1,485 research outputs found

    Self-propagating reactions for environmental protection: Treatment of wastes containing asbestos

    Get PDF
    A thermochemical process based on the occurrence of self-propagating reactions that is able to convert asbestos fibers into harmless, nonfibrous species is proposed. Specifically, a mixture consisting of a waste (containing about 85 wt % of chrysotile), ferric oxide, and magnesium is able, once locally ignited by a thermal source, to generate a self-propagating reaction that travels through the mixture without requiring additional energy. The process is accompanied by a dramatic change in the material from both the chemical and microstructural points of view. In addition, front velocity and maximum combustion temperature decrease as the amount of waste in the starting mixture increases, with the self-propagating character being maintained if the waste content is equal to or below 60 wt %. It is also observed that, when nonasbestos (nontoxic) materials, i.e., sepiolite and glass fibers, are used instead of the hazardous waste, the front velocity, combustion temperature, propagation limits, and apparent activation energies are found to be very similar to those observed in the case of asbestos

    Mitigating Sensor and Acquisition Method-Dependence of Fingerprint Presentation Attack Detection Systems by Exploiting Data from Multiple Devices

    Get PDF
    The problem of interoperability is still open in fingerprint presentation attack detection (PAD) systems. This involves costs for designers and manufacturers who intend to change sensors of personal recognition systems or design multi-sensor systems, because they need to obtain sensor-specific spoofs and retrain the system. The solutions proposed in the state of the art to mitigate the problem still require data from the target sensor and are therefore not exempt from the problem of obtaining new data. In this paper, we provide insights for the design of PAD systems thanks to an overview of an interoperability analysis on modern systems: hand-crafted, deep-learning-based, and hybrid. We investigated realistic use cases to determine the pros and cons of training with data from multiple sensors compared to training with single sensor data, and drafted the main guidelines to follow for deciding the most convenient PAD design technique depending on the intended use of the fingerprint identification/authentication system

    Total Synthesis of Aspidosperma and Strychnos Alkaloids through Indole Dearomatization

    Get PDF
    Monoterpenoid indole alkaloids are the major class of tryptamine-derived alkaloids found in nature. Together with their structural complexity, this has attracted great interest from synthetic organic chemists. In this Review, the syntheses of Aspidosperma and Strychnos alkaloids through dearomatization of indoles are discussed

    Fingerprint recognition with embedded presentation attacks detection: are we ready?

    Get PDF
    The diffusion of fingerprint verification systems for security applications makes it urgent to investigate the embedding of software-based presentation attack detection algorithms (PAD) into such systems. Companies and institutions need to know whether such integration would make the system more “secure” and whether the technology available is ready, and, if so, at what operational working conditions. Despite significant improvements, especially by adopting deep learning approaches to fingerprint PAD, current research did not state much about their effectiveness when embedded in fingerprint verification systems. We believe that the lack of works is explained by the lack of instruments to investigate the problem, that is, modeling the cause-effect relationships when two non-zero error-free systems work together. Accordingly, this paper explores the fusion of PAD into verification systems by proposing a novel investigation instrument: a performance simulator based on the probabilistic modeling of the relationships among the Receiver Operating Characteristics (ROC) of the two individual systems when PAD and verification stages are implemented sequentially. As a matter of fact, this is the most straightforward, flexible, and widespread approach. We carry out simulations on the PAD algorithms’ ROCs submitted to the most recent editions of LivDet (2017-2019), the state-of-the-art NIST Bozorth3, and the top-level Veryfinger 12 matchers. Reported experiments explore significant scenarios to get the conditions under which fingerprint matching with embedded PAD can improve, rather than degrade, the overall personal verification performance

    Association between C. albicans and leukoplakia and its treatment with Photodynamic Therapy: a review of the literature and a case report

