Publications by authors named "Luca Schenato"

Alluvial aquifers often exhibit highly conductive embedded formations that can act as preferential pathways for the transport of solutes. In this context, a detailed subsurface characterization becomes crucial for an effective monitoring of groundwater quality and early detection of contaminants. However, small-scale heterogeneities are seldom detected by traditional nondestructive investigations.

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We propose a method for shape sensing that employs Rayleigh-signature domain multiplexing to simultaneously probe the fibers or cores of a shape sensing setup with a single optical frequency-domain reflectometry scan. The technique enables incrementing the measurement speed by a factor equal to the number of multiplexed fibers at the expense of an increased noise floor in accordance with the Cramér-Rao lower bound. Nonetheless, we verify that the shape reconstruction performance of the proposed method is in very good agreement with that of conventional sequential core interrogation.

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Distributed optical fiber sensing is a unique technology that offers unprecedented advantages and performance, especially in those experimental fields where requirements such as high spatial resolution, the large spatial extension of the monitored area, and the harshness of the environment limit the applicability of standard sensors. In this paper, we focus on one of the scattering mechanisms, which take place in fibers, upon which distributed sensing may rely, i.e.

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Background: The ability to rapidly adapt to adverse environmental conditions represents the key of success of many pathogens and, in particular, of Mycobacterium tuberculosis. Upon exposition to heat shock, antibiotics or other sources of stress, appropriate responses in terms of genes transcription and proteins activity are activated leading part of a genetically identical bacterial population to express a different phenotype, namely to develop persistence. When the stress response network is mathematically described by an ordinary differential equations model, development of persistence in the bacterial population is associated with bistability of the model, since different emerging phenotypes are represented by different stable steady states.

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Article Synopsis
  • During the Covid-19 pandemic, deciding who should be tested for the virus can really affect how well we keep people safe and healthy.
  • The paper talks about using smart methods to choose individuals for testing, aimed at finding and stopping hidden cases of the virus.
  • Tests on a community of 10,000 people showed that this smart testing approach could help control the spread of disease while keeping the number of people confined lower than other methods.
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In this paper we explore the effect of the number of daily tests on an epidemics control policy purely based on testing and selective quarantine, and the impact of these actions depending on the time their application starts. We introduce a general model incorporating a stochastic disease evolution, a particular weighted graph representing the population, and an optimal contact tracing strategy to allocate available tests. Simulations on a community of 50'000 individuals show that the evolution of the epidemic produces a clear non-linear response to the variation of the number of tests used and to the starting time of their application.

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There is evidence that the toll of death and destruction caused by natural hazards is rising. This is often ascribed to the impact of climate change that resulted in an increased frequency of extreme meteorological events. As a consequence, it is realistic to expect that the casualties and damages caused by floods will increase in the near future.

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Article Synopsis
  • The paper addresses the challenge of collaboratively estimating Gaussian processes among multiple agents with limited data collection, computation, and communication abilities.
  • Instead of requiring all agents to share extensive measurements and compute an impractical large matrix inversion, the authors propose two suboptimal methods utilizing a smaller set of eigenfunctions from the Karhunen-Loève expansion to simplify computations and communication.
  • The study offers probabilistic bounds for estimation accuracy and introduces new distributed strategies for optimizing regularization parameters, demonstrating their effectiveness through tests on both synthetic and real-world data.
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A distributed optical fibre sensing system is used to measure landslide-induced strains on an optical fibre buried in a large scale physical model of a slope. The fibre sensing cable is deployed at the predefined failure surface and interrogated by means of optical frequency domain reflectometry. The strain evolution is measured with centimetre spatial resolution until the occurrence of the slope failure.

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This paper considers the classification problem using support vector (SV) machines and investigates how to maximally reduce the size of the training set without losing information. Under separable data set assumptions, we derive the exact conditions stating which observations can be discarded without diminishing the overall information content. For this purpose, we introduce the concept of potential SVs, i.

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The modal distribution of a novel elliptical hollow optical fiber is experimentally and numerically characterized. The fiber has a central elliptical air hole surrounded by a germanosilicate lanceolate ring core. Experiments reveal that the fiber behaves like a dual core waveguide and it is found that the differential group delay of each core decreases with wavelength with a PMD coefficient slope of ~10(-2) ps/m/THz.

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This paper gives a detailed technical overview of some of the activities carried out in the context of the "Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)" project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide.

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We present a novel reflectometric technique for the measurement of orientation and modulus of the linear birefringence vector in single-mode optical fibers. The technique provides information also on circular birefringence, although this component, if present, appears as a rotation of the linear birefringence. A detailed theoretical analysis is reported and validated by experimental results.

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We show that the polarization mode dispersion of a constantly spun, single-mode fiber is strongly influenced by the autocorrelation function of its birefringence. In particular, under probable conditions, the mean square differential group delay of the spun fiber may even be higher than the delay that the same fiber would have if it were not spun.

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A simplified phenomenological model for the description of randomly birefringent, strongly spun fibers is proposed. It is shown that the spinning, besides causing an apparent reduction of the linear random birefringence, may also induce an apparent deterministic circular birefringence.

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