compute the QCD corrections at next-to-leading order for the process $gg \rightarrow ZH$, including both the virtual two-loop terms and real-emission contributions. The two-loop box diagrams in the virtual corrections are approximated analytically over the complete phase space, combining the results of an expansion in the limit of small transverse momentum and an expansion in the regime of high energy. We obtain both inclusive and differential results for the cross section. We find that the NLO QCD corrections are of the same size as the LO contribution up to $ZH$ invariant masses close to 1 TeV, but they increase significantly when higher energies are considered, due to a class of real-emission diagrams in which the $Z$ boson is radiated from an open quark line. Finally, we estimate the uncertainty due to the renormalization scheme used for the top-quark mass both on the total and differential cross section.

Journal ArticleDOI
TL;DR: In this paper , an algebraic description for sum-rank metric codes, as quotient space of a skew polynomial ring, is provided. But the complexity of the algebraic model is not the same as in this paper.

Journal ArticleDOI
TL;DR: In this paper , the performance of the laser induced breakdown spectroscopy system has been demonstrated and the new capabilities of the runaway electron imaging spectrometry system for in-flight runaway studies have been explored.
Abstract: Abstract Since the 2018 IAEA FEC Conference, FTU operations have been devoted to several experiments covering a large range of topics, from the investigation of the behaviour of a liquid tin limiter to the runaway electrons mitigation and control and to the stabilization of tearing modes by electron cyclotron heating and by pellet injection. Other experiments have involved the spectroscopy of heavy metal ions, the electron density peaking in helium doped plasmas, the electron cyclotron assisted start-up and the electron temperature measurements in high temperature plasmas. The effectiveness of the laser induced breakdown spectroscopy system has been demonstrated and the new capabilities of the runaway electron imaging spectrometry system for in-flight runaways studies have been explored. Finally, a high resolution saddle coil array for MHD analysis and UV and SXR diamond detectors have been successfully tested on different plasma scenarios.

Journal ArticleDOI
TL;DR: In this paper, a new approach for prerequisite discovery based on word embeddings is presented. But public taxonomies of prerequisites, or learning object metadata useful to trace down prerequisites are not generally available.

Journal ArticleDOI
TL;DR: In this article , a Round Robin Test among international partners was performed using different versions of LEED sustainability protocol to the same building with the same boundary conditions, comparing and analyzing the results provided by the participants.