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Physiological Measurements (physiological + measurement)
Selected AbstractsIndirect effects of algae on coral: algae-mediated, microbe-induced coral mortalityECOLOGY LETTERS, Issue 7 2006Jennifer E. Smith Abstract Declines in coral cover are generally associated with increases in the abundance of fleshy algae. In many cases, it remains unclear whether algae are responsible, directly or indirectly, for coral death or whether they simply settle on dead coral surfaces. Here, we show that algae can indirectly cause coral mortality by enhancing microbial activity via the release of dissolved compounds. When coral and algae were placed in chambers together but separated by a 0.02 ,m filter, corals suffered 100% mortality. With the addition of the broad-spectrum antibiotic ampicillin, mortality was completely prevented. Physiological measurements showed complementary patterns of increasing coral stress with proximity to algae. Our results suggest that as human impacts increase and algae become more abundant on reefs a positive feedback loop may be created whereby compounds released by algae enhance microbial activity on live coral surfaces causing mortality of corals and further algal growth. [source] BUILDING A DATA-MINING GRID FOR MULTIPLE HUMAN BRAIN DATA ANALYSISCOMPUTATIONAL INTELLIGENCE, Issue 2 2005Ning Zhong E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision. [source] Towards predictive modelling of the electrophysiology of the heartEXPERIMENTAL PHYSIOLOGY, Issue 5 2009Edward Vigmond The simulation of cardiac electrical function is an example of a successful integrative multiscale modelling approach that is directly relevant to human disease. Today we stand at the threshold of a new era, in which anatomically detailed, tomographically reconstructed models are being developed that integrate from the ion channel to the electromechanical interactions in the intact heart. Such models hold high promise for interpretation of clinical and physiological measurements, for improving the basic understanding of the mechanisms of dysfunction in disease, such as arrhythmias, myocardial ischaemia and heart failure, and for the development and performance optimization of medical devices. The goal of this article is to present an overview of current state-of-art advances towards predictive computational modelling of the heart as developed recently by the authors of this article. We first outline the methodology for constructing electrophysiological models of the heart. We then provide three examples that demonstrate the use of these models, focusing specifically on the mechanisms for arrhythmogenesis and defibrillation in the heart. These include: (1) uncovering the role of ventricular structure in defibrillation; (2) examining the contribution of Purkinje fibres to the failure of the shock; and (3) using magnetic resonance imaging reconstructed heart models to investigate the re-entrant circuits formed in the presence of an infarct scar. [source] Evaluation of six process-based forest growth models using eddy-covariance measurements of CO2 and H2O fluxes at six forest sites in EuropeGLOBAL CHANGE BIOLOGY, Issue 3 2002K. Kramer Abstract Reliable models are required to assess the impacts of climate change on forest ecosystems. Precise and independent data are essential to assess this accuracy. The flux measurements collected by the EUROFLUX project over a wide range of forest types and climatic regions in Europe allow a critical testing of the process-based models which were developed in the LTEEF project. The ECOCRAFT project complements this with a wealth of independent plant physiological measurements. Thus, it was aimed in this study to test six process-based forest growth models against the flux measurements of six European forest types, taking advantage of a large database with plant physiological parameters. The reliability of both the flux data and parameter values itself was not under discussion in this study. The data provided by the researchers of the EUROFLUX sites, possibly with local corrections, were used with a minor gap-filling procedure to avoid the loss of many days with observations. The model performance is discussed based on their accuracy, generality and realism. Accuracy was evaluated based on the goodness-of-fit with observed values of daily net ecosystem exchange, gross primary production and ecosystem respiration (gC m,2 d,1), and transpiration (kg H2O m,2 d,1). Moreover, accuracy was also evaluated based on systematic and unsystematic errors. Generality was characterized by the applicability of the models to different European forest ecosystems. Reality was evaluated by comparing the modelled and observed responses of gross primary production, ecosystem respiration to radiation and temperature. The results indicated that: Accuracy. All models showed similar high correlation with the measured carbon flux data, and also low systematic and unsystematic prediction errors at one or more sites of flux measurements. The results were similar in the case of several models when the water fluxes were considered. Most models fulfilled the criteria of sufficient accuracy for the ability to predict the carbon and water exchange between forests and the atmosphere. Generality. Three models of six could be applied for both deciduous and coniferous forests. Furthermore, four models were applied both for boreal and temperate conditions. However, no severe water-limited conditions were encountered, and no year-to-year variability could be tested. Realism. Most models fulfil the criterion of realism that the relationships between the modelled phenomena (carbon and water exchange) and environment are described causally. Again several of the models were able to reproduce the responses of measurable variables such as gross primary production (GPP), ecosystem respiration and transpiration to environmental driving factors such as radiation and temperature. Stomatal conductance appears to be the most critical process causing differences in predicted fluxes of carbon and water between those models that accurately describe the annual totals of GPP, ecosystem respiration and transpiration. As a conclusion, several process-based models are available that produce accurate estimates of carbon and water fluxes at several forest sites of Europe. This considerable accuracy fulfils one requirement of models to be able to predict the impacts of climate change on the carbon balance of European forests. However, the generality of the models should be further evaluated by expanding the range of testing over both time and space. In addition, differences in behaviour between models at the process level indicate requirement of further model testing, with special emphasis on modelling