The Role of Motivational Persistence and Resilience Over the Well-being Changes Registered in Time

The present study investigates the interaction between personal characteristics that are considered nowadays strengths used to face difficult events or transition period. A number of 200 married or living together participants completed self-reports for common goals, motivational persistence, resilience and well-being. Results show that persistence and resilience do interact with each other at an individual level but also from a family concept perspective. Moreover, maintaining apositive outlook and family spirituality do have an impact over the intensity and direction of the relationship between long term purposes pursuing and recurrence of unattained purposes and changes in well-being registered in time. Resiliency as a personal characteristic and family resilience show good psychometric qualities for this study. Although some of the results are descriptive, in-depth analyses of direction and intensity of the relationships lead the finalconclusions to suggestions for further research and implications for psychological practice

Developing Academic Persistence in the International Baccalaureate Diploma Programme: Educational Strategies, Associated Personality Traits and Outcomes

The aim of the study was to investigate the relationships between certain educational strategies and students' personality traits, on the one hand, and students' academic performance, on the other, respectively between the latter and two types of outcomes (i.e. students' academic performance and intentions to drop out of high school). These relationships were examined in two educational settings: in the Diploma Programme (DP), a two-year college-preparatory curriculum offered by the International Baccalaureate (IB), an international private educational system, and the traditional Romanian schools. A sample of IB students in 3 Eastern and Central European countries, and a comparison sample of non-IB students in Romania participated in the research. Results reveal several educational strategies and personality traits among those suggested by previous investigations that significantly sustain IB DP students’ academic persistence. Also, IB students’ academic performance and dropout intentions are influenced by these traits and educational strategies, and these effects are fully or partially mediated by academic persistence. A different pattern of associations emerged in the non-IB sample, with independent work style as the most important determinant of academic persistence, suggesting that relative to the traditional Romanian schools, the IB programme promotes a climate that better supports students in completing their education

Pathophysiology of L-dopa-induced motor and non-motor complications in Parkinson's disease

Involuntary movements, or dyskinesia, represent a debilitating complication of levodopa (L-dopa) therapy for Parkinson’s disease (PD). L-dopa-induced dyskinesia (LID) are ultimately experienced by the vast majority of patients. In addition, psychiatric conditions often manifested as compulsive behaviours, are emerging as a serious problem in the management of L-dopa therapy. The present review attempts to provide an overview of our current understanding of dyskinesia and other L-dopa-induced dysfunctions, a field that dramatically evolved in the past twenty years. In view of the extensive literature on LID, there appeared a critical need to re-frame the concepts, to highlight the most suitable models, to review the central nervous system (CNS) circuitry that may be involved, and to propose a pathophysiological framework was timely and necessary. An updated review to clarify our understanding of LID and other L-dopa-related side effects was therefore timely and necessary. This review should help in the development of novel therapeutic strategies aimed at preventing the generation of dyskinetic symptom

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation