The Effects of FIT Taijipao on Heart Rate: A Case Study

As an American College of Sports Medicine (ACSM) initiative known as Exercise Is Medicine (EIM) is becoming more and more popular globally, FIT Taijipao has been proposed as a new approach to exercise. FIT Taijipao has been introduced as an individualized and dynamic exercise. The purpose of this study was to examine the effects of FIT Taijipao on Heart Rate (HR) at different speeds including peak (YANG) and minimum (YIN) points every three months across 15 months of continuous FIT Taijipao exercise, concluding with a follow-up retention test to examine the effects of an 18-month detraining. The participant of the case study was recruited in a college-wide mind & health program. A 48-year-old sedentary Asian female volunteered for this pilot longitudinal study. The participant performed FIT Taijipao on a treadmill two to three times per week in the exercise lab. A Polar HR Monitor (M400 + H10 chest unit) was used to record HR data. According to FIT Taijipao guidelines, HR Average per 200m was used for data analysis. The Borg Rating of Perceived Exertion (RPE) scale was used to monitor the participant’s subjective effort and controlled to be no higher than 15. YANG Speed (peak) is attained as RPE reaches 15 or less when HR reaches 145 bpm. The running speed was adjusted according to FIT Taijipao established speed profile. Weekly HR average of YANG (peak) speed decreased by 25.3 bpm (146.3 to 121.0 bpm) after first 3 months of FIT Taijipao; Weekly HR average at the same speed continuously decreased to 117.3, 120.0, 116.0, and 116.3 bpm at 4.5 mph speed. YANG (peak) speed increased gradually from 4.5 mph, to 5.7, 6.0, 6.1, 6.3, and 6.3 mph every three months. After 18 months of detraining, a retention FIT Taijipao test was done to examine the HR change. Weekly HR average at 6.3 mph was 160.6 bpm, and the lap average speed was 5.7 mph when HR was around 145 bpm. The RPE reported was 13. This case study illustrates that regular FIT Taijipao leads to a decreased HR, a useful index for exercise intensity and cardio-respiratory fitness. The participant enjoyed FIT Taijipao, a 40-45 minutes run. FIT Taijipao has a great potential to help general population to gain the benefits of exercise and physical activity without being over stressed

Developing Sustainable Snow Sports Education Programs for Adolescent Participation

Following Beijing’s winning bid to host the 2022 Winter Olympic Games, winter sports have ushered in a great development opportunity for adolescents in China. Beijing initiated the Ice and Snow Sports on Campus Program in 2016, however, one of the challenges is that the lack of quality snow sports instructors and access to ski resorts is limiting sustainable programs. Greek Peak Ski Resort, located in upstate NY, has a successful history of running snow sport educational programs that Beijing may be able to learn from. The purpose of this study was to assess and compare the Ice and Snow Sports on Campus Program in Beijing with the snow sports programs at Greek Peak Ski Resort, having a goal to explore sustainable education programs for adolescents. Literature research, program reports, field observation, and interviews with program directors and experts were used in this study to assess and compare the programs in Beijing and Greek Peak Ski Resort. The findings indicated that with the Ice and Snow Sports on Campus Program initiated in 2016 by the Beijing Municipal Education Commission, about 2.1 million K-12 students’ participation counts in ice and snow sports have been recorded. In 2021, more than 200 K-12 schools with ice and snow sports specialties were certified in Beijing. A total of 60 model courses with the topic in winter sports and Olympics have been developed to improve ice and snow sports teaching. The strong and historical school skiing program at Greek Peak Ski Resort includes about 55-57 K-12 school programs and 5 college PE programs each year, with an estimated student participation count of 20,000 per year. The collaboration between Greek Peak Ski Resort and local schools/ colleges/universities offers sustainable educational programs, benefitting generations of students and all parties involved and efficiently sharing resources. The 2022 Beijing Winter Olympics provides a rare historical opportunity for multi-level and multi-dimensional cooperation between the sports and educational departments in Beijing. With supporting policies and guidance, the strategic goal of cultivating more young people to participate in winter sports is being achieved. Education programs provide opportunities for adolescents to learn winter sports skills and promote active healthy behavior. The collaboration between local schools, colleges/universities and Greek Peak Resort can be a good solution for Beijing to resolve the critical challenge of lack of quality instructors and easy access to winter sports facilities

