521 research outputs found

    European versus Domestic Politics: Media Negativity during the 2019 European Elections Campaign in Italy

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    This article aims at understanding to what extent European issues and actors are covered through a negative tone within the news coverage of the 2019 EP election campaign in Italy. We rely on an original dataset based on content analysis of the 50 days prior to the 2019 EP elections in four mainstream newspapers (n=3,943) and four mainstream TV newscasts (n=1,873). Our findings show that the media negativity is primarily associated with domestic politics, while all in all European politics is covered using a less negative tone. This general picture is the results of two differentiated patterns: newspapers are less negative towards both EU politics and Eu and foreign political actors, while TV news are more negative towards Eu and foreign political actors

    Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter

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    [EN] This paper proposes a methodology for examining the presence of Keynesian ideas in the economic debate. To this aim we use Twitter as a source of data to monitor the debate in real time. We quantify the presence of Keynesian and anti-Keynesian thought in tweets about the economy and we qualify the emotional tone of these tweets. Our preliminary results show that the 20 per-cent of total English tweets about #economy contain words related to Keynes while about 8 per- cent contain words referring to anti-Keynesian policies. The monthly analysis of the tweets shows a certain heterogeneity. The distribution of Keynes-related tweets is much more uneven than the distribution of anti-keynesian tweets. Our evidence suggests that the methodology we applied to understand how much of the Keynesian thought is still around in the economic debate can be promising. The next step will be to focus on georeferenced tweets to detect heterogenity across countries and to understand how country-level trends reflect the economy cycle. This study still has some limitations that will be faced in future research such as the classification of topics and the focus on English texts for the moment.Perfetto, C.; Rancan, A.; Resce, G. (2023). Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter. Editorial Universitat Politècnica de València. 129-137. https://doi.org/10.4995/CARMA2023.2023.1643212913

    Efficiency evaluation of food waste materials for the removal of metals and metalloids from complex multi-element solutions

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    Recent studies have shown the potential of food waste materials as low cost adsorbents for the removal of heavy metals and toxic elements from wastewater. However, the adsorption experiments have been performed in heterogeneous conditions, consequently it is difficult to compare the efficiency of the individual adsorbents. In this study, the adsorption capacities of 12 food waste materials were evaluated by comparing the adsorbents' efficiency for the removal of 23 elements from complex multi-element solutions, maintaining homogeneous experimental conditions. The examined materials resulted to be extremely efficient for the adsorption of many elements from synthetic multi-element solutions as well as from a heavy metal wastewater. The 12 adsorbent surfaces were analyzed by Fourier transform infrared spectroscopy and showed different types and amounts of functional groups, which demonstrated to act as adsorption active sites for various elements. By multivariate statistical computations of the obtained data, the 12 food waste materials were grouped in five clusters characterized by different elements' removal efficiency which resulted to be in correlation with the specific adsorbents' chemical structures. Banana peel, watermelon peel and grape waste resulted the least selective and the most efficient food waste materials for the removal of most of the elements

    The contribution of pattern recognition of seismic and morphostructural data to seismic hazard assessment

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    The reliable statistical characterization of the spatial and temporal properties of large earthquakes occurrence is one of the most debated issues in seismic hazard assessment, due to the unavoidably limited observations from past events. We show that pattern recognition techniques, which are designed in a formal and testable way, may provide significant space-time constraints about impending strong earthquakes. This information, when combined with physically sound methods for ground shaking computation, like the neo-deterministic approach (NDSHA), may produce effectively preventive seismic hazard maps. Pattern recognition analysis of morphostructural data provide quantitative and systematic criteria for identifying the areas prone to the largest events, taking into account a wide set of possible geophysical and geological data, whilst the formal identification of precursory seismicity patterns (by means of CN and M8S algorithms), duly validated by prospective testing, provides useful constraints about impending strong earthquakes at the intermediate space-time scale. According to a multi-scale approach, the information about the areas where a strong earthquake is likely to occur can be effectively integrated with different observations (e.g. geodetic and satellite data), including regional scale modeling of the stress field variations and of the seismic ground shaking, so as to identify a set of priority areas for detailed investigations of short-term precursors at local scale and for microzonation studies. Results from the pattern recognition of earthquake prone areas (M>=5.0) in the Po plain (Northern Italy), as well as from prospective testing and validation of the time-dependent NDSHA scenarios are presented.Comment: 33 pages, 7 Figures, 9 Tables. Submitted to Bollettino di Geofisica Teorica e Applicata (BGTA

