946 resultados para preference for routine


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This paper considers a time varying parameter extension of the Ruge-Murcia (2003, 2004) model to explore whether some of the variation in parameter estimates seen in the literature could arise from this source. A time varying value for the unemployment volatility parameter can be motivated through several means including variation in the slope of the Phillips curve or variation in the preferences of the monetary authority.We show that allowing time variation for the coefficient on the unemployment volatility parameter improves the model fit and it helps to provide an explanation of inflation bias based on asymmetric central banker preferences, which is consistent across subsamples.

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Objective: The subjective experience of psychotic patients toward treatment is a key factor in medication adherence, quality of life, and clinical outcome. The aim of this study was to assess the subjective well-being in patients with schizophrenia and to examine its relationship with the presence and severity of depressive symptoms. Methods: A multicenter, cross-sectional study was conducted with clinically stable outpatients diagnosed with schizophrenia. The Subjective Well-Being under Neuroleptic Scale - short version (SWN-K) and the Calgary Depression Scale for Schizophrenia (CDSS) were used to gather information on well-being and the presence and severity of depressive symptoms, respectively. Spearman's rank correlation was used to assess the associations between the SWN-K total score, its five subscales, and the CDSS total score. Discriminative validity was evaluated against that criterion by analysing the area under the curve (AUC). Results: Ninety-seven patients were included in the study. Mean age was 35 years (standard deviation = 10) and 72% were male. Both the total SWN-K scale and its five subscales correlated inversely and significantly with the CDSS total score (P < 0.0001). The highest correlation was observed for the total SWN-K (Spearman's rank order correlation [ rho] = -0.59), being the other correlations: mental functioning (-0.47), social integration (-0.46), emotional regulation (-0.51), physical functioning (-0.48), and self-control (-0.41). A total of 33 patients (34%) were classified as depressed. Total SWN-K showed the highest AUC when discriminating between depressive severity levels (0.84), followed by emotional regulation (0.80), social integration (0.78), physical functioning and self-control (0.77), and mental functioning (0.73). Total SWN-K and its five subscales showed a significant linear trend against CDSS severity levels (P < 0.001). Conclusion: The presence of moderate to severe depressive symptoms was relatively high, and correlated inversely with patients' subjective well-being. Routine assessment of patient-reported measures in patients with schizophrenia might reduce potential discrepancy between patient and physician assessment, increase therapeutic alliance, and improve outcome.

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The Alliance for Coastal Technologies (ACT) Workshop "Making Oxygen Measurements Routine Like Temperature" was convened in St. Petersburg, Florida, January 4th - 6th, 2006. This event was sponsored by the University of South Florida (USF) College of Marine Science, an ACT partner institution and co-hosted by the Ocean Research Interactive Observatory Networks (ORION). Participants from researcldacademia, resource management, industry, and engineering sectors collaborated with the aim to foster ideas and information on how to make measuring dissolved oxygen a routine part of a coastal or open ocean observing system. Plans are in motion to develop large scale ocean observing systems as part of the US Integrated Ocean Observing System (100s; see http://ocean.us) and the NSF Ocean Observatory Initiative (001; see http://www.orionprogram.org/00I/default.hl). These systems will require biological and chemical sensors that can be deployed in large numbers, with high reliability, and for extended periods of time (years). It is also likely that the development cycle for new sensors is sufficiently long enough that completely new instruments, which operate on novel principles, cannot be developed before these complex observing systems will be deployed. The most likely path to development of robust, reliable, high endurance sensors in the near future is to move the current generation of sensors to a much greater degree of readiness. The ACT Oxygen Sensor Technology Evaluation demonstrated two important facts that are related to the need for sensors. There is a suite of commercially available sensors that can, in some circumstances, generate high quality data; however, the evaluation also showed that none of the sensors were able to generate high quality data in all circumstances for even one month time periods due to biofouling issues. Many groups are attempting to use oxygen sensors in large observing programs; however, there often seems to be limited communication between these groups and they often do not have access to sophisticated engineering resources. Instrument manufacturers also do not have sufficient resources to bring sensors, which are marketable, but of limited endurance or reliability, to a higher state of readiness. The goal of this ACT/ORION Oxygen Sensor Workshop was to bring together a group of experienced oceanographers who are now deploying oxygen sensors in extended arrays along with a core of experienced and interested academic and industrial engineers, and manufacturers. The intended direction for this workshop was for this group to exchange information accumulated through a variety of sensor deployments, examine failure mechanisms and explore a variety of potential solutions to these problems. One anticipated outcome was for there to be focused recommendations to funding agencies on development needs and potential solutions for 02 sensors. (pdf contains 19 pages)

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Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.

