306 resultados para Treadmill running


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Intense exercise stimulates the systemic release of a variety of factors that alter neutrophil surface receptor expression and functional activity. These alterations may influence resistance to infection after intense exercise. The aim of this study was to examine the influence of exercise intensity on neutrophil receptor expression, degranulation (measured by plasma and intracellular myeloperoxidase concentrations), and respiratory burst activity. Ten well-trained male runners ran on a treadmill for 60 min at 60% [moderate-intensity exercise (MI)] and 85% maximal oxygen consumption [high-intensity exercise (HI)]. Blood was drawn immediately before and after exercise and at 1 h postexercise. Immediately after HI, the expression of the neutrophil receptor CD16 was significantly below preexercise values (P < 0.01), whereas MI significantly reduced CD35 expression below preexercise values (P < 0.05). One hour after exercise at both intensities, there was a significant decline in CD11b expression (P < 0.05) and a further decrease in CD16 expression compared with preexercise values (P < 0.01). CD16 expression was lower 1 h after HI than 1 h after MI (P < 0.01). Immediately after HI, intracellular myeloperoxidase concentration was less than preexercise values (P < 0.01), whereas plasma myeloperoxidase concentration was greater (P < 0.01), indicating that HI stimulated neutrophil degranulation. Plasma myeloperoxidase concentration was higher immediately after HI than after MI (P < 0.01). Neutrophil respiratory burst activity increased after HI (P < 0.01). In summary, both MI and HI reduced neutrophil surface receptor expression. Although CD16 expression was reduced to a greater extent after HI, this reduction did not impair neutrophil degranulation and respiratory burst activity.

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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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Context: Very few authors have investigated the relationship between hip-abductor muscle strength and frontal-plane knee mechanics during running. Objective: To investigate this relationship using a 3-week hip-abductor muscle-strengthening program to identify changes in strength, pain, and biomechanics in runners with patellofemoral pain syndrome (PFPS). Design: Cohort study. Setting: University-based clinical research laboratory. Patients or Other Participants: Fifteen individuals (5 men, 10 women) with PFPS and 10 individuals without PFPS (4 men, 6 women) participated. Intervention(s): The patients with PFPS completed a 3-week hip-abductor strengthening protocol; control participants did not. Main Outcome Measure(s): The dependent variables of interest were maximal isometric hip-abductor muscle strength, 2-dimensional peak knee genu valgum angle, and stride-to-stride knee-joint variability. All measures were recorded at baseline and 3 weeks later. Between-groups differences were compared using repeated-measures analyses of variance. Results: At baseline, the PFPS group exhibited reduced strength, no difference in peak genu valgum angle, and increased stride-to-stride knee-joint variability compared with the control group. After the 3-week protocol, the PFPS group demonstrated increased strength, less pain, no change in peak genu valgum angle, and reduced stride-to-stride knee-joint variability compared with baseline. Conclusions: A 3-week hip-abductor muscle-strengthening protocol was effective in increasing muscle strength and decreasing pain and stride-to-stride knee-joint variability in individuals with PFPS. However, concomitant changes in peak knee genu valgum angle were not observed.

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The aim of this work is to develop software that is capable of back projecting primary fluence images obtained from EPID measurements through phantom and patient geometries in order to calculate 3D dose distributions. In the first instance, we aim to develop a tool for pretreatment verification in IMRT. In our approach, a Geant4 application is used to back project primary fluence values from each EPID pixel towards the source. Each beam is considered to be polyenergetic, with a spectrum obtained from Monte Carlo calculations for the LINAC in question. At each step of the ray tracing process, the energy differential fluence is corrected for attenuation and beam divergence. Subsequently, the TERMA is calculated and accumulated to an energy differential 3D TERMA distribution. This distribution is then convolved with monoenergetic point spread kernels, thus generating energy differential 3D dose distributions. The resulting dose distributions are accumulated to yield the total dose distribution, which can then be used for pre-treatment verification of IMRT plans. Preliminary results were obtained for a test EPID image comprised of 100 9 100 pixels of unity fluence. Back projection of this field into a 30 cm9 30 cm 9 30 cm water phantom was performed, with TERMA distributions obtained in approximately 10 min (running on a single core of a 3 GHz processor). Point spread kernels for monoenergetic photons in water were calculated using a separate Geant4 application. Following convolution and summation, the resulting 3D dose distribution produced familiar build-up and penumbral features. In order to validate the dose model we will use EPID images recorded without any attenuating material in the beam for a number of MLC defined square fields. The dose distributions in water will be calculated and compared to TPS predictions.

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Video presented as part of Smart Services CRC Participants conferences. This video is a demonstration of a 3D visualisation of a running workflow in YAWL connected by a custom service to Second Life. The avatar, Clik, is being controlled by a workflow tool called YAWL, as it traverses the workflow schema, illustrating the process of film preproduction and shooting. This video was captured while the workflow tool was running - NO human is controlling the avatar during the video. It is all scripted from an external source on the Internet. See www.bpmve.org for more on this work.

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Introduction: Lower limb function in hurdling is patently asymmetrical. The lead limb undertakes the preparatory and landing steps while the trail limb contends with the hurdle and recovery steps. Discrete loading profiles of these steps will reflect the asymmetrical function and may provide useful insight into injury mechanisms. A pilot study was undertaken to determine the loading profiles of the hurdle, landing and recovery steps of elite male hurdlers. Equivalent data for steps between hurdles, where the running action is more symmetrical, were used for the purpose of comparison, simultaneously minimising the confounding effect of speed. Methodology: In-shoe pressures were recorded (FScan, 200 Hz) for four elite male hurdlers while they completed a routine hurdle drill at a self-selected fast but sub-race speed. The drill comprised of three consecutive hurdles. Data for the hurdle, landing and recovery steps of the first and second hurdles, along with data for the running steps between hurdles 1 and 2, and 2 and 3, were used for the purpose of analysis. Peak pressures within 1cm2 masks were determined for the hallux, first, central and fifth metatarsals (T1, M1, M2–4 and M5 respectively). Peak pressure (kPa) and loading duration (ms) for the hurdle, landing and recovery steps are reported as a percentage of the respective limb-matched values for between-hurdle steps. Results/discussion: For between-hurdle steps, T1, M1 and M2–4 peak pressures were 312/357, 356/306 and 362/368 kPa, lead/trail limbs respectively. For the hurdle, landing and recovery steps, pressures at T1 and M1 increased. For T1 the increases were in the order of 17%, 36% and 8% (hurdle, landing and recovery steps, respectively) while the corresponding increases at M1 were 7%, 54% and 20%. Pressures at M2–4 were similar for all steps, while M5 loaded erratically. For the between-hurdle steps, the loading durations at T1, M1 and M2–4, were 160/162, 170/142 and 190/191 ms, respectively. For the landing step, loading duration decreased for T1, M1and M2–4 (−8%, −19% and −18%, respectively). In the hurdle step, loading duration decreased for the metatarsals but not for T1. Conclusions: The hurdling action leads to regional pressure increases that act for shorter durations in comparison to the between-hurdle running steps. These changes are most notable at the first metatarsal, a common site of foot injury.

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Neutrophils serve as an intriguing model for the study of innate immune cellular activity induced by physiological stress. We measured changes in the transcriptome of circulating neutrophils following an experimental exercise trial (EXTRI) consisting of 1 h of intense cycling immediately followed by 1 h of intense running. Blood samples were taken at baseline, 3 h, 48 h, and 96 h post-EXTRI from eight healthy, endurance-trained, male subjects. RNA was extracted from isolated neutrophils. Differential gene expression was evaluated using Illumina microarrays and validated with quantitative PCR. Gene set enrichment analysis identified enriched molecular signatures chosen from the Molecular Signatures Database. Blood concentrations of muscle damage indexes, neutrophils, interleukin (IL)-6 and IL-10 were increased (P < 0.05) 3 h post-EXTRI. Upregulated groups of functionally related genes 3 h post-EXTRI included gene sets associated with the recognition of tissue damage, the IL-1 receptor, and Toll-like receptor (TLR) pathways (familywise error rate, P value < 0.05). The core enrichment for these pathways included TLRs, low-affinity immunoglobulin receptors, S100 calcium binding protein A12, and negative regulators of innate immunity, e.g., IL-1 receptor antagonist, and IL-1 receptor associated kinase-3. Plasma myoglobin changes correlated with neutrophil TLR4 gene expression (r = 0.74; P < 0.05). Neutrophils had returned to their nonactivated state 48 h post-EXTRI, indicating that their initial proinflammatory response was transient and rapidly counterregulated. This study provides novel insight into the signaling mechanisms underlying the neutrophil responses to endurance exercise, suggesting that their transcriptional activity was particularly induced by damage-associated molecule patterns, hypothetically originating from the leakage of muscle components into the circulation.