stomatal conductance realistically. [source] Online pattern recognition based on a generalized hidden Markov model for intraoperative vital sign monitoringINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2010Ping Yang Abstract The trend patterns of vital signs provide significant insight into the interpretation of intraoperative physiological measurements. We have modeled the trend signal of a vital sign parameter as a generalized hidden Markov model (also known as a hidden semi-Markov model). This model treats a time series as a sequence of predefined patterns and describes the transition between these patterns as a first-order Markov process and the intra-segmental variations as different dynamic linear systems. Based on this model, a switching Kalman smoother combines a Bayesian inference process with a fixed-point Kalman smoother in order to estimate the unconditional true signal values and generates the probability of occurrence for each pattern online. The probabilities of pattern transitions are tested against a threshold to detect change points. A second-order generalized pseudo-Bayesian algorithm is used to summarize the state propagation over time and reduces the computational overhead. The memory complexity is reduced using linked tables. The algorithm was tested on 30 simulated signals and 10 non-invasive-mean-blood-pressure trend signals collected at a local hospital. In the simulated test, the algorithm achieved a high accuracy of signal estimation and pattern recognition. In the test on clinical data, the change directions of 45 trend segments, out of the 54 segments annotated by an expert, were correctly detected with the best performing threshold, and with the introduction of only 8 false-positive detections. The proposed method can detect the changes of trend patterns in a time series online, while generating quantitative evaluation of the significance of detection. This method is promising for physiological monitoring as the method not only generates early alerts, but also summarizes the temporal contextual information for a high-level decision support system. Copyright © 2009 John Wiley & Sons, Ltd. [source] Obesity and Physical Activity in College Women: Implications for Clinical PracticeJOURNAL OF THE AMERICAN ACADEMY OF NURSE PRACTITIONERS, Issue 7 2004APRN-BC, Jacquelyn M. Clement PhD Purpose To investigate the relationships between levels of physical activity, health attitudes and behaviors, and specific health indicators in women attending college. Data Sources A convenience sample of 116 college women, ages 18 to 24 years, participated in this research study at a moderate-sized midwestern university. The data were obtained through self-administered questionnaire; trained technicians collected physiological measurements. Conclusions The young women in this study had, on average, normal body mass indexes (BMIs) and reported activity levels consistent with or greater than the Centers for Disease Control and Prevention/American College of Sports Medicine guidelines. Items used to assign participants into the appropriate stage of the transtheoretical model of change were correlated with participants' perceived personal physical activity levels. Similarly, the participants, whose scores fell in the higher stages of the transtheoretical model, reported greater levels of physical activity; consumption of more fruits, vegetables, and water; and less consumption of high-fat/high-calorie foods. Implications for Practice The years between ages 18 and 24 are a critical time in the lives of young women. During this period, they develop physical activity and nutrition habits that will affect their health across the life span. Because of the sometimes insidious development of major health problems, young women's current health status may not accurately reflect the possible longterm results of negative health habits. Nurse practitioners (NPs) have many opportunities to identify and address major factors that, if unattended, may threaten the life-long health status of women. Health teaching in the areas of physical activity and dietary habits may be useful even in young women who appear to be healthy, are of normal weight, and are physically active.Poor dietary habits, if unattended, may eventually contribute to the development of obesity and related illnesses. [source] Evidence for shutter-speed variation in CR bolus-tracking studies of human pathologyNMR IN BIOMEDICINE, Issue 3 2005Thomas E. Yankeelov Abstract The standard pharmacokinetic model for the analysis of MRI contrast reagent (CR) bolus-tracking (B-T) data assumes that the mean intracellular water molecule lifetime (,i) is effectively zero. This assertion is inconsistent with a considerable body of physiological measurements. Furthermore, theory and simulation show the B-T time-course shape to be very sensitive to the ,i magnitude in the physiological range (hundreds of milliseconds to several seconds). Consequently, this standard model aspect can cause significant underestimations (factors of 2 or 3) of the two parameters usually determined: Ktrans, the vascular wall CR transfer rate constant, and ve, the CR distribution volume (the extracellular, extravascular space fraction). Analyses of animal model data confirmed two predicted behaviors indicative of this standard model inadequacy: (1) a specific temporal pattern for the mismatch between the best-fitted curve and data; and (2) an inverse dependence of the curve's Ktrans and ve magnitudes on the CR dose. These parameters should be CR dose-independent. The most parsimonious analysis allowing for realistic ,i values is the ,shutter-speed' model. Its application to the experimental animal data essentially eliminated the two standard model signature inadequacies. This paper reports the first survey for the extent of this ,shutter-speed effect' in human data. Retrospective analyses are made of clinical data chosen from a range of pathology (the active multiple sclerosis lesion, the invasive ductal carcinoma breast tumor, and osteosarcoma in the leg) that provides a wide variation, particularly of Ktrans. The signature temporal mismatch of the standard model is observed in all cases, and is essentially eliminated by use of the shutter-speed model. Pixel-by-pixel maps show that parameter values from the shutter-speed analysis are increased by more than a factor of 3 for some lesion regions. This endows the lesions with very high contrast, and reveals heterogeneities that are often not seen in the standard model maps. Normal muscle regions in the leg allow validation of the shutter-speed model Ktrans, ve, and ,i magnitudes, by comparison with results of previous careful rat leg studies not possible for human subjects. Copyright © 2004 John Wiley & Sons, Ltd. [source] | |||||||||||||