995 resultados para Monitoring, Physiologic


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Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

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Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

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Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

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Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

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This thesis increased the researchers understanding of the relationship between operations and maintenance in underground longwall coal mines, using data from a Queensland underground coal mine. The thesis explores various relationships between recorded variables. Issues with human recorded data was uncovered, and results emphasised the significance of variables associated with conveyor operation to explain production.

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Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

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Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

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Time reversal active sensing using Lamb waves is investigated for health monitoring of a metallic structure. Experiments were conducted on an aluminum plate to study the time reversal behavior of A(0) and S-0 Lamb wave modes under narrow band and broad band pulse excitation. Damage in the form of a notch was introduced in the plate to study the changes in the characteristics of the time reversed Lamb wave modes experimentally. Time-frequency analysis of the time reversed signal was carried out to extract the damage information. A measure of damage based on wavelet transform was derived to quantify the hidden damage information in the time reversed signal. It has been shown that time reversal can be used to achieve temporal recompression of Lamb waves under broadband signal excitation. Further, the broad band excitation can also improve the resolution of the technique in detecting closely located defects. This is demonstrated by picking up the reflection of waves from the edge of the plate, from a defect close to the edge of the plate and from defects located near to each other. This study shows the effectiveness of Lamb wave time reversal for temporal recompression of dispersive Lamb waves for damage detection in health monitoring applications. (C) 2009 Elsevier B.V. All rights reserved.

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In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

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Background: The fecal neutrophil-derived proteins calprotectin and lactoferrin have proven useful surrogate markers of intestinal inflammation. The aim of this study was to compare fecal calprotectin and lactoferrin concentrations to clinically, endoscopically, and histologically assessed Crohn’s disease (CD) activity, and to explore the suitability of these proteins as surrogate markers of mucosal healing during anti-TNFα therapy. Furthermore, we studied changes in the number and expression of effector and regulatory T cells in bowel biopsy specimens during anti-TNFα therapy. Patients and methods: Adult CD patients referred for ileocolonoscopy (n=106 for 77 patients) for various reasons were recruited (Study I). Clinical disease activity was assessed with the Crohn’s disease activity index (CDAI) and endoscopic activity with both the Crohn’s disease index of severity (CDEIS) and the simple endoscopic score for Crohn’s disease (SES-CD). Stool samples for measurements of calprotectin and lactoferrin, and blood samples for CRP were collected. For Study II, biopsy specimens were obtained from the ileum and the colon for histologic activity scoring. In prospective Study III, after baseline ileocolonoscopy, 15 patients received induction with anti-TNFα blocking agents and endoscopic, histologic, and fecal-marker responses to therapy were evaluated at 12 weeks. For detecting changes in the number and expression of effector and regulatory T cells, biopsy specimens were taken from the most severely diseased lesions in the ileum and the colon (Study IV). Results: Endoscopic scores correlated significantly with fecal calprotectin and lactoferrin (p<0.001). Both fecal markers were significantly lower in patients with endoscopically inactive than with active disease (p<0.001). In detecting endoscopically active disease, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for calprotectin ≥200 μg/g were 70%, 92%, 94%, and 61%; for lactoferrin ≥10 μg/g they were 66%, 92%, 94%, and 59%. Accordingly, the sensitivity, specificity, PPV, and NPV for CRP >5 mg/l were 48%, 91%, 91%, and 48%. Fecal markers were significantly higher in active colonic (both p<0.001) or ileocolonic (calprotectin p=0.028, lactoferrin p=0.004) than in ileal disease. In ileocolonic or colonic disease, colon histology score correlated significantly with fecal calprotectin (r=0.563) and lactoferrin (r=0.543). In patients receiving anti-TNFα therapy, median fecal calprotectin decreased from 1173 μg/g (range 88-15326) to 130 μg/g (13-1419) and lactoferrin from 105.0 μg/g (4.2-1258.9) to 2.7 μg/g (0.0-228.5), both p=0.001. The relation of ileal IL-17+ cells to CD4+ cells decreased significantly during anti-TNF treatment (p=0.047). The relation of IL-17+ cells to Foxp3+ cells was higher in the patients’ baseline specimens than in their post-treatment specimens (p=0.038). Conclusions: For evaluation of CD activity, based on endoscopic findings, more sensitive surrogate markers than CDAI and CRP were fecal calprotectin and lactoferrin. Fecal calprotectin and lactoferrin were significantly higher in endoscopically active disease than in endoscopic remission. In both ileocolonic and colonic disease, fecal markers correlated closely with histologic disease activity. In CD, these neutrophil-derived proteins thus seem to be useful surrogate markers of endoscopic activity. During anti-TNFα therapy, fecal calprotectin and lactoferrin decreased significantly. The anti-TNFα treatment was also reflected in a decreased IL-17/Foxp3 cell ratio, which may indicate improved balance between effector and regulatory T cells with treatment.

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Thrombin is a multifunctional protease, which has a central role in the development and progression of coronary atherosclerotic lesions and it is a possible mediator of myocardial ischemia-reperfusion injury. Its generation and procoagulant activity are greatly upregulated during cardiopulmonary bypass (CPB). On the other hand, activated protein C, a physiologic anticoagulant that is activated by thrombomodulin-bound thrombin, has been beneficial in various models of ischemia-reperfusion. Therefore, our aim in this study was to test whether thrombin generation or protein C activation during coronary artery bypass grafting (CABG) associate with postoperative myocardial damage or hemodynamic changes. To further investigate the regulation of thrombin during CABG, we tested whether preoperative thrombophilic factors associate with increased CPB-related generation of thrombin or its procoagulant activity. We also measured the anticoagulant effects of heparin during CPB with a novel coagulation test, prothrombinase-induced clotting time (PiCT), and compared the performance of this test with the present standard of laboratory-based anticoagulation monitoring. One hundred patients undergoing elective on-pump CABG were studied prospectively. A progressive increase in markers of thrombin generation (F1+2), fibrinolysis (D-dimer), and fibrin formation (soluble fibrin monomer complexes) was observed during CPB, which was further distinctly propagated by reperfusion after myocardial ischemia, and continued to peak after the neutralization of heparin with protamine. Thrombin generation during reperfusion after CABG associated with postoperative myocardial damage and increased pulmonary vascular resistance. Activated protein C levels increased only slightly during CPB before the release of the aortic clamp, but reperfusion and more significantly heparin neutralization caused a massive increase in activated protein C levels. Protein C activation was clearly delayed in relation to both thrombin generation and fibrin formation. Even though activated protein C associated dynamically with postoperative hemodynamic performance, it did not associate with postoperative myocardial damage. Preoperative thrombophilic variables did not associate with perioperative thrombin generation or its procoagulant activity. Therefore, our results do not favor routine thrombophilia screening before CABG. There was poor agreement between PiCT and other measurements of heparin effects in the setting of CPB. However, lower heparin levels during CPB associated with inferior thrombin control and high heparin levels during CPB associated with fewer perioperative transfusions of blood products. Overall, our results suggest that hypercoagulation after CABG, especially during reperfusion, might be clinically important.

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The mass spectrometry technique of multiple reaction monitoring (MRM) was used to quantify and compare the expression level of lactoferrin in tear films among control, prostate cancer (CaP), and benign prostate hyperplasia (BPH) groups. Tear samples from 14 men with CaP, 15 men with BPH, and 14 controls were analyzed in the study. Collected tears (2 μl) of each sample were digested with trypsin overnight at 37 °C without any pretreatment, and tear lactoferrin was quantified using a lactoferrin-specific peptide, VPSHAVVAR, both using natural/light and isotopic-labeled/heavy peptides with MRM. The average tear lactoferrin concentration was 1.01 ± 0.07 μg/μl in control samples, 0.96 ± 0.07 μg/μl in the BPH group, and 0.98 ± 0.07 μg/μl in the CaP group. Our study is the first to quantify tear proteins using a total of 43 individual (non-pooled) tear samples and showed that direct digestion of tear samples is suitable for MRM studies. The calculated average lactoferrin concentration in the control group matched that in the published range of human tear lactoferrin concentration measured by enzyme-linked immunosorbent assay (ELISA). Moreover, the lactoferrin was stably expressed across all of the samples, with no significant differences being observed among the control, BPH, and CaP groups.