Using a Choice Experiment to Estimate the Benefits of a Reduction of Externalities in Urban Areas with Special Focus on Electrosmog

Noise, air pollution and electromagnetic pollution (i.e. non-ionizing radiation, also called electrosmog) are typical negative local externalities in urban areas. They are side-effects of human and economic activity (e.g. road transport, telecommunication) and affect individuals’ well-being negatively without compensation. Measurements carried out in 2005 and 2006 show that in several Swiss cities the limit values of air pollution fixed in the Swiss law have often been exceeded. Moreover, in several areas of these cities also the day and night standards for the noise level were violated. Further, the increased number of mobile phone antennas in residential areas, and thus the increased intensity of radiated power, has, in recent years, aroused public concern, discussions and protests. The view of an antenna is annoying an increasing number of inhabitants. In order to solve these problems, policy-makers have to introduce new environmental instruments to improve the quality of the environment in the Swiss cities. This paper aims at giving policy-makers information on benefits generated by an improvement of local environmental quality. In two Swiss cities (Lugano and Zurich), stated choice experiment is used to estimate the benefits of a reduction of the level of the negative externalities mentioned above. Results from this choice experiment reveal that there is a positive and significant willingness to pay (WTP) for a reduction of the level of air pollution and noise to those limit values fixed by the government. In addition, this is the first study that uses a stated preference approach based on a choice experiment for the estimation of the benefit of a reduction of electrosmog.choice experiment, electrosmog, noise, air pollution

Deep Learning for Head Pose Estimation: A Survey

Head pose estimation (HPE) is an active and popular area of research. Over the years, many approaches have constantly been developed, leading to a progressive improvement in accuracy; nevertheless, head pose estimation remains an open research topic, especially in unconstrained environments. In this paper, we will review the increasing amount of available datasets and the modern methodologies used to estimate orientation, with a special attention to deep learning techniques. We will discuss the evolution of the feld by proposing a classifcation of head pose estimation methods, explaining their advantages and disadvantages, and highlighting the diferent ways deep learning techniques have been used in the context of HPE. An in-depth performance comparison and discussion is presented at the end of the work. We also highlight the most promising research directions for future investigations on the topic

Lean Startup: mindset per governare le startup

Le startup durante la loro crescita necessitano di un'organizzazione differente rispetto alla tradizionale: l'incertezza del mercato, i pochi fondi a disposizione e la non identificazione del mercato corretto potrebbero portare la startup a realizzare un prodotto di cui il mercato non necessita. Il lean startup aiuta le giovani imprese a crescere in modo corretto insegnando loro un mindset costruisci-apprendi-misura il quale porta la giovane azienda a misurarsi con il proprio utente, in questo caso con i primi utilizzatori del prodotto. Viene introdotta la figura del growth hacker la quale, applicando i principi del lean startup, sviluppa un prodotto a stretto contatto con l'utente con un approccio data-driven. Il growth hacker realizza esperimenti e misura i risultati. Se quest'ultimi sono coerenti e hanno effettivamente portato un miglioramento al prodotto, l'esperimento viene integrato nei processi della startup. L'elaborato include un report di Startup Genome che, a seguito di un'analisi effettuata si oltre 3200 startup, dimostra che una startup consistente, ovvero una startup che segue i principi del lean startup, abbia una maggior probabilità di avere successo rispetto ad una non consistente. L'elaborato si conclude con il caso studio di AffittoGiardino. La startup, applicando i principi del lean startup, è riuscita a produrre un prodotto utile per il mercato e adottata da molti innovatori del mercato. Alcuni di questi infatti, hanno rivoluzionato la loro economia reinventando il proprio giardino. AffittoGiardino è attualmente incubata nell'incubatore delle startup dell'Università di Bologna dove, giornalmente, applica il mindset del lean startup

