University of Lisbon

About: University of Lisbon is a education organization based out in Lisbon, Lisboa, Portugal. It is known for research contribution in the topics: Population & Context (language use). The organization has 19122 authors who have published 48503 publications receiving 1102623 citations. The organization is also known as: Universidade de Lisboa & Lisbon University.

Stress in Academic Life: Work Characteristics as Predictors of Student Well‐being and Performance

Abstract: La relation entre les caracteristiques du travail, le bien-etre des etudiants et la performance a eteevaluee a partir du modele de Karasck & Theorell ≪Travail, exigences, controle, soutien≫ (1990). Un echantillon d’etudiants portugais (N= 825) a repondu a un questionnaire comprenant des mesures du controle et des exigences du travail universitaire, du soutien des pairs, de la satisfaction relative a la vie universitaire, de l’anxiete/depression et des resultats aux examens. Il apparut, comme dans d’aures contextes de travail, que la satisfaction des etudiants pour ce qui est de la vie universitaire, ainsi que les niveaux d’anxiete/depression etaient fortement dependants de leur perception des caracteristiques du travail. Les niveaux de satisfaction ont un effet direct sur la performance et agissent sur la relation entre la maitrise du travail universitaire et la performance. The relationship between work characteristics, student well-being and performance was assessed, based upon Karasek and Theorell's (1990) Job Demands–Control–Support model. A sample of Portuguese university students (N= 825) answered a questionnaire comprising measures of academic work demands and control, peer support, satisfaction with academic life, anxiety/depression and academic performance. Results suggested that, similar to other work contexts, student satisfaction with academic life and anxiety/depression levels are strongly dependent on their perceptions of work characteristics. Levels of satisfaction have a direct impact on student performance and mediate the relationship between academic work control and performance.

A global water resources ensemble of hydrological models: The eartH2Observe Tier-1 dataset

Abstract: . The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070 .

Identification of the brightest Lyα emitters at z = 6.6: implications for the evolution of the luminosity function in the reionization era

Abstract: Using wide-field narrow-band surveys, we provide a new measurement of the z = 6.6 Lymanα emitter (LAE) luminosity function (LF), which constraints the bright end for the first time. We use a combination of archival narrow-band NB921 data in UDS and new NB921 measurements in SA22 and COSMOS/UltraVISTA, all observed with the Subaru telescope, with a total area of ~5 deg 2 . We exclude lower redshift interlopers by using broad-band optical and near-infrared photometry and also exclude three supernovae with data split over multiple epochs. Combining the UDS and COSMOS samples, we find no evolution of the bright end of the Lyα LF between z = 5.7 and 6.6, which is supported by spectroscopic follow-up, and conclude that sources with Himiko-like luminosity are not as rare as previously thought, with number densities of ~1.5 × 10 -5 Mpc -3 . Combined with our wide-field SA22 measurements, our results indicate a non-Schechter-like bright end of the LF at z = 6.6 and a different evolution of observed faint and bright LAEs, overcoming cosmic variance. This differential evolution is also seen in the spectroscopic follow-up of UV-selected galaxies and is now also confirmed for LAEs, and we argue that it may be an effect of reionization. Using a toy model, we show that such differential evolution of the LF is expected, since brighter sources are able to ionize their surroundings earlier, such that Lyα photons are able to escape. Our targets are excellent candidates for detailed follow-up studies and provide the possibility to give a unique view on the earliest stages in the formation of galaxies and reionization process.

Rapid Automatized Naming and Reading Performance: A Meta-Analysis.

Abstract: Evidence that rapid naming skill is associated with reading ability has become increasingly prevalent in recent years. However, there is considerable variation in the literature concerning the magnitude of this relationship. The objective of the present study was to provide a comprehensive analysis of the evidence on the relationship between rapid automatized naming (RAN) and reading performance. To this end, we conducted a meta-analysis of the correlational relationship between these 2 constructs to (a) determine the overall strength of the RAN–reading association and (b) identify variables that systematically moderate this relationship. A random-effects model analysis of data from 137 studies (857 effect sizes; 28,826 participants) indicated a moderate-to-strong relationship between RAN and reading performance (r = .43, I2 = 68.40). Further analyses revealed that RAN contributes to the 4 measures of reading (word reading, text reading, non-word reading, and reading comprehension), but higher coefficients emerged in favor of real word reading and text reading. RAN stimulus type and type of reading score were the factors with the greatest moderator effect on the magnitude of the RAN–reading relationship. The consistency of orthography and the subjects’ grade level were also found to impact this relationship, although the effect was contingent on reading outcome. It was less evident whether the subjects’ reading proficiency played a role in the relationship. Implications for future studies are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved)