The diagnostic agreement of sarcopenic obesity with different definitions in Chinese community-dwelling middle-aged and older adults

BackgroundIn 2022, the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) launched a consensus on the diagnostic methods for sarcopenic obesity (SO). The study aimed to identify the prevalence and diagnostic agreement of SO using different diagnostic methods in a cohort of subjects from West China aged at least 50 years old.MethodsA large multi-ethnic sample of 4,155 participants from the West China Health and Aging Trend (WCHAT) study was analyzed. SO was defined according to the newly published consensus of the ESPEN/EASO. Furthermore, SO was diagnosed as a combination of sarcopenia and obesity. The criteria established by the Asian Working Group for Sarcopenia 2019 (AWGS2019) were used to define sarcopenia. Obesity was defined by four widely used indicators: percent of body fat (PBF), visceral fat area (VFA), waist circumference (WC), and body mass index (BMI). Cohen’s kappa was used to analyze the diagnostic agreement of the above five diagnostic methods.ResultsA total of 4,155 participants were part of the study, including 1,499 men (63.76 ± 8.23 years) and 2,656 women (61.61 ± 8.20 years). The prevalence of SO was 0.63–7.22% with different diagnostic methods. The diagnosis agreement of five diagnostic methods was poor-to-good (κ: 0.06–0.67). The consensus by the ESPEN/EASO had the poorest agreement with other methods (κ: 0.06–0.32). AWGS+VFA had the best agreement with AWGS+WC (κ = 0.67), and consensus by the ESPEN/EASO had the best agreement with AWGS+ PBF (κ = 0.32).ConclusionThe prevalence and diagnostic agreement of SO varies considerably between different diagnostic methods. AWGS+WC has the highest diagnostic rate in the diagnosis of SO, whereas AWGS+BMI has the lowest. AWGS+VFA has a relatively good diagnostic agreement with other diagnostic methods, while the consensus of the ESPEN/EASO has a poor diagnostic agreement. AWGS+PBF may be suitable for the alternative diagnosis of the 2022 ESPEN/EASO

A Lightweight Two-End Feature Fusion Network for Object 6D Pose Estimation

Currently, many methods of object pose estimation use images or point clouds alone for pose estimation. This leads to their inability to accurately estimate the object pose in the case of occlusion and poor illumination. Second, these models have large parameters and cannot be deployed on mobile devices. Therefore, we propose a lightweight two-terminal feature fusion network, which can effectively use images and point clouds for accurate object pose estimation. First, Pointno problemNet network is used to extract point cloud features. Then the extracted point cloud features are combined with the images at pixel level and the features are extracted by CNN. Secondly, the extracted image features are combined with the point cloud point by point. Then feature extraction is performed on it using the improved PointNet++ network. Finally, a set of center point features are obtained and pose estimation is performed for each feature. The pose with the highest confidence is selected as the final result. Furthermore, we apply depthwise separable convolutions to reduce the amount of model parameters. Experiments show that the proposed method exhibits better performance on Linemod and Occlusion Linemod datasets. Furthermore, the model parameters are small, and it is robust in occlusion and low-light situations

A three-dimensional vibration data compression method for rolling bearing condition monitoring

In condition monitoring for rolling bearings, it has achieved good diagnostic performance and clear mechanistic interpretation based on vibration data. The high sampling frequency of data collection preserves fault characteristics but brings the problem of big data. An effective way to reduce this problem is to apply data compression. However, in order not to affect the diagnostic performance of data, it is difficult to improve the compression ratio further. Inspired by the binarization method, the compression dimension of the bit cost of a single sample point is first introduced into the fault-mechanism-based method in this article. On this basis, a three-dimensional data compression method is proposed, and it is subsequently validated with two real-bearing datasets. Two performance metrics, including a newly defined one, are utilized to compare the proposed method with the five existing methods. The comparison results show that the proposed method significantly improves the compression ratio of data but maintains good diagnostic performance.This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1702400, in part by the Key Research and Development Program of Sichuan Province under Grant 23ZDYF0212, and in part by the China Scholarship Council with a Scholarship under Grant 202106070089

An Adaptive Sampling Framework for Life Cycle Degradation Monitoring

Data redundancy and data loss are relevant issues in condition monitoring. Sampling strategies for segment intervals can address these at the source, but do not receive the attention they deserve. Currently, the sampling methods in relevant research lack sufficient adaptability to the condition. In this paper, an adaptive sampling framework of segment intervals is proposed, based on the summary and improvement of existing problems. The framework is implemented to monitor mechanical degradation, and experiments are implemented on simulation data and real datasets. Subsequently, the distributions of the samples collected by different sampling strategies are visually presented through a color map, and five metrics are designed to assess the sampling results. The intuitive and numerical results show the superiority of the proposed method in comparison to existing methods, and the results are closely related to data status and degradation indicators. The smaller the data fluctuation and the more stable the degradation trend, the better the result. Furthermore, the results of the objective physical indicators are obviously better than those of the feature indicators. By addressing existing problems, the proposed framework opens up a new idea of predictive sampling, which significantly improves the degradation monitoring

Testing of precast recycled aggregate concrete shear wall with pressed sleeve connection subjected to cyclic loading

