Can climate models capture the structure of extratropical cyclones?

Composites of wind speeds, equivalent potential temperature, mean sea level pressure, vertical velocity, and relative humidity have been produced for the 100 most intense extratropical cyclones in the Northern Hemisphere winter for the 40-yr ECMWF Re-Analysis (ERA-40) and the high resolution global environment model (HiGEM). Features of conceptual models of cyclone structure—the warm conveyor belt, cold conveyor belt, and dry intrusion—have been identified in the composites from ERA-40 and compared to HiGEM. Such features can be identified in the composite fields despite the smoothing that occurs in the compositing process. The surface features and the three-dimensional structure of the cyclones in HiGEM compare very well with those from ERA-40. The warm conveyor belt is identified in the temperature and wind fields as a mass of warm air undergoing moist isentropic uplift and is very similar in ERA-40 and HiGEM. The rate of ascent is lower in HiGEM, associated with a shallower slope of the moist isentropes in the warm sector. There are also differences in the relative humidity fields in the warm conveyor belt. In ERA-40, the high values of relative humidity are strongly associated with the moist isentropic uplift, whereas in HiGEM these are not so strongly associated. The cold conveyor belt is identified as rearward flowing air that undercuts the warm conveyor belt and produces a low-level jet, and is very similar in HiGEM and ERA-40. The dry intrusion is identified in the 500-hPa vertical velocity and relative humidity. The structure of the dry intrusion compares well between HiGEM and ERA-40 but the descent is weaker in HiGEM because of weaker along-isentrope flow behind the composite cyclone. HiGEM’s ability to represent the key features of extratropical cyclone structure can give confidence in future predictions from this model.

On the ability of statistical wind-wave models to capture the variability and long-term trends of the North Atlantic winter wave climate

A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.

Why have land use change models for the Amazon failed to capture the amount of deforestation over the last decade?

Land cover change in the Neotropics represents one of the major drivers of global environmental change. Several models have been proposed to explore future trajectories of land use and cover change, particularly in the Amazon. Despite the remarkable development of these tools, model results are still surrounded by uncertainties. None of the model projections available in the literature plausibly captured the overall trajectory of land use and cover change that has been observed in the Amazon over the last decade. In this context, this study aims to review and analyze the general structure of the land use models that have most recently been used to explore land use change in the Amazon, seeking to investigate methodological factors that could explain the divergence between the observed and projected rates, paying special attention to the land demand calculations. Based on this review, the primary limitations inherent to this type of model and the extent to which these limitations can affect the consistency of the projections will also be analyzed. Finally, we discuss potential drivers that could have influenced the recent dynamic of the land use system in the Amazon and produced the unforeseen land cover change trajectory observed in this period. In a complementary way, the primary challenges of the new generation of land use models for the Amazon are synthesized. (c) 2014 Elsevier Ltd. All rights reserved.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

Contingent attentional capture or delayed allocation of attention?

Under certain circumstances, external stimuli will elicit an involuntary shift of spatial attention, referred to as attentional capture. According to the contingent involuntary orienting account (Folk, Remington, & Johnston, 1992), capture is conditioned by top-down factors that set attention to respond involuntarily to stimulus properties relevant to one's behavioral goals. Evidence for this comes from spatial cuing studies showing that a spatial cuing effect is observed only when cues have goal-relevant properties. Here, we examine alternative, decision-level explanations of the spatial cuing effect that attribute evidence of capture to postpresentation delays in the voluntary allocation of attention, rather than to on-line involuntary shifts in direct response to the cue. In three spatial cuing experiments, delayed-allocation accounts were tested by examining whether items at the cued location were preferentially processed. The experiments provide evidence that costs and benefits in spatial cuing experiments do reflect the on-line capture of attention. The implications of these results for models of attentional control are discussed.

Data analysis model selection for estimating local population size of the Risso’s dolphin (Grampus griseus) in the Azores

27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.

Safety and Effectiveness of the Genous Endothelial Progenitor Cell-Capture Stent: Follow-Up to 5 Years

AIMS: To evaluate the long-term clinical outcomes following percutaneous coronary intervention (PCI) with the Genous stent in an unselected population. METHODS: All patients admitted to a single center who underwent PCI using the GS exclusively, between May 2006 and May 2012, were enrolled, and a clinical follow-up of up to 60 months was carried out. The primary endpoint of major adverse cardiac event (MACE) rate was defined as the composite of cardiac death, acute myocardial infarction (AMI), and target lesion revascularization (TLR). RESULTS: Of the 450 patients included (75.1% male; 65.5 ± 11.7 years), 28.4% were diabetic and acute coronary syndrome was the reason for PCI in 76.4%. Angioplasty was performed in 524 lesions using 597 Genous stents, with angiographic success in 97.1%. At a median of 36 months of follow-up (range, 1-75 months), MACE, AMI, TLR, stent restenosis (SR), and stent thrombosis (ST) rates were 15.6%, 8.4%, 4.4%, 3.8%, and 2.2%, respectively. Between 12 and 24 months, the TLR, SR, and ST rates practically stabilized, up to 60 months. Bifurcation lesions were independently associated with MACE, TLR, and SR. CONCLUSION: This is the first study reporting clinical results with the Genous stent up to 60 months. The Genous stent was safe and effective in the long-term, in an unselected population.

Dynamic adaptation of interaction models for stateful web services

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Comparison of capture methods for the diagnosis of adult anopheline populations from State of Mato Grosso, Brazil

INTRODUCTION: The present study compares human landing catches of primary malaria vectors with two alternative methods of capture: the Shannon trap and the Mosquito magnet. METHODS: This study used regression models to adjust capture data to a negative binominal distribution. RESULTS: Capture numbers and relative percentages obtained from the three methods vary strongly between species. The highest overall captures were obtained for Anopheles triannulatus with captures for the Shannon trap and the Mosquito magnet measuring more than 330% higher than captures obtained by human landings. For Anopheles darlingi, captures by the Shannon trap and the Mosquito magnet were about 14% and 26% of human landing catches, respectively. Another species with malaria transmission potential that was not sampled by human landing captures weascaptured by the Shannon trap and the Mosquito magnet (Anopheles oswaldoi). Both alternative sampling techniques can predict the human landing of Anopheles triannulatus, but without proportionality. Models for Anopheles darlingi counts, after totaling daily captures, are significant and proportional, but prediction models are more reliable when using the Shannon trap compared with the Mosquito magnet captures. CONCLUSIONS: These alternative capture methods can be partially recommended for the substitution of human landing captures or, at least, as complementary forms of monitoring for malarial mosquitoes.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Stability of Growth Models with Generalised Lag Structures

This paper considers the lag structures of dynamic models in economics, arguing that the standard approach is too simple to capture the complexity of actual lag structures arising, for example, from production and investment decisions. It is argued that recent (1990s) developments in the the theory of functional differential equations provide a means to analyse models with generalised lag structures. The stability and asymptotic stability of two growth models with generalised lag structures are analysed. The paper concludes with some speculative discussion of time-varying parameters.

Mosquito traps designed to capture Aedes aegypti (Diptera: Culicidae) females: preliminary comparison of Adultrap, MosquiTRAP and backpack aspirator efficiency in a dengue-endemic area of Brazil

In this report, the efficiency of Adultrap under field conditions is compared to a CDC backpack aspirator and to MosquiTRAP. An urban dengue-endemic area of Rio de Janeiro was selected to evaluate the efficiency of mosquito traps in capturing Aedes aegypti females. Adultrap and aspirator captured similar numbers of Ae. aegypti females, with the former showing high specificity to gravid individuals (93.6%). A subsequent mark-release-recapture experiment was conducted to evaluate Adultrap and MosquiTRAP efficiency concomitantly. With a 6.34% recapture rate, MosquiTRAP captured a higher mean number of female Ae. aegypti per trap than Adultrap (Ç2 = 14.26; df = 1; p < 0,05). However, some MosquiTRAPs (28.12%) contained immature Ae. aegypti after 18 days of exposure in the field and could be pointed as an oviposition site for female mosquitoes. Both trapping methods, designed to collect gravid Ae. aegypti females, seem to be efficient, reliable and may aid routine Ae. aegypti surveillance.

Incorporating waiting time in competitive location models: formulations and heuristics

In this paper we propose a metaheuristic to solve a new version of the Maximum Capture Problem. In the original MCP, market capture is obtained by lower traveling distances or lower traveling time, in this new version not only the traveling time but also the waiting time will affect the market share. This problem is hard to solve using standard optimization techniques. Metaheuristics are shown to offer accurate results within acceptable computing times.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.