Between Modernization and Tradition: How does Culture Shape Older Taiwanese Women’s Perceptions of Successful Aging?

The purpose of this study was to understand how Taiwan’s culture context shapes the definitions of successful aging of older women. By interviewing 14 older Taiwanese women who aged over 60 and regularly volunteered for at least two years, the findings supported that successful aging was culturally constructed

Power Loss Characteristics of a Sensing Element Based on a Polymer Optical Fiber under Cyclic Tensile Elongation

In this study, power losses in polymer optical fiber (POF) subjected to cyclic tensile loadings are studied experimentally. The parameters discussed are the cyclic load level and the number of cycles. The results indicate that the power loss in POF specimens increases with increasing load level or number of cycles. The power loss can reach as high as 18.3% after 100 cyclic loadings. Based on the experimental results, a linear equation is proposed to estimate the relationship between the power loss and the number of cycles. The difference between the estimated results and the experimental results is found to be less than 3%

Human Motion Capture Algorithm Based on Inertial Sensors

On the basis of inertial navigation, we conducted a comprehensive analysis of the human body kinematics principle. From the direction of two characteristic parameters, namely, displacement and movement angle, we calculated the attitude of a node during the human motion capture process by combining complementary and Kalman filters. Then, we evaluated the performance of the proposed attitude strategy by selecting different platforms as the validation object. Results show that the proposed strategy for the real-time tracking of the human motion process has higher accuracy than the traditional strategy

Outlier-Aware Training for Improving Group Accuracy Disparities

Methods addressing spurious correlations such as Just Train Twice (JTT, arXiv:2107.09044v2) involve reweighting a subset of the training set to maximize the worst-group accuracy. However, the reweighted set of examples may potentially contain unlearnable examples that hamper the model's learning. We propose mitigating this by detecting outliers to the training set and removing them before reweighting. Our experiments show that our method achieves competitive or better accuracy compared with JTT and can detect and remove annotation errors in the subset being reweighted in JTT

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities