Intraguild predation, representing a true combination of predation and competition between two species that rely on a common resource, is of foremost importance in many natural communities. We investigate a spatial model of three species interaction, characterized by a Holling type II functional response and linear cross-diffusion. For this model we report necessary and sufficient conditions ensuring the insurgence of Turing instability for the coexistence equilibrium; we also obtain conditions characterizing the different patterns by multiple scale analysis. Numerical experiments confirm the occurrence of different scenarios of Turing instability, also including Turing–Hopf patterns.

A Cournot triopoly is a type of oligopoly market involving three firms that produce and sell homogeneous or similar products without cooperating with one another. In Cournot models, firms' decisions about production levels play a crucial role in determining overall market output. Compared to duopoly models, oligopolies with more than two firms have received relatively less attention in the literature. Nevertheless, triopoly models are more reflective of real-world market conditions, even though analyzing their dynamics remains a complex challenge. A reaction-diffusion system of PDEs generalizing a nonlinear triopoly model describing a master-slave Cournot game is introduced. The effect of diffusion on the stability of Nash equilibrium is investigated. Self-diffusion alone cannot induce Turing pattern formation. In fact, linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. The conditions for the onset of cross-diffusion-driven instability are obtained via linear stability analysis, and the formation of several Turing patterns is investigated through numerical simulations.

Land cover, or the biophysical cover of the earth's surface, plays an essential role in climate and environmental dynamics. Processes involving land cover change, are among the factors that most threaten the ecosystems sustainability and services. The objective of the work is to explore the potential of the PRISMA multi-temporal hyperspectral imagery in generating new EO products to complement/improve the products provided by Copernicus' Land Monitoring Service for the analysis and monitoring of complex and fragile ecosystems such as the coastal Metaponto (Southern Italy) by estimating of the land biological and economic productivity loss and land degradation vulnerability. Preliminary results showed that an improvement in ecosystem mapping is supported by the use of Artificial Neural Networks (ANN), k-Nearest Neighbors (KNN) and Support Vector Machines (SVM) and a hybrid approach to define the vegetation trait, leads to significant improvement in the damage assessment and land degradation assessment

Cyber insurance is a crucial tool for managing risks associated with cyber threats. A challenging task for insurance companies lies in pricing cyber risk. Our study is motivated by the reasonable assumption that firms entering into cyber insurance contracts face diverse cyber threats in terms of types and magnitude. Considering these differences ensures that premiums align with the actual risk exposure of the insured. The study discusses this approach proposing a case study based on the Chronology of Data Breaches provided by the Privacy Rights Clearinghouse.

Claude Shannon, eclettico matematico e ingegnere del Novecento, è considerato il padre della teoria dell’informazione, perché offrì una definizione formale, quantitativamente misurabile, di questo concetto, assimilandolo a quello di altre grandezze fisiche che possono essere descritte e calcolate matematicamente. Dimostrò poi fino a che punto l’informazione contenuta in un messaggio possa essere compressa, in modo da aumentare la velocità di trasmissione. Il secondo e fondamentale risultato di Shannon riguarda invece il canale di trasmissione, un qualunque mezzo attraverso il quale il messaggio viaggia e che può degradare parte dei contenuti trasmessi se il tasso di trasmissione supera la capacità del canale. Entrano in gioco quindi grandezze come l’errore, che si può ridurre inserendo nel messaggio strumenti matematici di correzione, e la stessa entropia, concetto sviluppato nella termodinamica ma che può riguardare anche la trasmissione delle informazioni, quale misura dell’incertezza di un risultato (la probabilità che sia quello giusto). Per esempio, in un testo italiano, la «e» è più probabile di una «z» e la stringa «le banche hanno un anno di tempo» è più probabile di «le banche anno un hanno di tempo». La teoria dell’informazione di Shannon è alla base di tutta la comunicazione digitale, che utilizza strumenti matematici per la compressione dei segnali, oggi indispensabile, per la riduzione degli errori di tramissione e per la gestione delle reti.

Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with Sentinel-2 multispectral imagery to produce early- and in-season crop maps using consolidated machine and deep learning algorithms. Results show that the accuracy of crop type classification using Sentinel-2 images is meaningfully poor compared with PRISMA (14% in overall accuracy (OA)). The 1D-CNN algorithm, with 89%, 91%, and 92% OA for winter, summer, and perennial cultivations, respectively, shows for the PRISMA images the highest accuracy in the in-season crop mapping and the fastest algorithm that achieves acceptable accuracy (OA 80%) for the winter, summer, and perennial cultivations early-season mapping using PRISMA images. Moreover, the 1D-CNN algorithm shows a limited reduction (6%) in performance, appearing to be the best algorithm for crop mapping within operational use in cross-farm applications. Machine/deep learning classification algorithms applied on the test fields cross-scene demonstrate that PRISMA hyperspectral time series images can provide good results for early- and in-season crop mapping.