A flexible design strategy for three-element non-uniform linear arrays

This paper illustrates a flexible design strategy for a three-element non-uniform linear array (NULA) aimed at estimating the direction of arrival (DoA) of a source of interest. Thanks to the spatial diversity resulting from non-uniform sensor spacings, satisfactory DoA estimation accuracies can be achieved by employing a very limited number of receiving elements. This makes NULA configurations particularly attractive for low-cost passive location applications. To estimate the DoA of the source of interest, we resort to the maximum likelihood estimator, and the proposed design strategy is obtained by constraining the maximum pairwise error probability to control the errors occurring due to outliers. In fact, it is well known that the accuracy of the maximum likelihood estimator is often degraded by outliers, especially when the signal-to-noise power ratio does not belong to the so-called asymptotic region. The imposed constraint allows for the defining of an admissible region in which the array should be selected. This region can be further modified to incorporate practical design constraints concerning the antenna element size and the positioning accuracy. The best admissible array is then compared to the one obtained with a conventional NULA design approach, where only antenna spacings multiple of λ/2 are considered, showing improved performance, which is also confirmed by the experimental results

Low dispersion finite volume/element discretization of the enhanced Green-Naghdi equations for wave propagation, breaking and runup on unstructured meshes

International audienceWe study a hybrid approach combining a FV and FE method to solve a fully nonlinear and weakly-dispersive depth averaged wave propagation model. The FV method is used to solve the underlying hyperbolic shallow water system, while a standard P 1 finite element method is used to solve the elliptic system associated to the dispersive correction. We study the impact of several numerical aspects: the impact of the reconstruction used in the hyperbolic phase; the representation of the FV data in the FE method used in the elliptic phase and their impact on the theoretical accuracy of the method; the well-posedness of the overall method. For the first element we proposed a systematic implementation of an iterative reconstruction providing on arbitrary meshes up to third order solutions, full second order first derivatives, as well as a consistent approximation of the second derivatives. These properties are exploited to improve the assembly of the elliptic solver, showing dramatic improvement of the finale accuracy, if the FV representation is correctly accounted for. Concerning the elliptic step, the original problem is usually better suited for an approximation in H(div) spaces. However, it has been shown that perturbed problems involving similar operators with a small Laplace perturbation are well behaved in H 1. We show, based on both heuristic and strong numerical evidence, that numerical dissipation plays a major role in stabilizing the coupled method, and not only providing convergent results, but also providing the expected convergence rates. Finally, the full mode, coupling a wave breaking closure previously developed by the authors, is thoroughly tested on standard benchmarks using unstructured grids with sizes comparable or coarser than those usually proposed in literature

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

(1) Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with still unknown etiology. Some occupational and environmental risk factors have been suggested, including long-term air pollutant exposure. We carried out a pilot case-control study in order to evaluate ALS risk due to particulate matter with a diameter of ≤10 µm (PM10) as a proxy of vehicular traffic exposure. (2) Methods: We recruited ALS patients and controls referred to the Modena Neurology ALS Care Center between 1994 and 2015. Using a geographical information system, we modeled PM10 concentrations due to traffic emissions at the geocoded residence address at the date of case diagnosis. We computed the odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model adjusted for age and sex. (3) Results: For the 132 study participants (52 cases and 80 controls), the average of annual median and maximum PM10 concentrations were 5.2 and 38.6 µg/m3, respectively. Using fixed cutpoints at 5, 10, and 20 of the annual median PM10 levels, and compared with exposure <5 µg/m3, we found no excess ALS risk at 5-10 µg/m3 (OR 0.87, 95% CI 0.39-1.96), 10-20 µg/m3 (0.94, 95% CI 0.24-3.70), and ≥20 µg/m3 (0.87, 95% CI 0.05-15.01). Based on maximum PM10 concentrations, we found a statistically unstable excess ALS risk for subjects exposed at 10-20 µg/m3 (OR 4.27, 95% CI 0.69-26.51) compared with those exposed <10 µg/m3. However, risk decreased at 20-50 µg/m3 (OR 1.49, 95% CI 0.39-5.75) and ≥50 µg/m3 (1.16, 95% CI 0.28-4.82). ALS risk in increasing tertiles of exposure showed a similar null association, while comparison between the highest and the three lowest quartiles lumped together showed little evidence for an excess risk at PM10 concentrations (OR 1.13, 95% CI 0.50-2.55). After restricting the analysis to subjects with stable residence, we found substantially similar results. (4) Conclusions: In this pilot study, we found limited evidence of an increased ALS risk due to long-term exposure at high PM10 concentration, though the high statistical imprecision of the risk estimates, due to the small sample size, particularly in some exposure categories, limited our capacity to detect small increases in risk, and further larger studies are needed to assess this relation

Salvage chemotherapy with procarbazine and fotemustine combination in the treatment of temozolomide treated recurrent glioblastoma patients

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