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During the last two decades, analysis of 1/f noise in cognitive science has led to a considerable progress in the way we understand the organization of our mental life. However, there is still a lack of specific models providing explanations of how 1/f noise is generated in coupled brain-body-environment systems, since existing models and experiments typically target either externally observable behaviour or isolated neuronal systems but do not address the interplay between neuronal mechanisms and sensorimotor dynamics. We present a conceptual model of a minimal neurorobotic agent solving a behavioural task that makes it possible to relate mechanistic (neurodynamic) and behavioural levels of description. The model consists of a simulated robot controlled by a network of Kuramoto oscillators with homeostatic plasticity and the ability to develop behavioural preferences mediated by sensorimotor patterns. With only three oscillators, this simple model displays self-organized criticality in the form of robust 1/f noise and a wide multifractal spectrum. We show that the emergence of self-organized criticality and 1/f noise in our model is the result of three simultaneous conditions: a) non-linear interaction dynamics capable of generating stable collective patterns, b) internal plastic mechanisms modulating the sensorimotor flows, and c) strong sensorimotor coupling with the environment that induces transient metastable neurodynamic regimes. We carry out a number of experiments to show that both synaptic plasticity and strong sensorimotor coupling play a necessary role, as constituents of self-organized criticality, in the generation of 1/f noise. The experiments also shown to be useful to test the robustness of 1/f scaling comparing the results of different techniques. We finally discuss the role of conceptual models as mediators between nomothetic and mechanistic models and how they can inform future experimental research where self-organized critically includes sensorimotor coupling among the essential interaction-dominant process giving rise to 1/f noise.

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The daily consumption rates and preference of juvenile Tilapia rendalli for some macrophytes, Ceratophyllum demersum, Lagarosiphon major, Najas pectinatas and Valisneria aethiopica were determined. Fish were offered single macrophyte diets to determine daily consumption and a mixture of the 4 macrophytes in equal quantities to determine selection. Consumption rates were 821.50 mg, 829.05 mg, 940.00 mg and 2293.53 mg per fish per day, respectively. The differences in consumption rates were significant. Preference was shown for V.aethiopica, whilst C.demersum was least selected. Fish fed on single species lost weight whereas those fed on a variety of macrophytes gained in weight.

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Many highly exploited ecosystems are managed on the basis of single-species demographic information. This management approach can exacerbate tensions among stakeholders with competing interests who in turn rely on data with notoriously high variance. In this case study, an application of diet and dive survey data was used to describe the prey preference of lingcod (Ophiodon elongatus) in a predictive framework on nearshore reefs off Oregon. The lingcod is a large, fast-growing generalist predator of invertebrates and fishes. In response to concerns that lingcod may significantly reduce diminished populations of rockfishes (Sebastes spp.), the diets of 375 lingcod on nearshore reefs along the Oregon Coast were compared with estimates of relative prey availability from dive surveys. In contrast to the transient pelagic fishes that comprised 46% of lingcod diet by number, rockfishes comprised at most 4.7% of prey items. Rockfishes were the most abundant potential prey observed in dive surveys, yet they were the least preferred. Ecosystem-based fisheries management (EBFM) requires information about primary trophic relationships, as well as relative abundance and distribution data for multiple species. This study shows that, at a minimum, predation relative to prey availability must be considered before predator effects can be understood in a management context.

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Standard and routine metabolic rates (SMRs and RMRs, respectively) of juvenile sandbar sharks (Carcharhinus plumbeus) were measured over a range of body sizes (n=34) and temperatures normally associated with western Atlantic coastal nursery areas. The mean SMR Q10 (increase in metabolic rate with temperature) was 2.9 ±0.2. Heart rate decreased with increasing body mass but increased with temperature at a Q10 of 1.8−2.2. Self-paired measures of SMR and RMR were obtained for 15 individuals. Routine metabolic rate averaged 1.8 ±0.1 times the SMR and was not correlated with body mass. Assuming the maximum metabolic rate of sandbar sharks is 1.8−2.75 times the SMR (as is observed in other elasmobranch species), sandbar sharks are using between 34% and 100% of their metabolic scope just to sustain their routine continuous activity. This limitation may help to explain their slow individual and population growth rates, as well as the slow recoveries from overfishing of many shark stocks worl

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Many common fishes associated with Caribbean coral reef ecosystems use resources from more than 1 patch type during routine daily foraging activities. Few studies have provided direct evidence of connectivity across seascapes, and the importance of benthic seascape structure on movement behavior is poorly known. To address this knowledge gap, we coupled hydro-acoustic technology to track fish with seafloor mapping and pattern analysis techniques from landscape ecology to quantify seascape structure. Bluestriped grunts Haemulon sciurus and schoolmaster snapper Lutjanus apodus were tracked over 24 h periods using boat-based acoustic telemetry. Movement pathways, and day and night activity spaces were mapped using geographical information system (GIS) tools, and seafloor structure within activity spaces was mapped from high-resolution aerial photography and quantified using spatial pattern metrics. For both fish species, night activity spaces were significantly larger than day activity spaces. Fish exhibited a daytime preference for seascapes with aggregate coral reef and colonized bedrock, then shifted to night activity spaces with lower complexity soft sediment including sand, seagrass, and scattered coral/rock. Movement path complexity was negatively correlated with seascape complexity. This demonstrates direct connectivity across multiple patch types and represents the first study to apply quantitative landscape ecology techniques to examine the movement ecology of marine fish. The spatially explicit approach facilitates understanding to the linkages between biological processes and the heterogeneity of the landscape. Such studies are essential for identifying ecologically relevant spatial scales, delineating essential fish habitat and designing marine protected areas.