118 resultados para Sequential task


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This article argues that a native-speaker baseline is a neglected dimension of studies into second language (L2) performance. If we investigate how learners perform language tasks, we should distinguish what performance features are due to their processing an L2 and which are due to their performing a particular task. Having defined what we mean by “native speaker,” we present the background to a research study into task features on nonnative task performance, designed to include native-speaker data as a baseline for interpreting nonnative-speaker performance. The nonnative results, published in this journal (Tavakoli & Foster, 2008) are recapitulated and then the native-speaker results are presented and discussed in the light of them. The study is guided by the assumption that limited attentional resources impact on L2 performance and explores how narrative design features—namely complexity of storyline and tightness of narrative structure— affect complexity, fluency, accuracy, and lexical diversity in language. The results show that both native and nonnative speakers are prompted by storyline complexity to use more subordinated language, but narrative structure had different effects on native and nonnative fluency. The learners, who were based in either London or Tehran, did not differ in their performance when compared to each other, except in lexical diversity, where the learners in London were close to native-speaker levels. The implications of the results for the applicability of Levelt’s model of speaking to an L2 are discussed, as is the potential for further L2 research using native speakers as a baseline.

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The overarching aim of the research reported here was to investigate the effects of task structure and storyline complexity of oral narrative tasks on second language task performance. Participants were 60 Iranian language learners of English who performed six narrative tasks of varying degree of structure and storyline complexity in an assessment setting. A number of analytic detailed measures were employed to examine whether there were any differences in the participants’ performances elicited by the different tasks in terms of their accuracy, fluency, syntactic complexity and lexical diversity. Results of the data analysis showed that performance in the more structured tasks was more accurate and to a great extent more fluent than that in the less structured tasks. The results further revealed that syntactic complexity of L2 performance was related to the storyline complexity, i.e. more syntactic complexity was associated with narratives that had both foreground and background storylines. These findings strongly suggest that there is some unsystematic variance in the participants’ performance triggered by the different aspects of task design.

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The increasing use of drug combinations to treat disease states, such as cancer, calls for improved delivery systems that are able to deliver multiple agents. Herein, we report a series of novel Janus dendrimers with potential for use in combination therapy. Different generations (first and second) of PEG-based dendrons containing two different “model drugs”, benzyl alcohol (BA) and 3-phenylpropionic acid (PPA), were synthesized. BA and PPA were attached via two different linkers (carbonate and ester, respectively) to promote differential drug release. The four dendrons were coupled together via (3 + 2) cycloaddition chemistries to afford four Janus dendrimers, which contained varying amounts and different ratios of BA and PPA, namely, (BA)2-G1-G1-(PPA)2, (BA)4-G2-G1-(PPA)2, (BA)2-G1-G2-(PPA)4, and (BA)4-G2-G2-(PPA)4. Release studies in plasma showed that the dendrimers provided sequential release of the two model drugs, with BA being released faster than PPA from all of the dendrons. The different dendrimers allowed delivery of increasing amounts (0.15–0.30 mM) and in exact molecular ratios (1:2; 2:1; 1:2; 2:2) of the two model drug compounds. The dendrimers were noncytotoxic (100% viability at 1 mg/mL) toward human umbilical vein endothelial cells (HUVEC) and nontoxic toward red blood cells, as confirmed by hemolysis studies. These studies demonstrate that these Janus PEG-based dendrimers offer great potential for the delivery of drugs via combination therapy.

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This article reports on a detailed empirical study of the way narrative task design influences the oral performance of second-language (L2) learners. Building on previous research findings, two dimensions of narrative design were chosen for investigation: narrative complexity and inherent narrative structure. Narrative complexity refers to the presence of simultaneous storylines; in this case, we compared single-story narratives with dual-story narratives. Inherent narrative structure refers to the order of events in a narrative; we compared narratives where this was fixed to others where the events could be reordered without loss of coherence. Additionally, we explored the influence of learning context on performance by gathering data from two comparable groups of participants: 60 learners in a foreign language context in Teheran and 40 in an L2 context in London. All participants recounted two of four narratives from cartoon pictures prompts, giving a between-subjects design for narrative complexity and a within-subjects design for inherent narrative structure. The results show clearly that for both groups, L2 performance was affected by the design of the task: Syntactic complexity was supported by narrative storyline complexity and grammatical accuracy was supported by an inherently fixed narrative structure. We reason that the task of recounting simultaneous events leads learners into attempting more hypotactic language, such as subordinate clauses that follow, for example, while, although, at the same time as, etc. We reason also that a tight narrative structure allows learners to achieve greater accuracy in the L2 (within minutes of performing less accurately on a loosely structured narrative) because the tight ordering of events releases attentional resources that would otherwise be spent on finding connections between the pictures. The learning context was shown to have no effect on either accuracy or fluency but an unexpectedly clear effect on syntactic complexity and lexical diversity. The learners in London seem to have benefited from being in the target language environment by developing not more accurate grammar but a more diverse resource of English words and syntactic choices. In a companion article (Foster & Tavakoli, 2009) we compared their performance with native-speaker baseline data and see that, in terms of nativelike selection of vocabulary and phrasing, the learners in London are closing in on native-speaker norms. The study provides empirical evidence that L2 performance is affected by task design in predictable ways. It also shows that living within the target language environment, and presumably using the L2 in a host of everyday tasks outside the classroom, confers a distinct lexical advantage, not a grammatical one.

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The prime purpose of this article is to put teachers’, learners’ and research perspectives of task difficulty (TD) together and to investigate whether teachers’ and learners’ perceptions of and criteria for TD are in line with the available research on TD. A summary of three interrelated empirical studies on learner and teacher perceptions of TD is presented before the findings are discussed in light of the current models of TD. The chapter concludes by arguing that cognitive demands of a task are a signifcant factor that contributes to TD and should be considered more critically by L2 educators and SLA researchers.

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Satellite-based Synthetic Aperture Radar (SAR) has proved useful for obtaining information on flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides water level observations that can be assimilated into a hydrodynamic model to decrease forecast uncertainty. With an increasing number of operational satellites with SAR capability, information on the relationship between satellite first visit and revisit times and forecast performance is required to optimise the operational scheduling of satellite imagery. By using an Ensemble Transform Kalman Filter (ETKF) and a synthetic analysis with the 2D hydrodynamic model LISFLOOD-FP based on a real flooding case affecting an urban area (summer 2007,Tewkesbury, Southwest UK), we evaluate the sensitivity of the forecast performance to visit parameters. We emulate a generic hydrologic-hydrodynamic modelling cascade by imposing a bias and spatiotemporal correlations to the inflow error ensemble into the hydrodynamic domain. First, in agreement with previous research, estimation and correction for this bias leads to a clear improvement in keeping the forecast on track. Second, imagery obtained early in the flood is shown to have a large influence on forecast statistics. Revisit interval is most influential for early observations. The results are promising for the future of remote sensing-based water level observations for real-time flood forecasting in complex scenarios.

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A procedure is described in which patients are randomized between two experimental treatments and a control. At a series of interim analyses, each experimental treatment is compared with control. One of the experimental treatments might then be found sufficiently superior to the control for it to be declared the best treatment, and the trial stopped. Alternatively, experimental treatments might be eliminated from further consideration at any stage. It is shown how the procedure can be conducted while controlling overall error probabilities. Data concerning evaluation of different doses of riluzole in the treatment of motor neurone disease are used for illustration.

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Radiometric data in the visible domain acquired by satellite remote sensing have proven to be powerful for monitoring the states of the ocean, both physical and biological. With the help of these data it is possible to understand certain variations in biological responses of marine phytoplankton on ecological time scales. Here, we implement a sequential data-assimilation technique to estimate from a conventional nutrient–phytoplankton–zooplankton (NPZ) model the time variations of observed and unobserved variables. In addition, we estimate the time evolution of two biological parameters, namely, the specific growth rate and specific mortality of phytoplankton. Our study demonstrates that: (i) the series of time-varying estimates of specific growth rate obtained by sequential data assimilation improves the fitting of the NPZ model to the satellite-derived time series: the model trajectories are closer to the observations than those obtained by implementing static values of the parameter; (ii) the estimates of unobserved variables, i.e., nutrient and zooplankton, obtained from an NPZ model by implementation of a pre-defined parameter evolution can be different from those obtained on applying the sequences of parameters estimated by assimilation; and (iii) the maximum estimated specific growth rate of phytoplankton in the study area is more sensitive to the sea-surface temperature than would be predicted by temperature-dependent functions reported previously. The overall results of the study are potentially useful for enhancing our understanding of the biological response of phytoplankton in a changing environment.

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We propose first, a simple task for the eliciting attitudes toward risky choice, the SGG lottery-panel task, which consists in a series of lotteries constructed to compensate riskier options with higher risk-return trade-offs. Using Principal Component Analysis technique, we show that the SGG lottery-panel task is capable of capturing two dimensions of individual risky decision making i.e. subjects’ average risk taking and their sensitivity towards variations in risk-return. From the results of a large experimental dataset, we confirm that the task systematically captures a number of regularities such as: A tendency to risk averse behavior (only around 10% of choices are compatible with risk neutrality); An attraction to certain payoffs compared to low risk lotteries, compatible with over-(under-) weighting of small (large) probabilities predicted in PT and; Gender differences, i.e. males being consistently less risk averse than females but both genders being similarly responsive to the increases in risk-premium. Another interesting result is that in hypothetical choices most individuals increase their risk taking responding to the increase in return to risk, as predicted by PT, while across panels with real rewards we see even more changes, but opposite to the expected pattern of riskier choices for higher risk-returns. Therefore, we conclude from our data that an “economic anomaly” emerges in the real reward choices opposite to the hypothetical choices. These findings are in line with Camerer's (1995) view that although in many domains, paid subjects probably do exert extra mental effort which improves their performance, choice over money gambles is not likely to be a domain in which effort will improve adherence to rational axioms (p. 635). Finally, we demonstrate that both dimensions of risk attitudes, average risk taking and sensitivity towards variations in the return to risk, are desirable not only to describe behavior under risk but also to explain behavior in other contexts, as illustrated by an example. In the second study, we propose three additional treatments intended to elicit risk attitudes under high stakes and mixed outcome (gains and losses) lotteries. Using a dataset obtained from a hypothetical implementation of the tasks we show that the new treatments are able to capture both dimensions of risk attitudes. This new dataset allows us to describe several regularities, both at the aggregate and within-subjects level. We find that in every treatment over 70% of choices show some degree of risk aversion and only between 0.6% and 15.3% of individuals are consistently risk neutral within the same treatment. We also confirm the existence of gender differences in the degree of risk taking, that is, in all treatments females prefer safer lotteries compared to males. Regarding our second dimension of risk attitudes we observe, in all treatments, an increase in risk taking in response to risk premium increases. Treatment comparisons reveal other regularities, such as a lower degree of risk taking in large stake treatments compared to low stake treatments and a lower degree of risk taking when losses are incorporated into the large stake lotteries. Results that are compatible with previous findings in the literature, for stake size effects (e.g., Binswanger, 1980; Antoni Bosch-Domènech & Silvestre, 1999; Hogarth & Einhorn, 1990; Holt & Laury, 2002; Kachelmeier & Shehata, 1992; Kühberger et al., 1999; B. J. Weber & Chapman, 2005; Wik et al., 2007) and domain effect (e.g., Brooks and Zank, 2005, Schoemaker, 1990, Wik et al., 2007). Whereas for small stake treatments, we find that the effect of incorporating losses into the outcomes is not so clear. At the aggregate level an increase in risk taking is observed, but also more dispersion in the choices, whilst at the within-subjects level the effect weakens. Finally, regarding responses to risk premium, we find that compared to only gains treatments sensitivity is lower in the mixed lotteries treatments (SL and LL). In general sensitivity to risk-return is more affected by the domain than the stake size. After having described the properties of risk attitudes as captured by the SGG risk elicitation task and its three new versions, it is important to recall that the danger of using unidimensional descriptions of risk attitudes goes beyond the incompatibility with modern economic theories like PT, CPT etc., all of which call for tests with multiple degrees of freedom. Being faithful to this recommendation, the contribution of this essay is an empirically and endogenously determined bi-dimensional specification of risk attitudes, useful to describe behavior under uncertainty and to explain behavior in other contexts. Hopefully, this will contribute to create large datasets containing a multidimensional description of individual risk attitudes, while at the same time allowing for a robust context, compatible with present and even future more complex descriptions of human attitudes towards risk.

