We present here a comparison between collision-streaming and finite-difference lattice Boltzmann (LB) models. This study provides a derivation of useful formulae which help one to properly compare the simulation results obtained with both LB models. We consider three physical problems: the shock wave propagation, the damping of shear waves, and the decay of Taylor-Green vortices, often used as benchmark tests. Despite the different mathematical and computational complexity of the two methods, we show how the physical results can be related to obtain relevant quantities.

We investigate nonlinear elliptic Dirichlet problems whose growth is driven by a general anisotropic N-function, which is not necessarily of power-type and need not satisfy the ? nor the ? -condition. Fully anisotropic, non-reflexive Orlicz-Sobolev spaces provide a natural functional framework associated with these problems. Minimal integrability assumptions are detected on the datum on the right-hand side of the equation ensuring existence and uniqueness of weak solutions. When merely integrable, or even measure, data are allowed, existence of suitably further generalized solutions--in the approximable sense--is established. Their maximal regularity in Marcinkiewicz-type spaces is exhibited as well. Uniqueness of approximable solutions is also proved in case of L-data.

This review discusses the lattice Boltzmann-particle dynamics (LBPD) multiscale paradigm for the simulation of complex states of flowing matter at the interface between physics, chemistry, and biology. In particular, current large-scale LBPD simulations of biopolymer translocation across cellular membranes, molecular transport in ion channels, and amyloid aggregation in cells are described. Prospects are provided for future LBPD explorations in the direction of cellular organization, the direct simulation of full biological organelles, all the way up to physiological scales of potential relevance to future precision-medicine applications, such as the accurate description of homeostatic processes. It is argued that. with the advent of Exascale computing, the mesoscale physics approach advocated in this review may come to age in the next decade and open up new exciting perspectives for physics-based computational medicine.

Process mining is the set of techniques to retrieve a process model starting from available logging data. The discovered process model has to be analyzed to verify whether it respects the defined properties, i.e., the so-called compliance checking. Our aim is to use a model checking based approach to verify compliance. First, we propose an integrated-tool approach using existing tools as ProM (a framework supporting process mining techniques) and CADP (a formal verification environment). More precisely, the execution traces from a software system are extracted. Then, using the "Mine Transition System" plugin in ProM, we obtain a labelled transition system, that can be easily used to verify formal properties through CADP. However, this choice presents the "state explosion" problem, i.e., models discovered through the classical process mining techniques tend to be large and complex. In order to solve this problem, another custom-made approach is shown, which accomplishes a pre-processing on the traces to obtain abstract traces, where abstraction is based on the set of temporal logic formulae specifying the system properties. Then, from the set of abstracted traces, we discover a system described in Lotos, a process algebra specification language; in this way we do not build an operational model for the system, but we produce only a language description from which a model checking environment will automatically obtain the reduced corresponding transition system. Real systems have been used as case studies to evaluate the proposed methodologies.

Measures and methods used in financial sector to quantify risk, have been recently applied to cyber world. The aim is to help organizations to improve risk management strategies and to wisely plan investments in cyber security. On the other hand, they are useful instruments for insurance companies in pricing cyber insurance contracts and setting the minimum capital requirements defined by the regulators. In this paper we propose an estimation of Value at Risk (VaR), referred to as Cyber Value at Risk in cyber security domain, and Tail Value at risk (TVaR). The data breach information we use is obtained from the 'Chronology of data breaches' compiled by the Privacy Rights Clearinghouse.

In the last decades companies worldwide are facing a new kind of risk, namely cyber risk, that has emerged as one of the top challenges in risk management. Insurance was only recently applied to cyber world and it is increasingly becoming part of the risk management process, posing many challenges to actuaries. One of the main issues is the lack of data, in particular nancial ones. The aim of the paper is to point out the peculiarities of cyber insurance contracts with respect to the classical non life insurance ones both from the insurer and the insured's perspective. Therefore, the main actuarial principles that are fundamental to any valu- ation in cyber context are discussed. An illustrative example is proposed where the Chronology of Data Breaches provided by the Privacy Rights Clearing House is deeply analyzed. The most suitable distributions to represent the frequency and the severity of the reported cyber incidents are examined and the value at risk measure is estimated. Then, two ex- emplifying cases oer the assessment of both the premium required by the insurer and the indierence premium that the insured is willing to pay. Even though this research is still preliminary and shows some limits highlighted by the authors, it could offer useful information to better un- derstand this peculiar kind of insurance policies.

Cloud detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking can be translated directly into significant uncertainty in the retrieved downstream geophysical products. The problem is particularly challenging when only of a limited number of spectral bands is available, and thermal infrared bands are lacking. This is the case of Proba-V instrument, for which the European Space Agency (ESA) carried out a dedicated Round Robin exercise, aimed at intercomparing several cloud detection algorithms to better understand their advantages and drawbacks for various clouds and surface conditions, and to learn lessons on cloud detection in the VNIR and SWIR domain for land and coastal water remote sensing. The present contribution is aimed at a thorough quality assessment of the results of the cloud detection approach we proposed, based on Cumulative Discriminant Analysis. Such a statistical method relies on the empirical cumulative distribution function of the measured reflectance in clear and cloudy conditions to produce a decision rule. It can be adapted to the user's requirements in terms of preferred levels for both type I and type II errors. In order to obtain a fully automatic procedure, we choose as a training dataset a subset of the full Proba-V scenes for which a cloud mask is estimated by a consolidated algorithm (silver standard), that is from either SEVIRI, MODIS or both sensors. Within this training set, different subsets have been setup according to the different types of surface underlying scenes (water, vegetation, bare land, urban, and snow/ice). We present the analysis of the cloud classification errors for a range of such test scenes to yield important inferences on the efficiency and accuracy of the proposed methodology when applied to different types of surfaces.

Background. Type 2 diabetes (T2D) is a chronic metabolic disease potentially leading to serious widespread tissue damage. Human organism develops T2D when the glucose-insulin control is broken for reasons that are not fully understood but have been demonstrated to be linked to the emergence of a chronic inflammation. Indeed such low-level chronic inflammation affects the pancreatic production of insulin and triggers the development of insulin resistance, eventually leading to an impaired control of the blood glucose concentration. On the contrary, it is well-known that obesity and inflammation are strongly correlated. Aim. In this study, we investigate in silico the effect of overfeeding on the adipose tissue and the consequent set up of an inflammatory state. We model the emergence of the inflammation as the result of adipose mass increase which, in turn, is a direct consequence of a prolonged excess of high calorie intake. Results. The model reproduces the fat accumulation due to excessive caloric intake observed in two clinical studies. Moreover, while showing consistent weight gains over long periods of time, it reveals a drift of the macrophage population toward the proinflammatory phenotype, thus confirming its association with fatness.

Sex dimorphism in cell response to stress has previously been investigated by different research groups. This dimorphism could be at least in part accounted for by sex-biased expression of regulatory elements such as microRNAs (miRs). In order to spot previously unknown miR expression differences we took advantage of prior knowledge on specialized databases to identify X chromosome-encoded miRs potentially escaping X chromosome inactivation (XCI). MiR-548am-5p emerged as potentially XCI escaper and was experimentally verified to be significantly up-regulated in human XX primary dermal fibroblasts (DFs) compared to XY ones. Accordingly, miR-548am-5p target mRNAs, e.g. the transcript for Bax, was differently modulated in XX and XY DFs. Functional analyses indicated that XY DFs were more prone to mitochondria-mediated apoptosis than XX ones. Experimentally induced overexpression of miR548am-5p in XY cells by lentivirus vector transduction decreased apoptosis susceptibility, whereas its down-regulation in XX cells enhanced apoptosis susceptibility. These data indicate that this approach could be used to identify previously unreported sex-biased differences in miR expression and that a miR identified with this approach, miR548am-5p, can account for sex-dependent differences observed in the susceptibility to mitochondrial apoptosis of human DFs.

Editorial Introduction of a special issue

In this paper an in silico study of the behavior of an active polar emulsion is reported, focusing on the case of a highly off-symmetric ratio between the polar (active) and passive components, both for the extensile and contractile case. In absence of activity the system is characterized by an hexatic-ordered droplets phase. We find that small extensile activity is able to enhance the hexatic order in the array of droplets with respect to the passive case, while increasing activity aster-like rotating droplets appear. In contractile systems activity creates shear flows and elongated structures are formed.

This paper considers a hub location problem where several carriers operate on a shared network to satisfy a given demand represented by a set of commodities. Possible cooperative strategies are studied where carriers can share resources or swap their respective commodities to produce tangible cost savings while fully satisfying the existing demand. Three different collaborative policies are introduced and discussed, and mixed integer programming formulations are provided for each of them. Theoretical analyses are developed in order to assess the potential savings of each model with respect to traditional non-collaborative approaches. An empirical performance comparison on state-of-art sets of instances offers a complementary viewpoint. The influence of several diverse problem parameters on the performance is analyzed to identify those operational settings enabling the highest possible savings for the considered collaborative hub location models. The number of carriers and the number of open hubs have shown to play a key role; depending on the collaborative strategy, savings of up to 50% can be obtained as the number of carriers increases or the number of open hubs decreases.