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Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

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The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

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Background: Few longitudinal studies have examined the mental health outcomes of women after abortion and the results are controversial. Despite falling birth rates, teenage pregnancies remain high and over half (53%) of teenage and a third (36%) of young adult (20_24 years) pregnancies are aborted. Recent findings from a NewZealand longitudinal birth cohort linked abortion and subsequent psychiatric disorders in young women. Limited Australian data is available examining this association. Methods: Data were taken from the Mater-University Study of Pregnancy (MUSP). Running since 1981, this is a prospective birth cohort study of 7223 mothers and children. At the 21-year follow-up 3775 (52.3% of the original cohort) participants were surveyed, of these 1132 young women had complete data on pregnancy outcomes and psychiatric diagnoses from a structured interview. Binary logistic regression examined the association between five lifetime psychiatric disorders (nicotine, alcohol, cannabis, affective and anxiety disorders) and ever having an abortion or birth. Analyses adjusted for age, concurrent and maternal sociodemographic factors, and factors related to adolescent behaviour, previous mental health and family functioning. Results: A quarter of the young women (n_261) reported at least one pregnancy and 32.6% had an abortion. Abortion was significantly associated with age-adjusted OR for all the lifetime disorders. After full adjustment abortion remained significantly associated with nicotine (OR_2.1, 1.2_3.6) and alcohol disorders (OR_2.0, 1.3_3.3). Conclusion: The findings suggest that abortion in young women is independently associated with an increased risk of nicotine and alcohol disorders.

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The invention relates to a method for monitoring user activity on a mobile device, comprising an input and an output unit, comprising the following steps preferably in the following order: detecting and / or logging user activity on said input unit, identifying a foreground running application, hashing of a user-interface-element management list of the foreground running application, and creating a screenshot comprising items displayed on said input unit. The invention also relates to a method for analyzing user activity at a server, comprising the following step: obtaining at least one of an information about detected and / or logged user activity, an information about a foreground running application, a hashed user-interface-element management list and a screenshot from a mobile device. Further, a computer program product is provided, comprising one or more computer readable media having computer executable instructions for performing the steps of at least one of the aforementioned methods.

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XRD (X-ray diffraction), XRF (X-ray fluorescence), TG (thermogravimetry), FT-IES (Fourier transform infrared emission spectroscopy), FESEM (field emission scanning electron microscope), TEM (transmission electron microscope) and nitrogen–adsorption–desorption analysis were used to characterize the composition and thermal evolution of the structure of natural goethite. The in situ FT-IES demonstrated the start temperature (250 °C) of the transformation of natural goethite to hematite and the thermodynamic stability of protohematite between 250 and 600 °C. The heated products showed a topotactic relationship to the original mineral based on SEM analysis. Finally, the nitrogen–adsorption–desorption isotherm provided the variation of surface area and pore size distribution as a function of temperature. The surface area displayed a remarkable increase up to 350 °C, and then decreased above this temperature. The significant increase in surface area was attributed to the formation of regularly arranged slit-shaped micropores running parallel to elongated direction of hematite microcrystal. The main pore size varied from 0.99 nm to 3.5 nm when heating temperature increases from 300 to 400 °C. The hematite derived from heating goethite possesses high surface area and favors the possible application of hematite as an adsorbent as well as catalyst carrier.

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It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

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The findings presented in this paper are part of a research project designed to provide a preliminary indication of the support needs of postdiagnosis women with breast cancer in remote and isolated areas in Queensland. This discussion will present data that focuses on the women’s expressed personal concerns. For participants in this research a diagnosis of breast cancer involves a confrontation with their own mortality and the possibility of a reduced life span. This is a definite life crisis, creating shock and needing considerable adjustment. Along with these generic issues the participants also articulated significant issues in relation to their experience as women in a rural setting. These concerns centred around worries about how their partner and families cope during their absences for treatment, the additional burden on the family of having to cope with running the property or farm during the participant’s absence or illness, added financial strain brought about by the cost of travel for treatment, maintenance of properties during absences, and problems created by time off from properties or self-employment. These findings accord with other reports of health and welfare services for rural Australian and the generic literature on psycho-oncology studies of breast cancer.

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Cross-Lingual Link Discovery (CLLD) is a new problem in Information Retrieval. The aim is to automatically identify meaningful and relevant hypertext links between documents in different languages. This is particularly helpful in knowledge discovery if a multi-lingual knowledge base is sparse in one language or another, or the topical coverage in each language is different; such is the case with Wikipedia. Techniques for identifying new and topically relevant cross-lingual links are a current topic of interest at NTCIR where the CrossLink task has been running since the 2011 NTCIR-9. This paper presents the evaluation framework for benchmarking algorithms for cross-lingual link discovery evaluated in the context of NTCIR-9. This framework includes topics, document collections, assessments, metrics, and a toolkit for pooling, assessment, and evaluation. The assessments are further divided into two separate sets: manual assessments performed by human assessors; and automatic assessments based on links extracted from Wikipedia itself. Using this framework we show that manual assessment is more robust than automatic assessment in the context of cross-lingual link discovery.