687 research outputs found

    Graphene derived lanthanum carbide targets for the SPES ISOL facility

    No full text
    Graphene derived lanthanum carbide targets for the SPES ISOL facility By:Corradetti, S (Corradetti, S.)[ 1 ] ; Carturan, SM (Carturan, S. M.)[ 1,2 ] ; Andrighetto, A (Andrighetto, A.)[ 1 ] ; Mariotto, G (Mariotto, G.)[ 3 ] ; Giarola, M (Giarola, M.)[ 3 ] ; Fabrizi, A (Fabrizi, A.)[ 4 ] ; Maddalena, A (Maddalena, A.)[ 5 ] ; Biasetto, L (Biasetto, L.)[ 1,4 ] CERAMICS INTERNATIONAL Volume: 43 Issue: 14 Pages: 10824-10831 DOI: 10.1016/j.ceramint.2017.05.106 Published: OCT 1 2017 View Journal Impact Abstract Lanthanum carbide based targets were produced as benchmark tests before the production of radioactive uranium carbide targets. Carbides possessing excess carbon and porosity seem to be the best candidates as target for the production of exotic beams in the SPES-ISOL facility. In addition, the capability of tailoring properties such as grains size and pores size represents a step ahead to improve the ions release efficiency. In this work, multilayered graphene was used as source of carbon for the production of LaC and the main physical properties of the produced targets were compared to standard LaCx produced using micrometric graphite. The main output of the work consisted in the reduced total porosity (28.8 vol% vs 47.8 vol%) and increased shrinkage (20.4 vol% vs 5.8 vol%) of the LaCx-Graphene samples compared to LaCx-Graphite ones. This result showed how graphene can be successfully employed as sintering aid for the sintering of carbides. Further studies are ongoing with UO2 as starting reagent for carburization within the project AUL-2013-16-176 "Study of the use of graphene as source of carbon for Uranium Carbide-Graphene nanocomposites production" now under conclusion at the European Commission DG Joint Research Centre - JRC

    Being Treated as an Instrument: Consequences of Instrumental Treatment and Self-Objectification on Task Engagement and Performance

    No full text
    Workers’ instrumental treatment is commonly seen as a strategic way to reach organizational goals. Drawing on relevant recent literature, this paper sought to show experimentally that instrumental treatment is instead associated with negative outcomes for the individual and the organization. We sought to demonstrate that treating people as instruments would lead them to self-objectify–to self-perceive as objects rather than human beings–which would result in them being less engaged in a given task, thus undermining their performance. Study 1 was designed to provide a first test of our hypotheses by manipulating the instrumental (vs. non-instrumental) treatment enacted by an experimenter toward naïve participants (N = 85) during the performance of a cognitive task. Study 2 consisted in a simulated online work activity in which participants (N = 147) were asked to play the role of a proofreader for a fictitious newspaper, while being treated in an instrumental (vs. non-instrumental) way by the editorial staff. The results provided convergent evidence about the hypothesized process: being instrumentally (vs. non-instrumentally) treated leads people to self-objectify (i.e., to self-perceive as more instrument-like than human) and, in turn, their engagement with the task and performance are undermined. Implications for organizational and social psychology research are discussed

    Grand Theft Auto is a “Sandbox” Game, but There are Weapons, Criminals, and Prostitutes in the Sandbox: Response to Ferguson and Donnellan (2017)

    No full text
    In this issue, (Ferguson, C. J., & Donnellan, B. D., Journal of Youth and and Adolescence, published online 21 June 2017) criticize one of our studies (Gabbiadini, A., Riva, P., Andrighetto, L., Volpato, C., & Bushman, B. J., PLoS ONE, 11: 1-14, 2016) that found violent sexist video games can reduce empathy for female violence victims in male players who identify with violent male game characters, and do so by increasing masculine beliefs. Their main criticism is a "straw person" argument built on a claim that we never made (i.e., a direct effect of sexist-violent video games on empathy). They also made several other criticisms of our article. We appreciate the opportunity to respond to their criticisms in this article. We also point out some flaws in their reanalysis. Despite their criticisms, the core contributions of our original article remain intact

    An easy decision-making graphic tool to improve herd level milk yield in a local scale dairy farming system

    No full text
    Several features prevent dairy farms from reaching their full potential milk yield levels. A plurality of methods are available to analyse a farm's yield gap, but in practice, farmers rarely use them to understand their main constraints to production. We propose a simple and graphical approach to tune the limiting (feed-related) or reducing (management-related) factors to evaluate the likelihood of being a high-yielding farm. We gathered data from 32 farms within a local-scale dairy system in Northern Italy. Data regarded milk yield (MY), dry matter intake (DMI), feeding ration's homogeneity index (Hi), feed sorting (Si) index, ration's geometric mean particle length (GMPL), ration digestibility, income over feed cost (IOFC) and MY summer-winter ratio (SWR). Farms were classified according to their MY levels into high (H) and low or medium (L + M), with a 36.7 kg x cow(-1) day(-1) threshold. At an ANOVA model for MY class, H farms resulted in higher IOFC (p < 0.001), GMPL (p = 0.046), DMI (p = 0.006), digestible DM (DDM, p = 0.013), digestible crude protein (DCP, p = 0.011), digestible starch (Dstarch, p = 0.001), and feed efficiency (FE, p = 0.003). At a logistic AIC stepwise regression, the GMPL (odds = 6.528, 95% CI = 1.11-64.2) and DMI (odds = 3.889, 95% CI = 1.43-16.5) favoured farms being classified in the H production class. The nomogram was used to calculate a confusion matrix, achieving an overall accuracy of 0.70, demonstrating its ability to transform predictive models into a graphical, realisable tool

    Does status affect intergroup perceptions of humanity?

    No full text
    Across three studies, we examined whether ingroup status may affect intergroup perceptions of humanity. In Studies 1 and 2, we considered real groups: Northern versus Southern Italians; in Study 3, we manipulated the socioeconomic status of two minimal groups. In all studies, members of higher status groups perceived the ingroup as more human than the outgroup, while members of lower status groups did not assign a privileged human status to the ingroup. Such findings were obtained using different implicit techniques: the Implicit Association Test (IAT) and the Go/No-go Association Task (GNAT). Further, results suggest that the different perceptions of humanity may depend on the stereotypic traits generally ascribed to higher and lower status groups. The implications of results for infrahumanization research are discussed. © The Author(s) 2012

    Herd Level Yield Gap Analysis in a Local Scale Dairy Farming System: A Practical Approach to Discriminate between Nutritional and Other Constraining Factors

    No full text
    This study performed a yield gap analysis to help farmers understand whether their constraints were mainly due to nutritional factors or management and health issues. Twenty-nine farms were periodically evaluated. Milk yield (MY), dry matter intake (DMI), total mixed ration (TMR) composition and homogeneity index (HI), TMR digestibility, income over feed cost (IOFC), and MY summer–winter ratio (SWR) were collected. Farms were divided and compared according to the average annual MY: Low (L), Medium (M) and High (H), characterised by 36.7 kg/head/day. An ANOVA mixed model and a stepwise regression to assess the relationship between nutritional variables and MY were run. H farms showed higher IOFC (p < 0.001), DMI (p = 0.006), DDM (p < 0.001), digestible crude protein (DCP, p = 0.019), HI (p = 0.09), SWR (p = 0.041) and lower HI coefficient of variation (p = 0.04). The conversion of DDM into milk was higher in H and M farms. Stepwise regression for MY selected DDM and CP (R2 = 0.716, p < 0.05). M farms were mainly constrained by nutritional factors, whereas L farms were also affected by other factors such as those related to management and health
    corecore