图式与英语听力理解

文章依据图式理论,探讨图式在英语听力理解中的预期作用、选择作用、推断作用和对记忆的组织作用。文章根据图式理论的启示对英语听力教学提出了相应的建议。     

青春期女性骨量峰值影响因素研究

女性最快速的骨量获得发生在青春早期至青春中期,青春晚期开始减退,青春期女性骨量峰值的高低与非生物力学因素和生物力学因素有关.非生物力学因素包括遗传、性别、钙的摄入、光照,烟酒嗜好等,生物力学因素是适量的运动,不同的运动方式,运动强度或持续时间不同对骨骼所起的作用也不一样.合理的体育运动可使青春期女性在生长期获得尽可能高的基础骨量,对提高其骨量峰值、预防骨量丢失和骨质疏松均具有非常重要的作用.     

Dominant edge direction based fast intra mode decision in the H.264/AVC encoder

The H.264/AVC video coding standard uses an intra prediction mode with 4×4 and 16×16 blocks for luma and 8×8 blocks for chroma. This standard uses the rate distortion optimization （RDO） method to determine the best coding mode based on the compression performance and video quality. This method offers a large improvement in coding efficiency compared to other compression standards, but the computational complexity is greater due to the various intra prediction modes. This paper proposes a fast intra mode decision algorithm for real-time encoding of H.264/AVC based on the dominant edge direction （DED）. The DED is extracted using pixel value summation and subtraction in the horizontal and vertical directions. By using the DED, three modes instead of nine are chosen for RDO calculation to decide on the best mode in the 4×4 luma block. For the 16×16 luma and the 8 × 8 chroma, only two modes are chosen instead of four. Experimental results show that the entire encoding time saving of the proposed algorithm is about 67% compared to the full intra search method with negligible loss of quality.     

基于 EMD-PSO-ELM 算法的大坝变形预测研究

基于极限学习机（ELM）构建的大坝变形预测模型易受连接权值、隐含层阈值及隐含层节点数影响,为获取更优的形变预测值,并改善模型预测可靠性,构建一种基于 EMD-PSO-ELM 算法,考虑时效、温度、水位等多因素的大坝变形预测模型。该模型首先从时频分析出发,利用经验模态分解（EMD）将变形时间序列分解成具有不同频率特征的分量|然后利用 PSO-ELM 模型解求形变预测值,重构获得大坝形变趋势。实验结果表明,融合时效、温度、水位等多因素的 EMD-PSO-ELM 大坝变形预测模型残差均方根误差为 1.83mm,平均绝对误差为 1.57mm,平均绝对百分比误差为 1.79%,比 ELM 模型与 EMD-ELM 模型相关误差值更小,在大坝变形预测方面性能更优。     

对称铣削系统协同运动位姿误差预测与补偿算法

针对对称铣削系统在加工过程中会出现协同位姿误差的问题,提出一种考虑温度变化的对称铣削系统协同位姿误差预测与补偿方法。在恒温条件下,将对称铣削系统的工作空间划分为平动轴运动空间和旋转轴运动空间,提出一种在采样点误差已知情况下的误差预测算法|在变温条件下,通过测量分析对称铣削系统的热误差,提出一种能够快速确定任意温度下系统误差的方法。在误差补偿方面,提出一种递归算法补偿系统误差,并在对称铣削系统上进行实验。结果表明,在恒温条件下,补偿后的协同位置精度及姿态精度分别提高了78.42%和 57.03% ,在变温条件下分别提高了 79.14%和 62.79%,验证了该算法的有效性。     

基于优化BP网络的类矩形盾构偏心刀盘故障预测

为实时监控类矩形盾构偏心刀盘工作状态,提出一种基于遗传算法（GA）优化BP神经网络模型的在线故障预测方法。首先,利用现场检测的相关测量数据,建立“特征—故障”数据集;然后,利用最优权值与阈值由遗传算法获取的BP神经网络对数据集进行自我学习,构建工作期故障预测模型;最后,开发偏心刀盘监控系统,对刀盘工作状态进行在线预测。实验结果表明,GA-BP网络模型预测准确率达到93.3%,与传统BP网络模型相比提高6%。基于GA-BP网络的偏心刀盘在线故障预测方法可精准预测刀盘工作状态,满足应用设计要求,为盾构施工安全提供有力保障。     

Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults

Abstract

The maximal fat oxidation (MFO), and the exercise intensity that elicits MFO (Fat_max), are considered excellent markers of fat metabolism during exercise. Besides individual’s biological characteristics (e.g. fed state, physical fitness level, sex, or age), data selection and analysis can affect MFO and Fatmax estimations, yet the effect is unknown. We investigated (i) the impact of using a pre-defined time interval on MFO and Fat_max estimation, and (ii) the impact of applying 2 different data analysis approaches (measured-values vs. polynomial-curve) on MFO and Fat_max estimations in sedentary adults. A total of 151 (97 women) sedentary adults aged 29.2?±?13.2 years old participated in the study. We assessed MFO and Fatmax through a walking graded exercise test using indirect calorimetry. We pre-defined 13 different time intervals for data analysis, and the estimation of MFO and Fat_max were performed through the measured-values and the polynomial-curve data analysis approaches. There were significant differences in MFO across pre-defined time intervals methods (P?<?0.001) applying measured-values data analysis approach, while no statistical differences were observed when using polynomial-curve data analysis approach (P?=?0.077). There were no differences in Fat_max across pre-defined time intervals independently of the data analysis approach (P?≥?0.7). We observed significant differences in MFO between measured-values and the polynomial-curve data analysis approaches across the time intervals methods selected (all P?≤?0.05), and no differences were observed in Fat_max (all P?≥?0.2). In conclusion, our results revealed that there are no differences in MFO and Fat_max across different time intervals methods selected using the polynomial-curve data analysis approach. We observed significant differences in MFO between measured-values vs. polynomial-curve data analysis approaches in all the study time intervals, whereas no differences were detected in Fatmax. Therefore, the use of polynomial-curve data analysis approach allows to compare MFO and Fat_max using different time intervals in sedentary adults.     