    Gender differences in reaching top roles in banking: a cross-sectional study performed by bankers work in province of Pisa

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    The financial industry is a pivot of the economy and plays an important social role. Goal of this study was to analyze factors associated with the framing level in banking in the province of Pisa. We collected data about age, gender, framing level, workplace and type of bank for bankers in Pisa through trade unionists. We collected data on 2018 workers and we found significant associations between framing level and aged over 40 years (OR = 4.5; 95% CI: 2.9-6.9), workplace in Pisa (OR = 0.30; 95% CI: 0.20-0.44) and male gender (OR = 2.89; 95% CI: 1.98-4.21). The first two factors are explainable with organizational characteristics. In fact for becoming manager you already have to work a number of year and in cities rather than in the surrounding municipalities, consistent with the size of bank. However, the third factor, already known in the literature in other work areas, requires further studies for explaining causes and helping to implement actions to reduce the gender gap

    The use of virtual environments for survey spatial ability evaluation in topographical disorientation

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    Due to their interactivity and to the sense of presence they afford, virtual environments constitute an interesting opportunity to study spatial cognition. In accordance with this perspective, we aimed to introduce a spatial test in virtual simulation in order to investigate the survey spatial ability in patients with topographical disorientation. To do this, we used the “planning in advance task” in a virtual environment that constitutes an effective procedure to experimentally evaluate survey maps. With this procedure we present the single case of a woman, with a right medial temporal lobe lesion, who shows a selective impairment in the acquisition of new spatial relationships. The patient’s performance in “planning in advance task” was compared with that of a control group made up of 40 female subjects matched for age and education. Results show how the patient revealed a significantly lower spatial performance when compared to the control group, demonstrating an inability to solve survey-type spatial tasks in complex virtual environments

    ER+-derived breast cancer stem cells reveal a high expression of the serpin protease inhibitor PI-9.

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    Introduction: Breast cancers (BC) are the major cause of death in women. More than 70% of BCs express high levels of estrogen receptor-α (ERα) and are sustained for their growth by the hormone. Estrogens seem to protect BC cells from apoptosis mediated by immunosurveillance associated with cytotoxic T lymphocytes and NK cells granzyme B release. However, the production of granzyme B inhibitor PI-9 by tumor cells causes a short-circuit in immunosurveillance’s signalling. Although it has been shown the role of PI-9 in BC cells, its presence has not been investigated in tumor stem cells so far. Methods: Cell viability was evaluated by MTT, cell cycle by propidium iodide staining; mRNA and protein levels by qPCR and western blotting. Tumorspheres from ERα+BC MCF7 cells were isolated in ultra-low attachment conditions. The higher expression of stemness markers (Nanog, Oct3/4 and Sox2) was found in tertiary tumorspheres which were used in our study. Results: Low doses (10 nM-10 μM) of 17-β estradiol consistently increased the number of MCF7 cells more than tumorspheres, while higher doses (50-100 μM) reduced cell number as a consequence of G2/M cell cycle arrest. The analysis of ERα disclosed the presence of three different isoforms (66, 46 and 36 kDa) in MCF7 cells. In contrast, tumorspheres exhibited an increase in ERα36, which lacks transcriptional activity, while the level of ERα66 was undetectable. Then, we analyzed the level of PI-9, which is transcriptionally regulated by ERα66. Surprisingly, we found that tertiary tumorspheres, express higher levels of both PI-9 protein and mRNA than MCF7 cells. Conclusions: Our data provided evidence that the high level of PI-9 in ER+ tertiary tumorspheres could supply a selective advantage to BC stem cells by interfering with immune-surveillance systems. Ongoing studies aim to elucidate the relationship between the levels of different ERα isoforms and PI-9 high expression in BC-stem cells
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