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This article presents a study examining how narrative structure and narrative complexity might influence the performance of second language learners. Forty learners of English in London and sixty learners in Teheran were asked to retell cartoon stories from picture prompts. Each performed two of four narrative tasks that had different degrees of narrative structure (loose or tight) and of storyline complexity (with or without background events). Results support the findings of previous research that tight task structure is connected to increased accuracy and that narratives involving background information give rise to more complex syntax. A comparison of the data from the London and Teheran cohorts showed that the learners in London used significantly more complex syntax and diverse vocabulary even though they did not differ from the Teheran learners in other performance dimensions.

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Despite the increasing number of studies examining the correlates of interest and boredom, surprisingly little research has focused on within-person fluctuations in these emotions, making it difficult to describe their situational nature. To address this gap in the literature, this study conducted repeated measurements (12 times) on a sample of 158 undergraduate students using a variety of self-report assessments, and examined the within-person relationships between task-specific perceptions (expectancy, utility, and difficulty) and interest and boredom. This study further explored the role of achievement goals in predicting between-person differences in these within-person relationships. Utilizing hierarchical-linear modeling, we found that, on average, a higher perception of both expectancy and utility, as well as a lower perception of difficulty, was associated with higher interest and lower boredom levels within individuals. Moreover, mastery-approach goals weakened the negative within-person relationship between difficulty and interest and the negative within-person relationship between utility and boredom. Mastery-avoidance and performance-avoidance goals strengthened the negative relationship between expectancy and boredom. These results suggest how educators can more effectively instruct students with different types of goals, minimizing boredom and maximizing interest and learning.

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In probabilistic decision tasks, an expected value (EV) of a choice is calculated, and after the choice has been made, this can be updated based on a temporal difference (TD) prediction error between the EV and the reward magnitude (RM) obtained. The EV is measured as the probability of obtaining a reward x RM. To understand the contribution of different brain areas to these decision-making processes, functional magnetic resonance imaging activations related to EV versus RM (or outcome) were measured in a probabilistic decision task. Activations in the medial orbitofrontal cortex were correlated with both RM and with EV and confirmed in a conjunction analysis to extend toward the pregenual cingulate cortex. From these representations, TD reward prediction errors could be produced. Activations in areas that receive from the orbitofrontal cortex including the ventral striatum, midbrain, and inferior frontal gyrus were correlated with the TD error. Activations in the anterior insula were correlated negatively with EV, occurring when low reward outcomes were expected, and also with the uncertainty of the reward, implicating this region in basic and crucial decision-making parameters, low expected outcomes, and uncertainty.

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The present study investigated whether developmental changes in cognitive control may underlie improvements of time-based prospective memory. Five-, 7-, 9-, and 11-year-olds (N = 166) completed a driving simulation task (ongoing task) in which they had to refuel their vehicle at specific points in time (PM task). The availability of cognitive control resources was experimentally manipulated by imposing a secondary task that required divided attention. Children completed the driving simulation task both in a full attention condition and a divided attention condition where they had to carry out a secondary task. Results revealed that older children performed better than younger children on the ongoing task and PM task. Children performed worse on the ongoing and PM tasks in the divided attention condition compared to the full attention condition. With respect to time monitoring in the final interval prior to the PM target, divided attention interacted with age such that older children’s time monitoring was more negatively affected by the secondary task compared to younger children. Results are discussed in terms of developmental shifts from reactive to proactive monitoring strategies.

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This paper presents a novel mobile sink area allocation scheme for consumer based mobile robotic devices with a proven application to robotic vacuum cleaners. In the home or office environment, rooms are physically separated by walls and an automated robotic cleaner cannot make a decision about which room to move to and perform the cleaning task. Likewise, state of the art cleaning robots do not move to other rooms without direct human interference. In a smart home monitoring system, sensor nodes may be deployed to monitor each separate room. In this work, a quad tree based data gathering scheme is proposed whereby the mobile sink physically moves through every room and logically links all separated sub-networks together. The proposed scheme sequentially collects data from the monitoring environment and transmits the information back to a base station. According to the sensor nodes information, the base station can command a cleaning robot to move to a specific location in the home environment. The quad tree based data gathering scheme minimizes the data gathering tour length and time through the efficient allocation of data gathering areas. A calculated shortest path data gathering tour can efficiently be allocated to the robotic cleaner to complete the cleaning task within a minimum time period. Simulation results show that the proposed scheme can effectively allocate and control the cleaning area to the robot vacuum cleaner without any direct interference from the consumer. The performance of the proposed scheme is then validated with a set of practical sequential data gathering tours in a typical office/home environment.