976 resultados para damage detection


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We investigated the effects of an Ironman triathlon race on markers of muscle damage, inflammation and heat shock protein 70 (HSP70). Nine well-trained male triathletes (mean +/- SD age 34 +/- 5 years; VO(2peak) 66.4 ml kg(-1) min(-1)) participated in the 2004 Western Australia Ironman triathlon race (3.8 km swim, 180 km cycle, 42.2 km run). We assessed jump height, muscle strength and soreness, and collected venous blood samples 2 days before the race, within 30 min and 14-20 h after the race. Plasma samples were analysed for muscle proteins, acute phase proteins, cytokines, heat shock protein 70 (HSP70), and clinical biochemical variables related to dehydration, haemolysis, liver and renal functions. Muscular strength and jump height decreased significantly (P < 0.05) after the race, whereas muscle soreness and the plasma concentrations of muscle proteins increased. The cytokines interleukin (IL)-1 receptor antagonist, IL-6 and IL-10, and HSP70 increased markedly after the race, while IL-12p40 and granulocyte colony-stimulating factor (G-CSF) were also elevated. IL-4, IL-1beta and tumour necrosis factor-alpha did not change significantly, despite elevated C-reactive protein and serum amyloid protein A on the day after the race. Plasma creatinine, uric acid and total bilirubin concentrations and gamma-glutamyl transferase activity also changed after the race. In conclusion, despite evidence of muscle damage and an acute phase response after the race, the pro-inflammatory cytokine response was minimal and anti-inflammatory cytokines were induced. HSP70 is released into the circulation as a function of exercise duration.

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The purpose of this study was to compare the effects of exercise intensity and exercise-induced muscle damage on changes in anti-inflammatory cytokines and other inflammatory mediators. Nine well-trained male runners completed three different exercise trials on separate occasions: (1) level treadmill running at 60% VO2max (moderate-intensity trial) for 60 min; (2) level treadmill running at 85% VO2max (high-intensity trial) for 60 min; (3) downhill treadmill running (-10% gradient) at 60% VO2max (downhill running trial) for 45 min. Blood was sampled before, immediately after and 1 h after exercise. Plasma was analyzed for interleukin-1 receptor antagonist (IL-1ra), IL-4, IL-5, IL-10, IL-12p40, IL-13, monocyte chemotactic protein-1 (MCP-1), prostaglandin E(2), leukotriene B(4) and heat shock protein 70 (HSP70). The plasma concentrations of IL-1ra, IL-12p40, MCP-1 and HSP70 increased significantly (P<0.05) after all three trials. Plasma prostaglandin E(2) concentration increased significantly after the downhill running and high-intensity trials, while plasma IL-10 concentration increased significantly only after the high-intensity trial. IL-4 and leukotriene B(4) did not increase significantly after exercise. Plasma IL-1ra and IL-10 concentrations were significantly higher (P<0.05) after the high-intensity trial than after both the moderate-intensity and downhill running trials. Therefore, following exercise up to 1 h duration, exercise intensity appears to have a greater effect on anti-inflammatory cytokine production than exercise-induced muscle damage

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Introduction: Unaccustomed eccentric exercise often results in muscle damage and neutrophil activation. We examined changes in plasma cytokines stress hormones, creatine kinase activity and myoglobin concentration, neutrophil surface receptor expression, degranulation, and the capacity of neutrophils to generate reactive oxygen species in response to in vitro stimulation after downhill running. Methods: Ten well-trained male runners ran downhill on a treadmill at a gradient of -10% for 45 min at 60% V̇O2max. Blood was sampled immediately before (PRE) and after (POST), 1 h (1 h POST), and 24 h (24 h POST) after exercise. Results: At POST, there were significant increases (P < 0.01) in neutrophil count (32%), plasma interleukin (IL)-6 concentration (460%), myoglobin (Mb) concentration (1100%), and creatine kinase (CK) activity (40%). At 1 h POST, there were further increases above preexercise values for neutrophil count (85%), plasma Mb levels (1800%), and CK activity (56%), and plasma IL-6 concentration remained above preexercise values (410%) (P < 0.01). At 24 h POST, neutrophil counts and plasma IL-6 levels had returned to baseline, whereas plasma Mb concentration (100%) and CK activity (420%) were elevated above preexercise values (P < 0.01). There were no significant changes in neutrophil receptor expression, degranulation and respiratory burst activity, and plasma IL-8 and granulocyte-colony stimulating factor concentrations at any time after exercise. Neutrophil count correlated with plasma Mb concentration at POST (r = 0.64, P < 0.05), and with plasma CK activity at POST (r = 0.83, P < 0.01) and 1 h POST (r = 0.78, P < 0.01). Conclusion: Neutrophil activation remains unchanged after downhill running in well-trained runners, despite increases in plasma markers of muscle damage.

