993 resultados para variables objectives


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Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.

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The European Project on Ocean Acidification (EPOCA) is Europe's first large-scale research initiative devoted to studying the impacts and consequences of ocean acidification. More than 100 scientists from 27 institutes and nine countries bring their expertise to the project, resulting in a multidisciplinary and versatile consortium. The project is funded for four years (2008 to 2012) by the European Commission within its Seventh Framework Programme. This article describes EPOCA and explains its different aspects, objectives, and products. Following a general introduction, six boxes highlight outcomes, techniques, and scientific results from each of the project's core themes.

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Mediterranean demersal fisheries are highly multispecific and many of their target stocks are overexploited. In addition, rocketing fuel costs and low market prices of traditionally high-value species are challenging the viability of fisheries. Here, based on the numeric results of a simulation model, we conclude that this situation can be remedied by reducing both fishing mortality and fishing costs. According to our model results, fishing effort reductions of 48–71% would improve the health of fish stocks while increasing the economic profits of Mallorca islands bottom trawl fishery to as much as 1.9 M€ (146% higher than current profits). If all fish stocks were exploited at their MSY (or below) level, the reduction in fishing effort would have to be of 71% from current values. If equilibrium profits from the fishery were to be maximized (MEY), fishing effort would need to be reduced by 48%. These results must be taken with caution due the many sources of uncertainty of our analysis. The modeling tools used to estimate these values are conditional to the adequate treatment of two sources of uncertainty that are particularly problematic in Mediterranean fisheries: insufficiently known recruitment variability and lack of periodic evaluations of the state of many species. Our results show that fishing effort reductions would produce economic yield gains after a period of transition. Further studies on the benefits of changing the size-selection pattern of fisheries, on better estimation of stock–recruitment relationships and on better quantifications of the contribution of secondary species to these fisheries, are expected to improve the scientific recommendations for Mediterranean demersal fisheries toward sustainability principles.

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The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

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The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998–2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.

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Mediterranean demersal fisheries are highly multispecific and many of their target stocks are overexploited. In addition, rocketing fuel costs and low market prices of traditionally high-value species are challenging the viability of fisheries. Here, based on the numeric results of a simulation model, we conclude that this situation can be remedied by reducing both fishing mortality and fishing costs. According to our model results, fishing effort reductions of 48-71% would improve the health of fish stocks while increasing the economic profits of Mallorca islands bottom trawl fishery to as much as 1.9 M(sic) (146% higher than current profits). If all fish stocks were exploited at their MSY (or below) level, the reduction in fishing effort would have to be of 71% from current values. If equilibrium profits from the fishery were to be maximized (MEY), fishing effort would need to be reduced by 48%. These results must be taken with caution due the many sources of uncertainty of our analysis. The modeling tools used to estimate these values are conditional to the adequate treatment of two sources of uncertainty that are particularly problematic in Mediterranean fisheries: insufficiently known recruitment variability and lack of periodic evaluations of the state of many species. Our results show that fishing effort reductions would produce economic yield gains after a period of transition. Further studies on the benefits of changing the size-selection pattern of fisheries, on better estimation of stock recruitment relationships and on better quantifications of the contribution of secondary species to these fisheries, are expected to improve the scientific recommendations for Mediterranean demersal fisheries toward sustainability principles.

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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

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A process of social transformation allied with ongoing changes to the family has made possible the existence of a relatively little-known phenomenon: that of child-parent violence, which is raised as one of the most commonly experienced forms of violence in the family environment. Based on the study of this phenomenon, in our research we have used the qualitative technique of a life story, making use of a field diary in which we have taken notes on our daily work in the therapeutic context, for the purposes of mitigating the effects of such a process. The following research objectives were set: establishing the connection existing between family education style and the use of violence by the minor; and evaluating the extent to which family therapy mitigates the use of violence by the minor. The family education model, together with other dimensions, results in situations of child-parent violence occurring repeatedly, with continuing negative reinforcement from both parties in order to maintain a recurrent cycle of conduct, from which it is difficult to «escape» other than through a process of ongoing psychological therapy.

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A method for simulation of acoustical bores, useful in the context of sound synthesis by physical modeling of woodwind instruments, is presented. As with previously developed methods, such as digital waveguide modeling (DWM) [Smith, Comput. Music J. 16, pp 74-91 (1992)] and the multi convolution algorithm (MCA) [Martinez et al., J. Acoust. Soc. Am. 84, pp 1620-1627 (1988)], the approach is based on a one-dimensional model of wave propagation in the bore. Both the DWM method and the MCA explicitly compute the transmission and reflection of wave variables that represent actual traveling pressure waves. The method presented in this report, the wave digital modeling (WDM) method, avoids the typical limitations associated with these methods by using a more general definition of the wave variables. An efficient and spatially modular discrete-time model is constructed from the digital representations of elemental bore units such as cylindrical sections, conical sections, and toneholes. Frequency-dependent phenomena, such as boundary losses, are approximated with digital filters. The stability of a simulation of a complete acoustic bore is investigated empirically. Results of the simulation of a full clarinet show that a very good concordance with classic transmission-line theory is obtained.

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OBJECTIVES: (1) Describe the population of mentally ill offenders over whom Ontario Review Board (ORB) held jurisdiction. (2) Assess the influences of psychopathology and criminal factors on criminal career. METHOD: This study was a retrospective case series design that reviewed all offenders who were court ordered for psychiatric evaluation at Mental Health Services Site of Providence Care in Kingston, Ontario from 1993 to 2007 (N=347). Eighty five subjects were found not criminally responsible on the account of mental disorder and were included in statistical analysis (n=85). Bivariate associations between five key variables and two outcome variables, seriousness of crime and recidivism, were examined. Logistic regressions were conducted to test the role of the predictor variables on the outcome variables. RESULTS: Age and change in principal psychiatric diagnosis over time were shown to be associated with seriousness of crime. Timing of psychiatric onset, early signs of deviance and change in diagnosis were shown to be associated with recidivism. On the whole, study population did not markedly vary in their distribution of variables by the outcome variables. Regression model included timing of psychiatric onset; psychiatric history; existence of criminal associate; child abuse history; and early signs of deviance. Recidivism was shown to be predicted by early signs of deviance (OR=8.154, p<0.05). Existence of criminal associates was shown to have substantial values of odds ratio at marginal significance (OR=7.577, p=0.13). CONCLUSION: Seriousness of crime is a complex factor that could not be sufficiently predicted by any one or combinations of study variables. Recidivism is better predicted by criminality factors than psychopathology. In the future, an exploratory analysis that more broadly examines the psychopathology and criminal factors in Canadian forensic population is needed. Findings from this study have important clinical and legal implications.

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This study presents a reproducible, cost-effective in vitro encrustation model and, furthermore, describes the effects of components of the artificial urine and the presence of agents that modify the action of urease on encrustation on commercially available ureteral stents. The encrustation model involved the use of small-volume reactors (700 mL) containing artificial urine and employing an orbital incubator (at 37 degrees C) to ensure controlled stirring. The artificial urine contained sources of calcium and magnesium (both as chlorides), albumin and urease. Alteration of the ratio (% w/w) of calcium salt to magnesium salt affected the mass of encrustation, with the greatest encrustation noted whenever magnesium was excluded from the artificial urine. Increasing the concentration of albumin, designed to mimic the presence of protein in urine, significantly decreased the mass of both calcium and magnesium encrustation until a plateau was observed. Finally, exclusion of urease from the artificial urine significantly reduced encrustation due to the indirect effects of this enzyme on pH. Inclusion of the urease inhibitor, acetohydroxamic acid, or urease substrates (methylurea or ethylurea) into the artificial medium markedly reduced encrustation on ureteral stents. In conclusion, this study has described the design of a reproducible, cost-effective in vitro encrustation model. Encrustation was markedly reduced on biomaterials by the inclusion of agents that modify the action of urease. These agents may, therefore, offer a novel clinical approach to the control of encrustation on urological medical devices. (c) 2005 Wiley Periodicals, Inc.