    Get PDF
    Objective: This paper deals with oral leukoplakia, a potential oral malignant disorder that often increases in malignancy due to an associated infection supported by the fungus Candida albicans. The work is aimed at describing this dual condition through a literature review and an unusual clinical case treated with Photodynamic Therapy. Materials and Methods: We used PubMed as a research engine in order to detect the most recent papers (2014-2023) written in English. Our main goal was to obtain more information about oral leukoplakia, its colonization by C. albicans and its rate of malignant transformation. We also searched the database in order to evaluate the efficacy of Photodynamic therapy against Candida infections. Case Presentation: The case presentation refers to a 37-year-old man with a diagnosis of tongue leukoplakia with a co-infection of C. albicans, treated with Photodynamic Therapy instead of conventional antifungal drugs. Results: The literature review was based on a total of 17939 articles, which were reduced to only 25 after setting the inclusion and exclusion criteria in several steps. Oral leukoplakia is an idiopathic condition that can be considered a precancerous lesion; its co-infection with C. albicans increases the chances of its malignant transformation. Photodynamic therapy is a new approach in terms of non-conventional therapies, and there is growing evidence that it can be used in the treatment of oral diseases, too. Conclusions: We eradicated the presence of C. albicans strains on our patient’s leukoplakia by using a mixture of photo-activated curcumin and H2O2, decreasing the chances of malignant transformation of our patient’s lesion, who is still undergoing a six-month control protocol

    A human–AI collaboration workflow for archaeological sites detection

    Get PDF
    This paper illustrates the results obtained by using pre-trained semantic segmentation deep learning models for the detection of archaeological sites within the Mesopotamian floodplains environment. The models were fine-tuned using openly available satellite imagery and vector shapes coming from a large corpus of annotations (i.e., surveyed sites). A randomized test showed that the best model reaches a detection accuracy in the neighborhood of 80%. Integrating domain expertise was crucial to define how to build the dataset and how to evaluate the predictions, since defining if a proposed mask counts as a prediction is very subjective. Furthermore, even an inaccurate prediction can be useful when put into context and interpreted by a trained archaeologist. Coming from these considerations we close the paper with a vision for a Human–AI collaboration workflow. Starting with an annotated dataset that is refined by the human expert we obtain a model whose predictions can either be combined to create a heatmap, to be overlaid on satellite and/or aerial imagery, or alternatively can be vectorized to make further analysis in a GIS software easier and automatic. In turn, the archaeologists can analyze the predictions, organize their onsite surveys, and refine the dataset with new, corrected, annotations

    Does living in previously exposed malaria or warm areas is associated with a lower risk of severe COVID-19 infection in Italy?

    Get PDF
    Incidence of Covid-19 positivity (21/2/2020-28/3/2020) in provinces of 4 Italian regions whose territory was described as previously exposed to Malaria was compared with those of other provinces of the same regions. The climate of such provinces was compared with the climate of the other provinces in some regions. Previously malarial areas show a lower risk than other provinces of the same regions: Mantua (Lombardy) RR=0.94 (CI95%0.89-0.99); Venice-Rovigo (Veneto) RR=0.61 (CI95%0.58-0.65); Ferrara-Ravenna (Emilia-Romagna) RR=0.37 (CI95%0.35-0.41); CagliariOristano-SouthSardinia (Sardinia) RR=0.25 (0.17-0.31). The maximum temperature in March 2020 in those provinces was higher in mean 1.5° for other provinces. The lower frequency of COVID-19 in the provinces previously exposed to Malaria of four Italian regions does not reveal a causal link. The phenomenon has emerged independently in all the regions investigated. People born between the 1920s and 1950s were those most exposed to malaria years ago and today are the most exposed to the severest forms of COVID-19. A warmer climate seems to be associated with a lower risk of COVID, in line with the evidence highlighted in equatorial states where a lower lethality of the virus has emerged, however this regardless of the presence of Malaria. This may suggest that climate and not Malaria is the real risk factor, though further studies need to determine the role of the association climate / COVID
    • …
    corecore