On the excursion area of perturbed Gaussian fields

We investigate Lipschitz-Killing curvatures for excursion sets of random fields on $\mathbb R^2$ under small spatial-invariant random perturbations. An expansion formula for mean curvatures is derived when the magnitude of the perturbation vanishes, which recovers the Gaussian Kinematic Formula at the limit by contiguity of the model. We develop an asymptotic study of the perturbed excursion area behaviour that leads to a quantitative non-Gaussian limit theorem, in Wasserstein distance, for fixed small perturbations and growing domain. When letting both the perturbation vanish and the domain grow, a standard Central Limit Theorem follows. Taking advantage of these results, we propose an estimator for the perturbation which turns out to be asymptotically normal and unbiased, allowing to make inference through sparse information on the field

Optimization of Stone Cutting Techniques for the Seismic Protection of Archaeological Sites

Since the beginning of civilization, history tells of the movement of art pieces, monuments and manufacts from site to site. The causes are multiple: the displacements due to the "spoils of war", ordered by kings and emperors, the movements caused by the need for reuse, especially in the early Christian period, and so forth. Considerations about the events of the past, yield a possible strategy to transform this concept into a technique for earthquake prevention of archaeological sites. The seismic safety retrofits have often proven to be scarcely effective, because of the difficulties involved in complex sites. The aim of this study is to analyze an "alternative" method of preventing natural disaster like floods, eruption and earthquakes, through the movimentation of the most representative structural elements of archaeological sites by decomposition of the masonry and marbles [1]. The procedure considers a process of "cutting optimization," calibrated on the characteristics of the specific material that has to be cut and then displaced in safer places (i.e., MEP, "manufact evacuation plan"). This process should not create excessive problems to the structure, and aims to reassembly the manufact in contexts able to guarantee safety through advanced earthquake-resistant expedients. From these considerations, the work develops a procedure to safeguard the archaeological site of Pompei (Naples), through an appropriate analysis of representative portions of the site, aimed to a careful handling and to a proper reconstruction in a safe location, from the seismic point of vie

Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory

This paper deals with the problem of estimating the level sets of an unknown distribution function $F$. A plug-in approach is followed. That is, given a consistent estimator $F_n$ of $F$, we estimate the level sets of $F$ by the level sets of $F_n$. In our setting no compactness property is a priori required for the level sets to estimate. We state consistency results with respect to the Hausdorff distance and the volume of the symmetric difference. Our results are motivated by applications in multivariate risk theory. In this sense we also present simulated and real examples which illustrate our theoretical results.Level sets ; Distribution function ; Plug-in estimation ; Hausdorff distance ; Conditional Tail Expectation

A Review of Laboratory and Numerical Techniques to Simulate Turbulent Flows

Turbulence is still an unsolved issue with enormous implications in several fields, from the turbulent wakes on moving objects to the accumulation of heat in the built environment or the optimization of the performances of heat exchangers or mixers. This review deals with the techniques and trends in turbulent flow simulations, which can be achieved through both laboratory and numerical modeling. As a matter of fact, even if the term “experiment” is commonly employed for laboratory techniques and the term “simulation” for numerical techniques, both the laboratory and numerical techniques try to simulate the real-world turbulent flows performing experiments under controlled conditions. The main target of this paper is to provide an overview of laboratory and numerical techniques to investigate turbulent flows, useful for the research and technical community also involved in the energy field (often non-specialist of turbulent flow investigations), highlighting the advantages and disadvantages of the main techniques, as well as their main fields of application, and also to highlight the trends of the above mentioned methodologies via bibliometric analysis. In this way, the reader can select the proper technique for the specific case of interest and use the quoted bibliography as a more detailed guide. As a consequence of this target, a limitation of this review is that the deepening of the single techniques is not provided. Moreover, even though the experimental and numerical techniques presented in this review are virtually applicable to any type of turbulent flow, given their variety in the very broad field of energy research, the examples presented and discussed in this work will be limited to single-phase subsonic flows of Newtonian fluids. The main result from the bibliometric analysis shows that, as of 2021, a 3:1 ratio of numerical simulations over laboratory experiments emerges from the analysis, which clearly shows a projected dominant trend of the former technique in the field of turbulence. Nonetheless, the main result from the discussion of advantages and disadvantages of both the techniques confirms that each of them has peculiar strengths and weaknesses and that both approaches are still indispensable, with different but complementary purposes

Bird-Borne Samplers for Monitoring CO2 and Atmospheric Physical Parameters

Air quality monitoring in cities is significant for both human health and environment. Here, an innovative miniaturized active air sampler wearable by free-flying birds is presented. The device integrates a GPS logger and atmospheric calibrated sensors allowing for high spatiotemporal resolution measurements of carbon dioxide (CO2) concentration, barometric pressure, air temperature, and relative humidity. A field campaign, carried out from January to June 2021, involved the repeated release of homing pigeons (Columba livia) from downtown Rome (Italy), to sample the air on their way back to the loft, located in a rural area out of the city. The measurements suggest the importance of green urban areas in decreasing CO2 levels. Moreover, a positive relation between CO2 levels, relative humidity, and air temperature was revealed. In contrast, a negative relation with distance from the point of release, month, and time of day was found. Flight speed and the altitude of flight were related to rising CO2 levels. The easy use of such devices paves the way for the application of miniaturized air samplers to other synanthropic species (i.e., gulls), making birds convenient biomonitors for the urban environment. © 2022 by the authors

