EFFECTS OF LOWER EXTREMITY STRENGTH TRAINING ON GAIT PATTERNS IN OBESE CHILDREN

The purpose of this study was to investigate the effect of muscle strength training on gait patterns in obese children. This study included 14 obese children who were required to complete 8 week lower extremity strength training. All participants went through a 3D gait analysis and an isokinetic strength test before and after training. With the improvement in muscle strength, walking speed and stride length significantly increased after intervention. Hip flexion moment and hip power generation increased 31.1% and 22.4%, respectively. Hip and knee power absorption also significantly increased. We concluded that the strength training improved obese children’s ability to promote locomotion through greater propulsion. Muscle strength plays an important role in attenuating the negative effects that obesity has on gait characteristics and kinetics

Goal-Guided Transformer-Enabled Reinforcement Learning for Efficient Autonomous Navigation

Despite some successful applications of goal-driven navigation, existing deep reinforcement learning (DRL)-based approaches notoriously suffers from poor data efficiency issue. One of the reasons is that the goal information is decoupled from the perception module and directly introduced as a condition of decision-making, resulting in the goal-irrelevant features of the scene representation playing an adversary role during the learning process. In light of this, we present a novel Goal-guided Transformer-enabled reinforcement learning (GTRL) approach by considering the physical goal states as an input of the scene encoder for guiding the scene representation to couple with the goal information and realizing efficient autonomous navigation. More specifically, we propose a novel variant of the Vision Transformer as the backbone of the perception system, namely Goal-guided Transformer (GoT), and pre-train it with expert priors to boost the data efficiency. Subsequently, a reinforcement learning algorithm is instantiated for the decision-making system, taking the goal-oriented scene representation from the GoT as the input and generating decision commands. As a result, our approach motivates the scene representation to concentrate mainly on goal-relevant features, which substantially enhances the data efficiency of the DRL learning process, leading to superior navigation performance. Both simulation and real-world experimental results manifest the superiority of our approach in terms of data efficiency, performance, robustness, and sim-to-real generalization, compared with other state-of-the-art (SOTA) baselines. The demonstration video (https://www.youtube.com/watch?v=aqJCHcsj4w0) and the source code (https://github.com/OscarHuangWind/DRL-Transformer-SimtoReal-Navigation) are also provided

Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation

As a distributed machine learning paradigm, Federated Learning (FL) enables large-scale clients to collaboratively train a model without sharing their raw data. However, due to the lack of data auditing for untrusted clients, FL is vulnerable to poisoning attacks, especially backdoor attacks. By using poisoned data for local training or directly changing the model parameters, attackers can easily inject backdoors into the model, which can trigger the model to make misclassification of targeted patterns in images. To address these issues, we propose a novel data-free trigger-generation-based defense approach based on the two characteristics of backdoor attacks: i) triggers are learned faster than normal knowledge, and ii) trigger patterns have a greater effect on image classification than normal class patterns. Our approach generates the images with newly learned knowledge by identifying the differences between the old and new global models, and filters trigger images by evaluating the effect of these generated images. By using these trigger images, our approach eliminates poisoned models to ensure the updated global model is benign. Comprehensive experiments demonstrate that our approach can defend against almost all the existing types of backdoor attacks and outperform all the seven state-of-the-art defense methods with both IID and non-IID scenarios. Especially, our approach can successfully defend against the backdoor attack even when 80\% of the clients are malicious

P3^3OVD: Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection

Inspired by the success of visual-language methods (VLMs) in zero-shot classification, recent works attempt to extend this line of work into object detection by leveraging the localization ability of pre-trained VLMs and generating pseudo labels for unseen classes in a self-training manner. However, since the current VLMs are usually pre-trained with aligning sentence embedding with global image embedding, the direct use of them lacks fine-grained alignment for object instances, which is the core of detection. In this paper, we propose a simple but effective Pretrain-adaPt-Pseudo labeling paradigm for Open-Vocabulary Detection (P$^3$OVD) that introduces a fine-grained visual-text prompt adapting stage to enhance the current self-training paradigm with a more powerful fine-grained alignment. During the adapting stage, we enable VLM to obtain fine-grained alignment by using learnable text prompts to resolve an auxiliary dense pixel-wise prediction task. Furthermore, we propose a visual prompt module to provide the prior task information (i.e., the categories need to be predicted) for the vision branch to better adapt the pretrained VLM to the downstream tasks. Experiments show that our method achieves the state-of-the-art performance for open-vocabulary object detection, e.g., 31.5% mAP on unseen classes of COCO

The effectiveness of a combined exercise intervention on physical fitness factors related to falls in community-dwelling older adults

This study aimed to evaluate the effectiveness of an innovative exercise program on muscle strength, balance, and gait kinematics in elderly community-dwellers. The exercise program included strength and balance training and the 8-form Tai Chi Chuan. The measurements were carried out at baseline and 12 weeks, and consisted of four physical performance tests, joint isokinetic strength tests, and three-dimensional gait analysis. Fifty-six community-dwelling older adults aged 60–80 years old were randomly assigned to an intervention or control group. After 12 weeks, the intervention group showed a 17.6% improvement in the timed up and go test, accompanied by a 54.7% increase in the 30-second chair stand test score. Significant increases in the score of star excursion balance tests, and the strength of the extensor and flexor muscles at knee and ankle joints were also observed. In addition, the intervention group walked at a faster speed with a longer step length, shorter support phase, and a greater sagittal plane range of motion at the hip and ankle joints. No statistical improvements were seen in the control group. This study provided an effective, evidence-based falls prevention program that can be implemented in community settings to improve physical fitness and reduce fall risks among community-dwelling older adults. The star excursion balance test could be a sensitive measure of physical performance for fall risk assessment in older people