The exploration and analysis of Web graphs has flourished in the recent past, producing a large number of relevant and interesting research results. However, the unique characteristics of the Tor network demand for specific algorithms to explore and analyze it. Tor is an anonymity network that allows offering and accessing various Internet resources while guaranteeing a high degree of provider and user anonymity. So far the attention of the research community has focused on assessing the security of the Tor infrastructure. Most research work on the Tor network aimed at discovering protocol vulnerabilities to de-anonymize users and services, while little or no information is available about the topology of the Tor Web graph or the relationship between pages' content and topological structure. With our work we aim at addressing such lack of information. We describe the topology of the Tor Web graph measuring both global and local properties by means of well-known metrics that require due to the size of the network, high performance algorithms. We consider three different snapshots obtained by extensively crawling Tor three times over a 5 months time frame. Finally we present a correlation analysis of pages' semantics and topology, discussing novel insights about the Tor Web organization and its content. Our findings show that the Tor graph presents some of the character- istics of social and surface web graphs, along with a few unique peculiarities.

Morphometric, biochemical and genetic analyses were conducted on Olea europaea L. of Campania, an area of Southern Italy highly suited to the cultivation of olive trees and the production of extra virgin olive oil (EVOO). We aimed to characterize the distribution of morphological, biochemical and genetic diversity in this area and to develop a practical tool to aid traceability of oils. Phenotypes were characterized using morphometric data of drupes and leaves; biochemical and genetic diversity were assessed on the basis of the fatty acid composition of the EVOOs and with microsatellite markers, respectively. We provide an open-source tool as a novel R package titled 'OliveR', useful in performing multivariate data analysis using a point and click interactive approach. These analyses highlight a clear correlation among the morphological, biochemical and genetic profiles of samples with four collection sites, and confirm that Southern Italy represents a wide reservoir of phenotypic and genetic variability.

In this paper, we deal with a group variable in size of pedestrians moving in a unknown confined environment and searching for an exit. Pedestrian dynamics are simulated by means of a recently introduced microscopic (agent-based) model, characterized by an exploration phase and an egress phase. First, we study the model to reveal the role of its main parameters and its qualitative properties. Second, we tackle a robust optimization problem by means of the Particle Swarm Optimization method, aiming at reducing the time-to-target by adding in the walking area multiple obstacles optimally placed and shaped. Robustness is sought against the number of people in the group, which is an uncertain quantity described by a random variable with given probability density distribution.

We review the state of the art of active fluids with particular attention to hydrodynamic continuous models and to the use of Lattice Boltzmann Methods (LBM) in this field. We present the thermodynamics of active fluids, in terms of liquid crystals modelling adapted to describe large-scale organization of active systems, as well as other effective phenomenological models. We discuss how LBM can be implemented to solve the hydrodynamics of active matter, starting from the case of a simple fluid, for which we explicitly recover the continuous equations by means of Chapman-Enskog expansion. Going beyond this simple case, we summarize how LBM can be used to treat complex and active fluids. We then review recent developments concerning some relevant topics in active matter that have been studied by means of LBM: spontaneous flow, self-propelled droplets, active emulsions, rheology, active turbulence, and active colloids.

In some important biological phenomena Volterra integral and integrodifferential equations represent an appropriate mathematical model for the description of the dynamics involved (see e.g. [1], and the bibliography therein). In most cases, the kernels of these equations are of convolution type, however, some recent applications, as cell migration and collective motion [4-5], are characterized by kernels with a quasi-convolution form, namely involving a convolution contribution plus a non-convolution term. We focus on problems of this type and exploit some known results about convolution equations [2, 3], in order to describe the asymptotic dynamics of numerical approximations and connect the results to the behaviour of the analytical solution

Purpose: Beckwith-Wiedemann syndrome (BWS) is a developmental disorder caused by dysregulation of the imprinted gene cluster of chromosome 11p15.5 and often associated with loss of methylation (LOM) of the imprinting center 2 (IC2) located in KCNQ1 intron 10. To unravel the etiological mechanisms underlying these epimutations, we searched for genetic variants associated with IC2 LOM. Methods: We looked for cases showing the clinical features of both BWS and long QT syndrome (LQTS), which is often associated with KCNQ1 variants. Pathogenic variants were identified by genomic analysis and targeted sequencing. Functional experiments were performed to link these pathogenic variants to the imprinting defect. Results: We found three rare cases in which complete IC2 LOM is associated with maternal transmission of KCNQ1 variants, two of which were demonstrated to affect KCNQ1 transcription upstream of IC2. As a consequence of KCNQ1 haploinsufficiency, these variants also cause LQTS on both maternal and paternal transmission. Conclusion: These results are consistent with the hypothesis that, similar to what has been demonstrated in mouse, lack of transcription across IC2 results in failure of methylation establishment in the female germline and BWS later in development, and also suggest a new link between LQTS and BWS that is important for genetic counseling.