274 resultados para Sport Climbing mini artificial wall


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Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing Light gauge Steel Frame (LSF) wall systems made of 1.15 mm G500 steel studs and varying plasterboard and insulation configurations (cavity and external insulation) using full scale fire tests. Suitable finite element models of LSF walls were then developed and validated by comparing with test results. In this study, the validated finite element models of LSF wall panels subject to standard fire conditions were used in a detailed parametric study to investigate the effects of important parameters such as steel grade and thickness, plasterboard screw spacing, plasterboard lateral restraint, insulation materials and load ratio on their performance under standard fire conditions. Suitable equations were proposed to predict the time–temperature profiles of LSF wall studs with eight different plasterboard-insulation configurations, and used in the finite element analyses. Finite element parametric studies produced extensive fire performance data for the LSF wall panels in the form of load ratio versus time and critical hot flange (failure) temperature curves for eight wall configurations. This data demonstrated the superior fire performance of externally insulated LSF wall panels made of different steel grades and thicknesses. It also led to the development of a set of equations to predict the important relationship between the load ratio and the critical hot flange temperature of LSF wall studs. Finally this paper proposes a simplified method to predict the fire resistance rating of LSF walls based on the two proposed set of equations for the load ratio–hot flange temperature and the time–temperature relationships.

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The application of artificial neural networks (ANN) in finance is relatively new area of research. We employed ANNs that used both fundamental and technical inputs to predict future prices of widely held Australian stocks and used these predicted prices for stock portfolio selection over a 10-year period (2001-2011). We found that the ANNs generally do well in predicting the direction of stock price movements. The stock portfolios selected by the ANNs with median accuracy are able to generate positive alpha over the 10-year period. More importantly, we found that a portfolio based on randomly selected network configuration had zero chance of resulting in a significantly negative alpha but a 27% chance of yielding a significantly positive alpha. This is in stark contrast to the findings of the research on mutual fund performance where active fund managers with negative alphas outnumber those with positive alphas.

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A pulsed wall jet has been used to simulate the gust front of a thunderstorm downburst. Flow visualization, wind speed and surface pressure measurements were obtained. The characteristics of the hypothesized ring vortex of a full-scale downburst were reproduced at a scale estimated to be 1:3000.

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The Acacia Light Wall is a permanent public artwork within the 3 stage Eden on the Yarra – a residential / commercial development on Victoria Street Abbotsford, Melbourne. The work was commissioned by the Hampton Group for Acacia Place, the first building in the development. The stylised screen was inspired by tangled wattle trees (Australia’s most common Acacia). The work consists of two walls, made from laser cut aluminium screen, acrylic ‘windows” Philips Colour Kinetic controllable LED (1250 nodes), Philips Colour Kinetics control ‘iPlayers”. One wall is 10 m long x 3 to 5 metres and the second is 12m by 3m. The windows are lit by an array of 600+ LED’s in each wall. These lights change colour from week to week marking the progress of the seasons. We worked with the project horticulturalist to develop a palate of colours for each week’s ‘light show’ that was drawn from local flowers and foliage likely to be in bloom that week. The lighting display is not static but rather a very slow moving (morphing) light show. It isn’t fast and flashy. Instead it’s restful and profound.

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Tissue Engineering is a promising emerging field that studies the intrinsic regenerative potential of the human body and uses it to restore functionality of damaged organs or tissues unable of self-healing due to illness or ageing. In order to achieve regeneration using Tissue Engineering strategies, it is first necessary to study the properties of the native tissue and determine the cause of tissue failure; second, to identify an optimum population of cells capable of restoring its functionality; and third, to design and manufacture a cellular microenvironment in which those specific cells are directed towards the desired cellular functions. The design of the artificial cellular niche has a tremendous importance, because cells will feel and respond to both its biochemical and biophysical properties very differently. In particular, the artificial niche will act as a physical scaffold for the cells, allowing their three-dimensional spatial organization; also, it will provide mechanical stability to the artificial construct; and finally, it will supply biochemical and mechanical cues to control cellular growth, migration, differentiation and synthesis of natural extracellular matrix. During the last decades, many scientists have made great contributions to the field of Tissue Engineering. Even though this research has frequently been accompanied by vast investments during extended periods of time, yet too often these efforts have not been enough to translate the advances into new clinical therapies. More and more scientists in this field are aware of the need of rational experimental designs before carrying out complex, expensive and time-consuming in vitro and in vivo trials. This review highlights the importance of computer modeling and novel biofabrication techniques as critical key players for a rational design of artificial cellular niches in Tissue Engineering.