Cyber risk is a significant concern for all types of businesses. The consequences of a cyber attack can be quite severe. Investing in security to mitigate the impact of such risks is a crucial task, both in terms of the frequency and the severity of cyber incidents. In this paper, we propose a practical application of the Gordon and Loeb model, thereby suggesting a methodology to estimate risk exposure and reconsidering some investment evaluation metrics. Our findings strongly support the claim that maximizing the expected net benefit of an investment solely at the optimal level is not sufficient for sound decision-making. On the contrary, incorporating metrics that evaluate the benefit in relation to risk and consider worst-case scenarios offers deeper insights

PRISMA is a hyperspectral pushbroom sensor, launched by the Italian Space Agency in 2019. PRISMA collects the reflected Earth signal from VNIR to the SWIR with 230 spectral bands with a variable FWHM according to the prism dispersion element. This work intends to develop a procedure suitable to monitor the consistency of photon and thermal noise components across a times series of L1 radiance images collected on different Mediterranean scenarios (i.e. rural and coastal). To improve the retrieval of the useful signal and the random noise on PRISMA images the spatial variability of the scenes has been considered in the new version of the HYperspectral Noise Parameters Estimation (HYNPE) algorithm. The procedure, tested on two PRISMA time series, has assessed quite stable and coherent values for the retrieved noise coefficients, not significantly affected by seasonal radiance variations and scene characteristics

After giving some background on neuron physiology, the classical (deterministic) models for the generation of action potentials are briefly introduced and their limitations discussed, so to motivate the need for a stochastic description of the neuronal firing activity. The more relevant stochastic models for single neuron dynamics are reviewed, with particular attention to the phenomenon of spike-frequency adaptation. Then some approaches to the modeling of network dynamics, where populations of excitatory and inhibitory neurons interact, are described. Finally,some recent models applying suitable strategies to reproduce complex neural dynamics emerging from networks of spiking neurons, such as fractional differentiation or other memory effects, are introduced as a perspective for current and future research.

Insieme al teorema dimostrato da Bernoulli nel 1713 e noto oggi come legge dei grandi numeri, il teorema del limite centrale è alla base della statistica inferenziale, che si propone di ricavare informazioni e di trarre conclusioni su una popolazione a partire dall'osservazione di un campione casuale dei suoi elementi.In sintesi, il teorema dice che in ogni situazione in cui i dati da noi osservati sono influenzati da tanti piccoli effetti casuali indipendenti tra loro, la distribuzione risultante sarà approssimativamente una curva gaussiana, detta anche normale. Ciò permette di determinare un valore attendibile per un parametro di interesse, come il valore atteso, con il relativo intervallo di fiducia per la nostra stima; o di valutare la credibilità di un'ipotesi di carattere generale dopo una serie di osservazioni.Le sue applicazione spaziano nei campi più diversi. Per esempio, l'altezza delle donne italiane, la luminosità delle stelle, i valori di colesterolo della popolazione di maschi adulti, le fluttuazioni giornaliere di un indice del mercato azionario, i punteggi registrati in un test preselettivo, fino all'attendibilità dei sondaggi e all'efficacia dei vaccini sulla popolazione.

Mortality shocks, such as pandemics, threaten the consolidated longevity improvements, confirmed in the last decades for the majority of western countries. Indeed, just before the COVID-19 pandemic, mortality was falling for all ages, with a different behavior according to different ages and countries. It is indubitable that the changes in the population longevity induced by shock events, even transitory ones, affecting demographic projections, have financial implications in public spending as well as in pension plans and life insurance. The Short Term Mortality Fluctuations (STMF) data series, providing data of all-cause mortality fluctuations by week within each calendar year for 38 countries worldwide, offers a powerful tool to timely analyze the effects of the mortality shock caused by the COVID-19 pandemic on Italian mortality rates. This dataset, recently made available as a new component of the Human Mortality Database, is described and techniques for the integration of its data with the historical mortality time series are proposed. Then, to forecast mortality rates, the well-known stochastic mortality model proposed by Lee and Carter in 1992 is first considered, to be consistent with the internal processing of the Human Mortality Database, where exposures are estimated by the Lee-Carter model; empirical results are discussed both on the estimation of the model coefficients and on the forecast of the mortality rates. In detail, we show how the integration of the yearly aggregated STMF data in the HMD database allows the Lee-Carter model to capture the complex evolution of the Italian mortality rates, including the higher lethality for males and older people, in the years that follow a large shock event such as the COVID-19 pandemic. Finally, we discuss some key points concerning the improvement of existing models to take into account mortality shocks and evaluate their impact on future mortality dynamics.

The PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite, launched by the Italian Space Agency (ASI) is presently operational on a global scale. The mission includes the hyperspectral imager PRISMA working in the 400-2500 nm spectral range with 234 bands and a panchromatic (PAN) camera (400-750 nm). In the context of this work, we intend to determine the two noise components (photon and thermal noise) and assess SNR with an image based approach. Results show that the SNR evaluation assessed through the collected images is coherent with the mission requirements and that the PRISMA noise components, derived on the fragmented Pignola test site, in Southern Italy, are comparable to the ones derived on the Rail Road Valley calibration site.

