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  1. A comparison of low and high dose of moderate intensity aerobic exercise on heart rate recovery of the sedentary adults: a pragmatic randomized controlled trial
    Jaafar Z, Lim YZ
    J Sports Med Phys Fitness, 2023 Feb;63(2):310-318.
    PMID: 35620954 DOI: 10.23736/S0022-4707.22.13958-7
    BACKGROUND: Heart rate recovery (HRR) has been used as a prognostication marker of health. A slower drop in HRR is linked to a higher risk of cardiovascular diseases and all-cause mortality. Since aerobic exercise has been shown to have favorable effects on HRR, we aimed to compare the effects of two different aerobic exercise doses on HRR among a sedentary adult population.

    METHODS: A pragmatic randomised controlled trial was conducted on 29 healthy sedentary adults (seven males and 22 females) in a 12-week exercise program. They were randomly assigned to group A (75 min/week, N.=15) or group B (150 min/week, N.=14) of moderate intensity aerobic exercise groups. HRR at 1-minute (HRR1), HRR at 2-minute (HRR2), and peak oxygen uptake (VO2peak) were measured pre- and post-intervention.

    RESULTS: The improvements of HRR1 and HRR2 were seen in both groups but was only significant (P<0.05) for group A with HRR1, -4.07 bpm (post 24.47±6.42 - pre 20.40±5.51, P=0.018) and HHR2, -3.93 bpm (post 43.40±13.61 - pre 39.47±10.68, P=0.046). Group B showed increment of HRR1, -1.14 bpm (post 21.14±5.35 - pre 20.00±6.30, P=0.286) and HRR2, -2.5 bpm, (post 39.36±8.01 - pre 36.86±9.57, P=0.221). Improvement of the VO2peak was only significant in group B with an increment of 1.52±2.61 (P=0.049).

    CONCLUSIONS: In conclusion, our study suggests that improvements in heart rate recovery (HRR1 and HRR2) among sedentary healthy adults can be achieved by engaging in moderate intensity exercise at a dose lower than the current recommended guidelines. The lower dose seems to be more attainable and may encourage exercise compliance. Future studies should further explore the effects of different exercise volumes on HRR in a larger sample size and also by controlling for BMI or gender.

  2. Fulltext Fast Recognition and Counting Method of Dragon Fruit Flowers and Fruits Based on Video Stream
    Li X, Wang X, Ong P, Yi Z, Ding L, Han C
    Sensors (Basel), 2023 Oct 13;23(20).
    PMID: 37896537 DOI: 10.3390/s23208444
    Dragon fruit (Hylocereus undatus) is a tropical and subtropical fruit that undergoes multiple ripening cycles throughout the year. Accurate monitoring of the flower and fruit quantities at various stages is crucial for growers to estimate yields, plan orders, and implement effective management strategies. However, traditional manual counting methods are labor-intensive and inefficient. Deep learning techniques have proven effective for object recognition tasks but limited research has been conducted on dragon fruit due to its unique stem morphology and the coexistence of flowers and fruits. Additionally, the challenge lies in developing a lightweight recognition and tracking model that can be seamlessly integrated into mobile platforms, enabling on-site quantity counting. In this study, a video stream inspection method was proposed to classify and count dragon fruit flowers, immature fruits (green fruits), and mature fruits (red fruits) in a dragon fruit plantation. The approach involves three key steps: (1) utilizing the YOLOv5 network for the identification of different dragon fruit categories, (2) employing the improved ByteTrack object tracking algorithm to assign unique IDs to each target and track their movement, and (3) defining a region of interest area for precise classification and counting of dragon fruit across categories. Experimental results demonstrate recognition accuracies of 94.1%, 94.8%, and 96.1% for dragon fruit flowers, green fruits, and red fruits, respectively, with an overall average recognition accuracy of 95.0%. Furthermore, the counting accuracy for each category is measured at 97.68%, 93.97%, and 91.89%, respectively. The proposed method achieves a counting speed of 56 frames per second on a 1080ti GPU. The findings establish the efficacy and practicality of this method for accurate counting of dragon fruit or other fruit varieties.
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