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This paper presents a study whereby a series of tests was undertaken using a naturally aspirated 4 cylinder, 2.216 litre, Perkins Diesel engine fitted with a piston having an undersized skirt. This experimental simulation resulted in engine running conditions that included abnormally high levels of piston slap occurring in one of the cylinders. The detectability of the resultant Diesel engine piston slap was investigated using acoustic emission signals. Data corresponding to both normal and piston slap engine running conditions was captured using acoustic emission transducers along with both; in-cylinder pressure and top-dead centre reference signals. Using these signals it was possible to demonstrate that the increased piston slap running conditions were distinguishable by monitoring the piston slap events occurring near the piston mid-stroke positions. However, when monitoring the piston slap events occurring near the TDC/BDC piston stroke positions, the normal and excessive piston slap engine running condition were not clearly distinguishable.

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Anisotropic damage distribution and evolution have a profound effect on borehole stress concentrations. Damage evolution is an irreversible process that is not adequately described within classical equilibrium thermodynamics. Therefore, we propose a constitutive model, based on non-equilibrium thermodynamics, that accounts for anisotropic damage distribution, anisotropic damage threshold and anisotropic damage evolution. We implemented this constitutive model numerically, using the finite element method, to calculate stress–strain curves and borehole stresses. The resulting stress–strain curves are distinctively different from linear elastic-brittle and linear elastic-ideal plastic constitutive models and realistically model experimental responses of brittle rocks. We show that the onset of damage evolution leads to an inhomogeneous redistribution of material properties and stresses along the borehole wall. The classical linear elastic-brittle approach to borehole stability analysis systematically overestimates the stress concentrations on the borehole wall, because dissipative strain-softening is underestimated. The proposed damage mechanics approach explicitly models dissipative behaviour and leads to non-conservative mud window estimations. Furthermore, anisotropic rocks with preferential planes of failure, like shales, can be addressed with our model.

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Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

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In eukaryotes, genomic DNA is tightly compacted into a protein-DNA complex known as chromatin. This dense structure presents a barrier to DNA-dependent processes including transcription, replication and DNA repair. The repressive structure of chromatin is overcome by ATP-dependent chromatin remodelling complexes and chromatin-modifying enzymes. There is now ample evidence that DNA double-strand breaks (DSBs) elicit various histone modifications (such as acetylation, deacetylation, and phosphorylation) that function combinatorially to control the dynamic structure of the chromatin microenvironment. The role of these mechanisms during transcription and replication has been well studied, while the research into their impact on regulation of DNA damage response is rapidly gaining momentum. How chromatin structure is remodeled in response to DNA damage and how such alterations influence DSB repair are currently significant questions. This review will summarise the major chromatin modifications and chromatin remodelling complexes implicated in the DNA damage response to DSBs.

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Monitoring fetal wellbeing is a compelling problem in modern obstetrics. Clinicians have become increasingly aware of the link between fetal activity (movement), well-being, and later developmental outcome. We have recently developed an ambulatory accelerometer-based fetal activity monitor (AFAM) to record 24-hour fetal movement. Using this system, we aim at developing signal processing methods to automatically detect and quantitatively characterize fetal movements. The first step in this direction is to test the performance of the accelerometer in detecting fetal movement against real-time ultrasound imaging (taken as the gold standard). This paper reports first results of this performance analysis.

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This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

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This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating correspond- ing velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

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Here we report an ultrasensitive method for detecting bio-active compounds in biological samples by means of functionalised nanoparticles interrogated by surface enhanced Raman spectroscopy (SERS). This method is applicable to the recovery and detection of many diagnostically important peptidyl analytes such as insulin, human growth hormone, growth factors (IGFs) and erythropoietin (EPO), as well as many small molecule analytes and metabolites. Our method, developed to detect EPO, demonstrates its utility in a complex yet well defined biological system. Recombinant human EPO (rhEPO) and EPO analogues have successfully been used to treat anaemia in end-stage renal failure, chronic disorders and infections, cancer and AIDS. Current methods for EPO testing are lengthy, laborious and relatively insensitive to low concentrations. In our rapid screening methodology, gold nanoparticles were functionalised with anti-EPO antibodies to provide very high selectivity towards the EPO protein in urine. These “smart sensor” nanoparticles interact with and trap EPO. Subsequent SERS screening allows for the detection and quantisation of ultra trace amounts (<<10-15 M) of EPO in urine samples with minimal sample preparation. We present data showing that the SERS spectrum differentiates between human endogenous EPO and rhEPO in unpurified urine, and potentially distinguishes between purified EPO isoforms. The elimination of sample preparation and direct screening in biological fluids significantly reduces the time required by current methods. Antibody recognition against a variety of biological targets and the availability of portable commercial SERS analysers for rapid onsite testing suggest broad diagnostic applicability in a flexible analytical platform.

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The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

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BACKGROUND: Epidemiologic research has demonstrated that cutaneous markers of photo-damage are associated with risk of basal cell carcinoma (BCC). However there has been no previous attempt to calculate pooled risk estimates. METHODS: We conducted a systematic review and meta-analysis after extracting relevant studies published up to January 2013 from five electronic databases. Eligible studies were those that permitted quantitative assessment of the association between histologically-confirmed BCC and actinic keratoses, solar elastosis, solar lentigines, or telangiectasia. RESULTS: Seven eligible studies were identified and summary odds ratios (OR) were calculated using both random and quality effects models. Having more than ten actinic keratoses was most strongly associated with BCC, conferring up to a 5-fold increase in risk (OR: 4.97; 95% CI: 3.26, 7.58). Other factors, including solar elastosis, solar lentigines, and telangiectasia had weaker but positive associations with BCC with ORs around 1.5. CONCLUSIONS: Markers of chronic photo-damage are positively associated with BCC. The presence of actinic keratoses was the most strongly associated with BCC of the markers examined. IMPACT: This work highlights the relatively modest association between markers of chronic ultraviolet exposure and BCC.

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This paper presents two algorithms to automate the detection of marine species in aerial imagery. An algorithm from an initial pilot study is presented in which morphology operations and colour analysis formed the basis of its working principle. A second approach is presented in which saturation channel and histogram-based shape profiling were used. We report on performance for both algorithms using datasets collected from an unmanned aerial system at an altitude of 1000 ft. Early results have demonstrated recall values of 48.57% and 51.4%, and precision values of 4.01% and 4.97%.

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Monitoring and estimation of marine populations is of paramount importance for the conservation and management of sea species. Regular surveys are used to this purpose followed often by a manual counting process. This paper proposes an algorithm for automatic detection of dugongs from imagery taken in aerial surveys. Our algorithm exploits the fact that dugongs are rare in most images, therefore we determine regions of interest partially based on color rarity. This simple observation makes the system robust to changes in illumination. We also show that by applying the extended-maxima transform on red-ratio images, submerged dugongs with very fuzzy edges can be detected. Performance figures obtained here are promising in terms of degree of confidence in the detection of marine species, but more importantly our approach represents a significant step in automating this type of surveys.