Endophytic bacterium Pseudomonas protegens suppresses mycelial growth of Botryosphaeria dothidea and decreases its pathogenicity to postharvest fruits

Apple (Malus domestica Borkh.), one of the most economically important fruits widely consumed worldwide, has been suffering from apple ring rot caused by Botryosphaeria dothidea, which dramatically affects its quality and yield. In the present study, we demonstrated that Pseudomonas protegens, isolated from Chinese leek (Allium tuberosum), significantly suppressed the mycelial growth and propagation of B. dothidea, respectively, further displayed a considerably inhibitory effect on the apple ring rot of postharvest fruits. In addition, P. protegens significantly improved the total soluble solid/titrable acidity (TSS/TA) ratio and soluble sugar/titrable acidity (SS/TA) ratio and drastically maintained the fruit firmness. Further analysis manifested that P. protegens substantially induced the defense-related genes such as MdGLU, MdPAL, MdPOD, MdCAL, and transcription factors related to the resistance to B. dothidea, including MdWRKY15, MdPUB29, MdMyb73, and MdERF11 in apple fruits. Meanwhile, P. protegens considerably restrained the expressions of the pathogenicity-related genes in B. dothidea, including the BdCYP450, BdADH, BdGHY, BdATS, Bdα/β-HY, and BdSTR. By inference, P. protegens inhibited the apple ring rot on postharvest fruits by activating the defense system of apple fruit and repressing the pathogenic factor of B. dothidea. The study provided a theoretical basis and a potential alternative to manage the apple ring rot on postharvest fruits

Achievements and Challenges in Improving Air Quality in China: Analysis of the Long-Term Trends from 2014 to 2022

Due to the implementation of air pollution control measures in China, air quality has significantly improved, although there are still additional issues to be addressed. This study used the long-term trends of air pollutants to discuss the achievements and challenges in further improving air quality in China. The Kolmogorov-Zurbenko (KZ) filter and multiple-linear regression (MLR) were used to quantify the meteorology-related and emission-related trends of air pollutants from 2014 to 2022 in China. The KZ filter analysis showed that PM2.5 decreased by 7.36 ± 2.92% yr􀀀 1, while daily maximum 8-h ozone (MDA8 O3) showed an increasing trend with 3.71 ± 2.89% yr􀀀 1 in China. The decrease in PM2.5 and increase in MDA8 O3 were primarily attributed to changes in emission, with the relative contribution of 85.8% and 86.0%, respectively. Meteorology variations, including increased ambient temperature, boundary layer height, and reduced relative humidity, also contributed to the reduction of PM2.5 and the enhancement of MDA8 O3. The emission-related trends of PM2.5 and MDA8 O3 exhibited continuous decrease and increase, respectively, from 2014 to 2022, while the variation rates slowed during 2018–2020 compared to that during 2014–2017, highlighting the challenges in further improving air quality, particularly in simultaneously reducing PM2.5 and O3. This study recommends reducing NH3 emissions from the agriculture sector in rural areas and transport emissions in urban areas to further decrease PM2.5 levels. Addressing O3 pollution requires the reduction of O3 precursor gases based on site-specific atmospheric chemistry considerations

Recent Advances in Extraction Methods, Biological Activities and Application in Foods of Puerarin

Puerarin is the major bioactive ingredient of Pueraria lobata, a traditional medicinal and edible plant in China, and it exerts multiple biological activities, including cardiovascular protection, anti-diabetes, anti-tumor, neuroprotection, bone protection, phytoestrogen-like function and regulating intestinal flora. It is widely used in healthcare, biomedicine, and food processing, exerting extensive and favorable effects. Based on an extensive literature search in the CNKI, Web of Science and PubMed databases in the past five years, this paper summarizes the extraction methods, biological activities and application in food processing of puerarin and discusses future prospects to provide references for the development and application of new puerarin-based products

Association between sleep duration and disability in activities of daily living among Chinese older adults: a nationwide observational study

BackgroundThis study aims to explore the relationship between sleep duration and Activity of Daily Living (ADL) disability among older adults in China. ADL disability severely impacts the quality of life of older adults and is associated with various physical and mental health issues. With the aging population in China, the burden of ADL disability is increasing.MethodsData were sourced from the 2018 national follow-up of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), including 9,572 participants aged 65 and above. Sleep duration was assessed via self-reported questionnaire and categorized into short (<7 h), medium (7–8 h), and long (≥9 h). ADL disability was evaluated through Basic Activities of Daily Living (BADL) and Instrumental Activities of Daily Living (IADL). Logistic regression models were used to analyze the relationship between sleep duration and ADL disability, with subgroup analyses conducted to explore differences by gender and physical activity.ResultsThe study found a significant non-linear relationship between sleep duration and ADL disability. Compared to older adults with a sleep duration of 7–8 h, those with over 9 h of sleep had a significantly higher risk of BADL and IADL disability (OR = 1.36, OR = 1.35). Subgroup analyses indicated that this relationship existed among older adults of different genders, age, and physical activity levels.ConclusionFor older adults in China, maintaining a sleep duration of 7–8 h may be an effective strategy for preventing ADL disability. Both excessively long and short sleep duration are associated with an increased risk of ADL disability in this population