Estimation of extreme L1L^1-multivariate expectiles with functional covariates

The present article is devoted to the semi-parametric estimation of multivariate expectiles for extreme levels. The considered multivariate risk measures also include the possible conditioning with respect to a functional covariate, belonging to an infinite-dimensional space. By using the first order optimality condition, we interpret these expectiles as solutions of a multidimensional nonlinear optimum problem. Then the inference is based on a minimization algorithm of gradient descent type, coupled with consistent kernel estimations of our key statistical quantities such as conditional quantiles, conditional tail index and conditional tail dependence functions. The method is valid for equivalently heavy-tailed marginals and under a multivariate regular variation condition on the underlying unknown random vector with arbitrary dependence structure. Our main result establishes the consistency in probability of the optimum approximated solution vectors with a speed rate. This allows us to estimate the global computational cost of the whole procedure according to the data sample size.Comment: 21 page

A local statistic for the spatial extent of extreme threshold exceedances

We introduce the extremal range, a local statistic for studying the spatial extent of extreme events in random fields on $\mathbb{R}^2$. Conditioned on exceedance of a high threshold at a location $s$, the extremal range at $s$ is the random variable defined as the smallest distance from $s$ to a location where there is a non-exceedance. We leverage tools from excursion-set theory to study distributional properties of the extremal range, propose parametric models and predict the median extremal range at extreme threshold levels. The extremal range captures the rate at which the spatial extent of conditional extreme events scales for increasingly high thresholds, and we relate its distributional properties with the bivariate tail dependence coefficient and the extremal index of time series in classical Extreme-Value Theory. Consistent estimation of the distribution function of the extremal range for stationary random fields is proven. For non-stationary random fields, we implement generalized additive median regression to predict extremal-range maps at very high threshold levels. An application to two large daily temperature datasets, namely reanalyses and climate-model simulations for France, highlights decreasing extremal dependence for increasing threshold levels and reveals strong differences in joint tail decay rates between reanalyses and simulations.Comment: 32 pages, 5 figure

On the identification and characterization of outdoor thermo-hygrometric stress events

Human thermal sensations are not controlled merely by the ambient temperature, but also by other biometeorological variables and personal factors. Therefore, thermo-hygrometric stress events need to be identified and monitored in addition to heat waves. The purpose of the present article is proposing a method for detection and characterization of thermo-hygrometric stress events, based on the rearrangement of heat waves indices and on new quantities. The Mediterranean Outdoor Thermal Comfort Index (MOCI) is used as a reference variable instead of the air temperature. The method is applied to Milan (Italy) for the 2022 summer, which: i) is the hottest in the period 1991–2020 with a temperature anomaly of 3.17 ◦C and ii) presents higher minimum temperatures (1.5 times higher) than those of the control period. The analysis of daytime values of MOCI demonstrates a cumulative MOCI higher than zero only in 2022. Hence, the lower fraction of data in the cold range determines a significant increase in the cumulative MOCI. The metrics on severe MOCI events in 2022 confirm the key-role of extreme temperatures. The proposed method is effective and, in this case, reveals the relevance of the cumulative thermal and thermo-hygrometric loads also in the absence of critical heating conditions

Generalized immersion and nonlinear robust output regulation problem

summary:The problem of output regulation of the system affected by unknown constant parameters is considered here. Under certain assumptions, such a problem is known to be solvable using error feedback via the so-called immersion to an observable linear system with outputs. Nevertheless, for many interesting cases this kind of finite dimensional immersion is difficult or even impossible to find. In order to achieve constructive procedures for wider classes, this paper investigates a more general type of immersion. Such a generalized immersion enables to solve robust output regulation problem via dynamic feedback compensator using error and exosystem state measurement. When the exosystem states are not completely measurable, a modified observed-based generalized immersion is then presented. The main result obtained here is that under reasonable assumptions both the full and partial exosystem measurement problems are equivalently solvable. Examples together with computer simulation are included to clarify the suggested approach

Interactions of mitochondrial and skeletal muscle biology in mitochondrial myopathy

\ua9 2023 The Author(s). Mitochondrial dysfunction in skeletal muscle fibres occurs with both healthy aging and a range of neuromuscular diseases. The impact of mitochondrial dysfunction in skeletal muscle and the way muscle fibres adapt to this dysfunction is important to understand disease mechanisms and to develop therapeutic interventions. Furthermore, interactions between mitochondrial dysfunction and skeletal muscle biology, in mitochondrial myopathy, likely have important implications for normal muscle function and physiology. In this review, we will try to give an overview of what is known to date about these interactions including metabolic remodelling, mitochondrial morphology, mitochondrial turnover, cellular processes and muscle cell structure and function. Each of these topics is at a different stage of understanding, with some being well researched and understood, and others in their infancy. Furthermore, some of what we know comes from disease models. Whilst some findings are confirmed in humans, where this is not yet the case, we must be cautious in interpreting findings in the context of human muscle and disease. Here, our goal is to discuss what is known, highlight what is unknown and give a perspective on the future direction of research in this area