681 research outputs found

    Shock waves in thermal lensing

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    We review experimental investigation on spatial shock waves formed by the self-defocusing action of a laser beam propagation in a disordered thermal nonlinear media.Comment: 9 pages, 12 figure

    Shock waves in disordered media

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    We experimentally investigate the interplay between spatial shock waves and the degree of disorder during nonlinear optical propagation in a thermal defocusing medium. We characterize the way the shock point is affected by the amount of disorder and scales with wave amplitude. Evidence for the existence of a phase diagram in terms of nonlinearity and amount of randomness is reported. The results are in quantitative agreement with a theoretical approach based on the hydrodynamic approximation.Comment: 4 pages, 5 figure

    Nonlinear Gamow vectors in nonlocal optical propagation

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    Shock waves dominate in a wide variety of fields in physics dealing with nonlinear phenomena, nevertheless the description of their evolution is not resolved for the entire dynamics. Here we propose an analytical method based on Gamow vectors, which belong to irreversible quantum mechanics. We theoretically and experimentally show the appearance of these decaying states during shock evolution allowing to describe the whole wave propagation. These results open new ways to the control of extreme nonlinear regimes such as supercontinuum generation or in the analogies of fundamental physical theories

    The secondary KIT mutation p.Ala510Val in a cutaneous mast cell tumour carrying the activating mutation p.Asn508Ile confers resistance to masitinib in dogs

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    Background: Gain-of-function mutations in KIT are driver events of oncogenesis in mast cell tumours (MCTs) affecting companion animals. Somatic mutations of KIT determine the constitutive activation of the tyrosine kinase receptor leading to a worse prognosis and a shorter survival time than MCTs harbouring wild-type KIT. However, canine MCTs carrying KIT somatic mutations generally respond well to tyrosine kinase inhibitors; hence their presence represents a predictor of treatment effectiveness, and its detection allows implementing a stratified medical approach. Despite this, veterinary oncologists experience treatment failures, even with targeted therapies whose cause cannot be elucidated. The first case of an MCT-affected dog caused by a secondary mutation in the tyrosine kinase domain responsible for resistance has recently been reported. The knowledge of this and all the other mutations responsible for resistance would allow the effective bedside implementation of a deeply stratified and more effective medical approach. Case presentation: The second case of a canine MCT carrying a different resistance mutation is herein described. The case was characterised by aggressive behaviour and early metastasis unresponsive to both vinblastine- and masitinib-based treatments. Molecular profiling of the tumoural masses revealed two different mutations; other than the already known activating mutation p.Asn508Ile in KIT exon 9, which is tyrosine kinase inhibitor-sensitive, a nearly adjacent secondary missense mutation, p.Ala510Val, which had never before been described, was detected. In vitro transfection experiments showed that the secondary mutation did not cause the constitutive activation by itself but played a role in conferring resistance to masitinib. Conclusions: This study highlighted the importance of the accurate molecular profiling of an MCT in order to improve understanding of the molecular mechanism underlying tumourigenesis and reveal chemoresistance in MCTs for more effective therapies. The detection of the somatic mutations responsible for resistance should be included in the molecular screening of MCTs, and a systematic analysis of all the cases characterised by unexpected refractoriness to therapies should be investigated in depth at both the genetic and the phenotypic level

    Lithium-ion batteries towards circular economy: A literature review of opportunities and issues of recycling treatments

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    Nowadays, Lithium-ion batteries are widely used in advanced technological devices and Electric and Hybrid Vehicles, due to their high energy density for weight, reduced memory effect and significant number of supported charging/discharging cycles. As a consequence, the production and the use of Lithium-ion batteries will continuously increase in the near future, focusing the global attention on their End-of-Life management. Unfortunately, wasted Lithium-ion batteries treatments are still under development, far from the optimization of recycling processes and technologies, and currently recycling represents the only alternative for the social, economic and environmental sustainability of this market, able to minimize toxicity of End-of-Life products, to create a monetary gain and to lead to the independence from foreign resources or critical materials. This paper analyses the current alternatives for the recycling of Lithium-ion batteries, specifically focusing on available procedures for batteries securing and discharging, mechanical pre-treatments and materials recovery processes (i.e. pyro- and hydrometallurgical), and it highlights the pros and cons of treatments in terms of energy consumption, recovery efficiency and safety issues. Target metals (e.g. Cobalt, Nickel and Lithium) are listed and prioritized, and the economic advantage deriving by the material recovery is outlined. An in-depth literature review was conducted, analysing the existing industrial processes, to show the on-going technological solutions proposed by research projects and industrial developments, comparing best results and open issues and criticalities

    Numerical ragweed pollen forecasts using different source maps: a comparison for France.

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    One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably

    Modelling RT-qPCR cycle-threshold using digital PCR data for implementing SARS-CoV-2 viral load studies

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    Objectives To exploit the features of digital PCR for implementing SARS-CoV-2 observational studies by reliably including the viral load factor expressed as copies/μL. Methods A small cohort of 51 Covid-19 positive samples was assessed by both RT-qPCR and digital PCR assays. A linear regression model was built using a training subset, and its accuracy was assessed in the remaining evaluation subset. The model was then used to convert the stored cycle threshold values of a large dataset of 6208 diagnostic samples into copies/μL of SARSCoV- 2. The calculated viral load was used for a single cohort retrospective study. Finally, the cohort was randomly divided into a training set (n = 3095) and an evaluation set (n = 3113) to establish a logistic regression model for predicting case-fatality and to assess its accuracy. Results The model for converting the Ct values into copies/μL was suitably accurate. The calculated viral load over time in the cohort of Covid-19 positive samples showed very low viral loads during the summer inter-epidemic waves in Italy. The calculated viral load along with gender and age allowed building a predictive model of case-fatality probability which showed high specificity (99.0%) and low sensitivity (21.7%) at the optimal threshold which varied by modifying the threshold (i.e. 75% sensitivity and 83.7% specificity). Alternative models including categorised cVL or raw cycle thresholds obtained by the same diagnostic method also gave the same performance. Conclusion The modelling of the cycle threshold values using digital PCR had the potential of fostering studies addressing issues regarding Sars-CoV-2; furthermore, it may allow setting up predictive tools capable of early identifying those patients at high risk of case-fatality already at diagnosis, irrespective of the diagnostic RT-qPCR platform in use. Depending upon the epidemiological situation, public health authority policies/aims, the resources available and the thresholds used, adequate sensitivity could be achieved with acceptable low specificity
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