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We present a mini-scale method for nuclear run-on transcription assay. In our method, all the centrifuge steps can be carried out by using micro-tubes for short time (5 min each) throughout the process, including isolation of transcriptionally active nuclei and purification of labeled RNA after synthesis of RNA in isolated nuclei. The assay can be performed using a small amount of plant tissue, which enables analysis of developmental changes in transcriptional status of given genes in a single individual plant. Successful results were obtained using the tissues of flower and leaf of petunia and embryo of pea, suggesting that the method is potentially applicable to a variety of plant tissues.

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The purpose of this study was to evaluate the validity and inter-rater reliability of the Observation System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N=29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-sec observe, 20-sec record). Two observers simultaneously observed and recorded children's PA intensity, practice context, social context, coach behavior, and coach proximity. Inter-rater reliability was based on agreement (Kappa) between the observer's coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect inter-observer agreement (Κappa = 0.67 to 0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49 - 0.90). A significant correlation (r = 0.73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children's PA and contextual factors during a youth soccer practice.

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The suggested model for pro-matrix metalloproteinase-2 (proMMP-2) activation by membrane type 1 MMP (MT1-MMP) implicates the complex between MT1-MMP and tissue inhibitor of MMP-2 (TIMP-2) as a receptor for proMMP-2. To dissect this model and assess the pathologic significance of MMP-2 activation, an artificial receptor for proMMP-2 was created by replacing the signal sequence of TIMP-2 with cytoplasmic/transmembrane domain of type II transmembrane mosaic serine protease (MSP-T2). Unlike TIMP-2, MSP-T2 served as a receptor for proMMP-2 without inhibiting MT1-MMP, and generated TIMP-2-free active MMP-2 even at a low level of MT1-MMP. Thus, MSP-T2 did not affect direct cleavage of the substrate testican-1 by MT1-MMP, whereas TIMP-2 inhibited it even at the level that stimulates proMMP-2 processing. Expression of MSP-T2 in HT1080 cells enhanced MMP-2 activation by endogenous MT1-MMP and caused intensive hydrolysis of collagen gel. Expression of MSP-T2 in U87 glioma cells, which express a trace level of endogenous MT1-MMP, induced MMP-2 activation and enhanced cell-associated protease activity, activation of extracellular signal-regulated kinase, and metastatic ability into chick embryonic liver and lung. MT1-MMP can exert both maximum MMP-2 activation and direct cleavage of substrates with MSP-T2, which cannot be achieved with TIMP-2. These results suggest that MMP-2 activation by MT1-MMP potentially amplifies protease activity, and combination with direct cleavage of substrate causes effective tissue degradation and enhances tumor invasion and metastasis, which highlights the complex role of TIMP-2. MSP-T2 is a unique tool to analyze physiologic and pathologic roles of MMP-2 and MT1-MMP in comparison with TIMP-2.

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Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

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The purpose of this study was to determine the extent to which sport education can provide students with sufficient opportunities for developing moderate- to-vigorous physical activity (MVPA). Nineteen seventh-grade boys (average age = 12.9 yrs.) participated in a 22-lesson season of floor hockey. For all students (both higher and lower skilled), students averaged a total of 31.6 min of MVPA during the season, or 63.2% of lesson time. Further, there was no significant difference according to skill level (33.4 min [Higher] vs. 30.4 min [Lower]), nor were there any significant differences in MVPA levels across the phases of the season.

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It is demonstrated that a magnetic field has a profound effect on the length of a single-wall carbon nanotube (SWCNT) synthesized in the arc discharge. The average length of SWCNT increases by a factor of 2 in discharge with magnetic field as compared with the discharge without magnetic field, and the yield of long nanotubes with lengths above 5 μm also increases. A model of SWCNT growth on metal catalyst in arc plasma was developed. Monte-Carlo simulations confirm that the increase of the plasma density in the magnetic field leads to an increase in the nanotube growth rate and thus leads to longer nanotubes.

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This paper presents the fire performance results of light gauge steel frame (LSF) walls lined with single and double plasterboards, and externally insulated with rock fibre insulation as obtained using a finite element analysis based parametric study. A validated numerical model was used to study the influence of various fire curves developed for a range of compartment characteristics. Data from the parametric study was utilized to develop a simplified method to predict the fire resistance ratings of LSF walls exposed to realistic design fire curves. Further, this paper also presents the details of suitable fire design rules based on current cold-formed steel standards and the modifications proposed by previous researchers. Of these the recently developed design rules by Gunalan and Mahendran [1] were investigated to determine their applicability to predict the axial compression strengths and fire resistance ratings (FRR) of LSF walls exposed to realistic design fires. Finally, the stud failure times obtained from fire design rules and finite element studies were compared for LSF walls lined with single and double plasterboards, and externally insulated with rock fibres under realistic design fire curves.