2,089 research outputs found

    The Role of Emotional Intelligence on Psychological Adjustment and Peer Victimization in a Sample of Spanish Adolescents

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    In the last decades, interest in the study of the negative consequences of bullying for the victims has increased. Victims are often known to show emotional adjustment issues, such as negative self-concept and low life satisfaction. Moreover, some studies have observed important associations between self-concept and life satisfaction, in which a positive self-concept is related to high levels of life satisfaction. Other studies have pointed out the importance of emotional intelligence (EI), as a regulatory and protective factor against the negative impact of victimization on adjustment in adolescents. The main objective of this work was to analyze the mediating effect of self-concept on life satisfaction and the moderated mediation effect of EI on self-concept and life satisfaction in the context of peer victimization. The participants in the study were 1,318 Spanish students of both sexes and aged between 11 and 18 (M = 13.8, SD = 1.32) years, from four compulsory secondary education centers. The results indicated that, on the one hand, self-concept mediated the relationship between victimization and life satisfaction. On the other hand, EI was not only positively associated with self-concept, but it also significantly moderated the negative influence of victimization on self-concept. EI may also indirectly moderate the relationship between victimization and life satisfaction through the self-concept. These data show the importance of EI as a possible protective and moderating factor of the negative effect of bullying on emotional adjustment, which is interesting for the design of future prevention and intervention programs in school contexts.This research was funded by the Ministry of Economy and Competitiveness of Spain and the European Union through the European Regional Development Fund—FEDER—“One way to make Europe,” grant number PID2019-109442RB-I00, with EE as the Principal Researcher

    Optimización de los gráficos de control CUSUM-FIR mediante algoritmos genéticos

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    [ESP] Las técnicas de Control estadístico de procesos (SPC) constituyen un conjunto de herramientas orientadas a la mejora de la calidad y de la productividad ampliamente implantadas en sectores industriales. Un entorno cada vez más competitivo es el escenario propicio para el desarrollo de nuevas herramientas, o la evolución de las ya existentes, que permitan mantener a nuestras empresas en la espiral de la mejora continua de la calidad de nuestros productos, procesos y servicios ante un mercado cada vez más exigente. Las herramientas más importantes del SPC son sin duda los conocidos Gráficos de Control, utilizados para la monitorización y control de características de calidad o de proceso críticas, con el objetivo de fabricar siempre desde el principio unidades dentro de especificaciones con la menor variabilidad posible y centradas en el nominal. Los gráficos de control permiten detectar situaciones llamadas estados de “fuera de control” originadas por causas puntuales llamadas causa especiales o asignables de variabilidad que pueden provocar la aparición de “piezas” defectuosas o aunque no estén fuera de especificaciones, provocar la aparición de no uniformidad en la producción. En la actualidad el uso de gráficos de control para la monitorización de una única característica de calidad de tipo continuo se lleva acabo utilizando alguno de los gráficos disponibles: Shewhart, CUSUM, EWMA, etc. (Montgomery (2009))

    The impact and effectiveness of the general public wearing masks to reduce the spread of pandemics in the UK: a multidisciplinary comparison of single-use masks versus reusable face masks

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    During the coronavirus (COVID-19) pandemic, the UK government mandated the use of face masks in various public settings and recommended the use of reusable masks to combat shortages of medically graded single-use masks in healthcare. To assist decision-making on the choice of masks for future pandemics, where shortages may not be a contributing factor, the University College London (UCL) Plastic Waste Innovation Hub has carried out a multidisciplinary comparison between single-use and reusable masks based on their anatomy, standalone effectiveness, behavioural considerations, environmental impact and costs. Although current single-use masks have a higher standalone effectiveness against bacteria and viruses, studies show that reusable masks have adequate performance in slowing infection rates of respiratory viruses. Material flow analysis (MFA), life cycle assessment (LCA) and cost comparison show that reusable masks have a lower environmental and economic impact than single-use masks. If every person in the UK uses one single-use mask each day for a year, it will create a total of 124,000 tonnes of waste, 66,000 tonnes of which would be unrecyclable contaminated plastic waste (the masks), with the rest being the recyclable packaging typically used for transportation and distribution of masks. Using reusable masks creates >85% less waste, generates 3.5 times lower impact on climate change and incurs 3.7 times lower costs. Further behavioural research is necessary to understand the extent and current practices of mask use; and how these practices affect mask effectiveness in reducing infection rates. Wearing single-use masks may be preferred over reusable masks due to perceptions of increased hygiene and convenience. Understanding behaviour towards the regular machine-washing of reusable masks for their effective reuse is key to maximise their public health benefits and minimise environmental and economic costs

    Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

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    A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)
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