Caffeine supplementation and peak anaerobic power output

Abstract

The aim of this study was to investigate the effects of caffeine supplementation on peak anaerobic power output (W_max). Using a counterbalanced, randomised, double-blind, placebo-controlled design, 14 well-trained men completed three trials of a protocol consisting of a series of 6-s cycle ergometer sprints, separated by 5-min passive recovery periods. Sprints were performed at progressively increasing torque factors to determine the peak power/torque relationship and W_max. Apart from Trial 1 (familiarisation), participants ingested a capsule containing 5 mg·kg^?1 of caffeine or placebo, one hour before each trial. The effects of caffeine on blood lactate were investigated using capillary samples taken after each sprint. The torque factor which produced W_max was not significantly different (p ≥ 0.05) between the caffeine (1.15 ± 0.08 N·m·kg^?1) and placebo (1.13 ± 0.10 N·m·kg^?1) trials. There was, however, a significant effect (p < 0.05) of supplementation on W_max, with caffeine producing a higher value (1885 ± 303 W) than placebo (1835 ± 290 W). Analysis of the blood lactate data revealed a significant (p < 0.05) torque factor × supplement interaction with values being significantly higher from the sixth sprint (torque factor 1.0 N·m·kg^?1) onwards following caffeine supplementation. The results of this study confirm previous reports that caffeine supplementation significantly increases blood lactate and W_max. These findings may explain why the majority of previous studies, which have used fixed-torque factors of around 0.75 N·m·kg^?1 and thereby failing to elicit W_max, have failed to find an effect of caffeine on sprinting performance.     

Validation of a single-stage submaximal treadmill walking test

Abstract

The single-stage treadmill walking test of Ebbeling et al. is commonly used to predict maximal oxygen consumption ([Vdot]O_2max) from a submaximal effort between 50% and 70% of the participant's age-predicted maximum heart rate. The purpose of this study was to determine if this submaximal test correctly predicts [Vdot]O_2max at the low (50% of maximum heart rate) and high (70% of maximum heart rate) ends of the specified heart rate range for males and females aged 18 – 55 years. Each of the 34 participants completed one low-intensity and one high-intensity trial. The two trials resulted in significantly different estimates of [Vdot]O_2max (low-intensity trial: mean 40.5 ml · kg^?1 · min^?1, s = 9.3; high-intensity trial: 47.5 ml · kg^?1 · min^?1, s = 8.8; P < 0.01). A subset of 22 participants concluded their second trial with a [Vdot]O_2max test (mean 47.9 ml · kg^?1 · min^?1, s = 8.9). The low-intensity trial underestimated (mean difference = ?3.5 ml · kg^?1 · min^?1; 95% CI = ?6.4 to ?0.6 ml · kg^?1 · min^?1; P = 0.02) and the high-intensity trial overestimated (mean difference = 3.5 ml · kg^?1 · min^?1; 95% CI = 1.1 to 6.0 ml · kg^?1 · min^?1; P = 0.01) the measured [Vdot]O_2max. The predictive validity of Ebbeling and colleagues' single-stage submaximal treadmill walking test is diminished when performed at the extremes of the specified heart rate range.     

Comparison of different theoretical models estimating peak power output and maximal oxygen uptake in trained and elite triathletes and endurance cyclists in the velodrome

Abstract

The primary objective of this study was to examine the relationship between heart rate intensity and pedometer step counts in adolescents. To determine cardiorespiratory fitness, 106 participants (47 boys, 59 girls, mean age 14.2 years, s = 0.8) completed the Queen's College Step Test and were classified as having low, moderate or high cardiorespiratory fitness. Adolescents also completed a 10-min treadmill trial while wearing a pedometer and heart rate monitor. The participants were instructed to maintain their heart rate between 65 and 75% of their maximum heart rate while running or walking on a treadmill. A heart rate of 65–75% maximum was associated with 146 steps per minute (s = 22) in boys and 137 steps per minute (s = 22) in girls. Results of analysis of variance indicated that there was a main effect for level of fitness (F _2,102 = 9.36, P < 0.001). The correlation between mean steps per minute and estimated maximum oxygen consumption was statistically significant (r = 0.44, P < 0.001). The results from this study suggest that a step rate of 130 steps per minute is equal to 65–75% maximum heart rate in low-fit adolescents and achieving 130 steps per minute could be used as an initial goal to improve fitness.