A classical Lotka-Volterra model with the logistical growth of prey-and-hunting coopera-tion in the functional response of predators to prey was extended by introducing advection terms,which included the velocities of animals. The effect of velocity on the kinetics of the problem wasanalyzed. In order to examine the band behavior of species over time, traveling wave solutions wereintroduced, and conditions for the coexistence of both populations and/or extinction were found.Numerical simulations illustrating the obtained results were performe

Digitization offers great opportunities as well as new challenges. Indeed, these opportunities entail increased cyber risks, both from deliberate cyberattacks and from incidents caused by inadvertent human error. Cyber risk must be mastered, and to this aim, its quantification is an urgent challenge. There is a lot of interest in this topic from the insurance community in order to price adequate coverage to their customers. A key first step is to investigate the frequency and severity of cyber incidents. On the grounds that data breaches seem to be the main cause of cyber incidents, the aim of this paper is to give further insights about the frequency and severity statistical distributions of malicious and negligent data breaches. For this purpose, we refer to a publicly available dataset: the Chronology of Data Breaches provided by the Privacy Rights Clearinghouse.

In March 2019, the PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyper-spectral satellite was launched by the Italian Space Agency (ASI), and it is currently operational on a global basis. The mission includes the hyperspectral imager PRISMA working in the 400-2500 nm spectral range with 237 bands and a panchromatic (PAN) camera (400-750 nm). This paper presents an evaluation of the PRISMA top-of-atmosphere (TOA) L1 products using different in situ measurements acquired over a fragmented rural area in Southern Italy (Pignola) between October 2019 and July 2021. L1 radiance values were compared with the TOA radiances simulated with a radiative transfer code configured using measurements of the atmospheric profile and the surface spectral characteristics. The L2 reflectance products were also compared with the data obtained by using the ImACor code atmospheric correction tool. A preliminary assessment to identify PRISMA noise characteristics was also conducted. The results showed that: (i) the PRISMA performance, as measured at the Pignola site over different seasons, is characterized by relative mean absolute differences (RMAD) of about 5-7% up to 1800 nm, while a decrease in accuracy was observed in the SWIR; (ii) a coherent noise could be observed in all the analyzed images below the 630th scan line, with a frequency of about 0.3-0.4 cycles/pixel; (iii) the most recent version of the standard reflectance L2 product (i.e., Version 2.05) matched well the reflectance values obtained by using the ImACor atmospheric correction tool. All these preliminary results confirm that PRISMA imagery is suitable for an accurate retrieval of the bio-geochemical variables pertaining to a complex fragmented ecosystem such as that of the Southern Apennines. Further studies are needed to confirm and monitor PRISMA data performance on different land-cover areas and on the Radiometric Calibration Network (RadCalNet) targets.

A reaction-diffusion system governing the prey-predator interaction with Allee effect on the predators, already introduced by the authors in a previous work is reconsidered with the aim of showing destabilization mechanisms of the biologically meaning equilibrium and detecting some aspects for the eventual oscillatory pattern formation. Extensive numerical simulations, depicting such complex dynamics, are shown. In order to complete the stability analysis of the coexistence equilibrium, a nonlinear stability result is shown.

A prey-predator system with logistic growth of prey and hunting cooperation of predators is studied. The introduction of fractional time derivatives and the related persistent memory strongly characterize the model behavior, as many dynamical systems in the applied sciences are well described by such fractional-order models. Mathematical analysis and numerical simulations are performed to highlight the characteristics of the proposed model. The existence, uniqueness and boundedness of solutions is proved; the stability of the coexistence equilibrium and the occurrence of Hopf bifurcation is investigated. Some numerical approximations of the solution are finally considered; the obtained trajectories confirm the theoretical findings. It is observed that the fractional-order derivative has a stabilizing effect and can be useful to control the coexistence between species.

In this paper, a reaction-diffusion prey-predator system including the fear effect of predator on prey population and group defense has been considered. The conditions for the onset of cross-diffusion-driven instability are obtained by linear stability analysis. The technique of multiple time scales is employed to deduce the amplitude equation near Turing bifurcation threshold by choosing the cross-diffusion coefficient as a bifurcation parameter. The stability analysis of these amplitude equations leads to the identification of various Turing patterns driven by the cross-diffusion, which are also investigated through numerical simulations.

In this paper, a reaction-diffusion prey-predator system including the fear effect of predator on prey population and group defense has been considered. The conditions for the onset of cross-diffusion-driven instability are obtained by linear stability analysis. The technique of multiple time scales is employed to deduce the amplitude equation near Turing bifurcation threshold by choosing the cross-diffusion coefficient as a bifurcation parameter. The stability analysis of these amplitude equations leads to the identification of various Turing patterns driven by the cross-diffusion, which are also investigated through numerical simulations.

A full ODE model for the transmission of cholera is investigated, includ- ing both direct and indirect transmission and a nonlinear growth for pathogens. The direct problem is preliminarily studied and characterized in terms of reproduction number, endemic and disease free equilibria. The inverse problem is then discussed in view of parameter estimation and model identification via a Least Squares Approximation approach. The procedure is applied to real data coming from the recent Yemen cholera outbreak of 2017-2018.