Exploring Asymmetric Tunable Blind-Spots for Self-supervised Denoising in Real-World Scenarios

Self-supervised denoising has attracted widespread attention due to its ability to train without clean images. However, noise in real-world scenarios is often spatially correlated, which causes many self-supervised algorithms based on the pixel-wise independent noise assumption to perform poorly on real-world images. Recently, asymmetric pixel-shuffle downsampling (AP) has been proposed to disrupt the spatial correlation of noise. However, downsampling introduces aliasing effects, and the post-processing to eliminate these effects can destroy the spatial structure and high-frequency details of the image, in addition to being time-consuming. In this paper, we systematically analyze downsampling-based methods and propose an Asymmetric Tunable Blind-Spot Network (AT-BSN) to address these issues. We design a blind-spot network with a freely tunable blind-spot size, using a large blind-spot during training to suppress local spatially correlated noise while minimizing damage to the global structure, and a small blind-spot during inference to minimize information loss. Moreover, we propose blind-spot self-ensemble and distillation of non-blind-spot network to further improve performance and reduce computational complexity. Experimental results demonstrate that our method achieves state-of-the-art results while comprehensively outperforming other self-supervised methods in terms of image texture maintaining, parameter count, computation cost, and inference time

Development and Control of Soybean Aphid, Aphis glycines, in Heilongjiang Province

Originating text in Chinese.Citation: Wang, Chunrong, Chen, Jiguang, Guo, Yuren, Gong, Xiangyu, Xu, Zhaofei, Lin, Chao. (1998). Development and Control of Soybean Aphid, Aphis glycines, in Heilongjiang Province. Soybean Bulletin, 6, 15

A Novel Noise Injection-based Training Scheme for Better Model Robustness

Noise injection-based method has been shown to be able to improve the robustness of artificial neural networks in previous work. In this work, we propose a novel noise injection-based training scheme for better model robustness. Specifically, we first develop a likelihood ratio method to estimate the gradient with respect to both synaptic weights and noise levels for stochastic gradient descent training. Then, we design an approximation for the vanilla noise injection-based training method to reduce memory and improve computational efficiency. Next, we apply our proposed scheme to spiking neural networks and evaluate the performance of classification accuracy and robustness on MNIST and Fashion-MNIST datasets. Experiment results show that our proposed method achieves a much better performance on adversarial robustness and slightly better performance on original accuracy, compared with the conventional gradient-based training method

Spatio-Temporal Patterns and Impacts of Sediment Variations in Downstream of the Three Gorges Dam on the Yangtze River, China

Spanning the Yangtze River of China, the Three Gorges Dam (TGD) has received considerable concern worldwide with its potential impacts on the downstream side of the dam. This work investigated the spatio-temporal variations of suspended sediment concentration (SSC) at the downstream section of Yichang-to-Chenglingji from 2002 to 2015. A random forest model was developed to estimate SSC using MODIS ground reflectance products, and the spatio-temporal distributions of SSC were retrieved with this model to investigate the characteristics of water-silt variation. Our results revealed that, relatively, SSC before 2003 was evenly distributed in the downstream Yangtze River, while this spatial distribution pattern changed ce 2003 when the dam started storing water. Temporally, the SSC demonstrated a W-shaped curve of seasonal variation as one peak occurred in September and two troughs in March and November, and showed a significantly decreasing trend after three-stage impoundment. After official operation of the TGD in 2009, the SSC was reduced by over 40% than before 2003. Spatially, the most significant changes occurred in the upper Jingjiang section, where the SSC dropped by 45%. During all stages of impoundment, the water impoundment to 135 m in 2003 had the most significant impact on suspended sediment. The decreased SSC has led to emerging risks of bank failure, aggravated erosion of water front and aggressive down-cutting erosion along the downstream of the dam, as well as other ecological and environmental issues that require urgent attention by the government