The pressed sleeve connection is a new type of connection technique reported in China recently. To explore the possibility of combining the advantages of pressed sleeve connections and recycled aggregate concrete (RAC) in precast concrete, the seismic performance of precast shear walls with pressed sleeves and recycled fine aggregate (RFA) concrete was investigated through a thorough experimental programme. A total of seven precast shear wall specimens and one cast-in-situ specimen were fabricated and tested under lateral cyclic loading, considering the effects of the aspect ratio, the axial compression ratio, and the RFA content. The failure modes, hysteretic behavior, bearing capacity, energy dissipation, stiffness and shear distortion of the specimens, as well as the strains of the steels, were reported and discussed. The test results demonstrated that the pressed sleeve connections were capable of transmitting both tensile and compressive forces between reinforcements, and the precast shear walls with pressed sleeve connections exhibited the same hysteresis behavior, strengths, ductility coefficient and energy dissipation capacity as the cast-in-situ counterpart. Moreover, the seismic behavior of the precast specimens with the RFA content of 30% was almost the same as those with natural aggregate concrete (NAC). The increase in the axial compression ratio and aspect ratio led to higher peak loads of the precast shear walls. Finally, existing design methods of ordinary reinforced concrete shear walls were evaluated for their application to the design of precast RFA concrete shear walls with pressed sleeves. Overall, the evaluation results revealed that the examined design methods offer generally accurate strength predictions for the proposed shear walls

Evaluation of Different Yeast Species for Improving Fermentation of Cereal Straws

Information on the effects of different yeast species on ruminal fermentation is limited. This experiment was conducted in a 3×4 factorial arrangement to explore and compare the effects of addition of three different live yeast species (Candida utilis 1314, Saccharomyces cerevisiae 1355, and Candida tropicalis 1254) at four doses (0, 0.25×107, 0.50×107, and 0.75×107 colony-forming unit [cfu]) on in vitro gas production kinetics, fiber degradation, methane production and ruminal fermentation characteristics of maize stover, and rice straw by mixed rumen microorganisms in dairy cows. The maximum gas production (Vf), dry matter disappearance (IVDMD), neutral detergent fiber disappearance (IVNDFD), and methane production in C. utilis group were less (p<0.01) than other two live yeast supplemented groups. The inclusion of S. cerevisiae reduced (p<0.01) the concentrations of ammonia nitrogen (NH3-N), isobutyrate, and isovalerate compared to the other two yeast groups. C. tropicalis addition generally enhanced (p<0.05) IVDMD and IVNDFD. The NH3-N concentration and CH4 production were increased (p<0.05) by the addition of S. cerevisiae and C. tropicalis compared with the control. Supplementation of three yeast species decreased (p<0.05) or numerically decreased the ratio of acetate to propionate. The current results indicate that C. tropicalis is more preferred as yeast culture supplements, and its optimal dose should be 0.25×107 cfu/500 mg substrates in vitro

Image_3_Tannic acid supplementation in the diet of Holstein bulls: Impacts on production performance, physiological and immunological characteristics, and ruminal microbiota.pdf

This study was conducted to evaluate the influences of supplementing tannic acid (TA) at different doses on the production performance, physiological and immunological characteristics, and rumen bacterial microbiome of cattle. Forty-eight Holstein bulls were randomly allocated to four dietary treatments: the control (CON, basal diet), the low-dose TA treatment [TAL, 0.3% dry matter (DM)], the mid-dose TA treatment (TAM, 0.9% DM), and the high-dose TA treatment (TAH, 2.7% DM). This trial consisted of 7 days for adaptation and 90 days for data and sample collection, and samples of blood and rumen fluid were collected on 37, 67, and 97 d, respectively. The average daily gain was unaffected (P > 0.05), whilst the ruminal NH3-N was significantly decreased (P < 0.01) by TA supplementation. The 0.3% TA addition lowered (P < 0.05) the levels of ruminal isobutyrate, valerate, and tumor necrosis factor alpha (TNF-α), and tended to (P < 0.1) increase the gain to feed ratio. The digestibility of DM, organic matter (OM), and crude protein, and percentages of butyrate, isobutyrate, and valerate were lower (P < 0.05), while the acetate proportion and acetate to propionate ratio in both TAM and TAH were higher (P < 0.05) than the CON. Besides, the 0.9% TA inclusion lessened (P < 0.05) the concentrations of glucagon and TNF-α, but enhanced (P < 0.05) the interferon gamma (IFN-γ) level and Simpson index of ruminal bacteria. The 2.7% TA supplementation reduced (P < 0.05) the intake of DM and OM, and levels of malondialdehyde and thyroxine, while elevated (P < 0.05) the Shannon index of the rumen bacterial populations. Moreover, the relative abundances of the phyla Fibrobacteres and Lentisphaerae, the genera Fibrobacter and Bradyrhizobium, and the species Bradyrhizobium sp., Lachnospiraceae bacterium RM29, and Lachnospiraceae bacterium CG57 were highly significantly (q < 0.01) or significantly (q < 0.05) raised by adding 2.7% TA. Results suggested that the TA addition at 0.3% is more suitable for the cattle, based on the general comparison on the impacts of supplementing TA at different doses on all the measured parameters.</p