Wearable Devices and Intelligent Application in Women’s Postpartum Repair for Smart Healthcare

Wearable devices are more and more widely used in the field of smart healthcare. The purpose of this study was to explore the effect of contraceptive counseling and education on contraceptive behavior of women after induced abortion. The investigators will explain the situation of this topic to the respondents and select the respondents in strict accordance with the framework requirements of sampling design. All the data are from the induced abortion women in the first-, second-, and third-level hospitals, which reduces the selection bias of the respondents. It is found that the proportion of induced abortion among college students is the highest, reaching 66.03%. This study is helpful to reduce the incidence of unwanted pregnancy, induced abortion, and repeated abortion and improve the reproductive health of women.

Social changes through the lens of language: A big data study of Chinese modal verbs

Leech’s corpus-based comparison of English modal verbs from 1961 to 1992 showed the steep decline of all modal verbs together, which he ascribed to continuing changes towards a more equal and less authority-driven society. This study inspired many diachronic and synchronic studies, mostly on English modal verbs and largely assuming the correlation between the use of modal verbs and power relations. Yet, there are continuing debates on sampling design and the choices of corpora. In addition, this hypothesis has not been attested in any other language with comparable corpus size or examined with longitudinal studies. This study tracks the use of Chinese modal verbs from 1901 to 2009, covering the historical events of the New Culture Movement, the establishment of the PRC, the implementation of simplified characters and the completion and finalization of simplification of the Chinese writing system. We found that the usage of modal verbs did rise and fall during the last century, and for more complex reasons. We also demonstrated that our longitudinal end-to-end approach produces convincing analysis on English modal verbs that reconciles conflicting results in the literature adopting Leech’s point-to-point approach.

Examining the effect of teacher’s self-efficacy on job satisfaction

The paper aims to examine the effect of teachers' self-efficacy on job satisfaction. To deepen the study, literature was reviewed and theories were established. The study used the descriptive correlational research design. The total enumeration was the sampling design of the study. It used questionnaires to gather the data. The study found that the teachers' self-efficacy is very high along the three dimensions of teachers' self-efficacy which include self-efficacy in student engagement, instructional strategies, and classroom management. While teachers' job satisfaction was considered high, not very high along the two dimensions such as satisfaction with the work itself and personal growth and career development. Concerning the correlation, it was found that there is a significant correlation between teachers' self-efficacy and job satisfaction.

Determining Plant Diversity within Interconnected Natural Habitat Remnants (Ecological Network) in an Agricultural Landscape: A Matter of Sampling Design?

In intensively used and human-modified landscapes, biodiversity is often confined to remnants of natural habitats. Thus, identifying ecological networks (ENs) necessary to connect these patches and maintain high levels of biodiversity, not only for conservation but also for the effective management of the landscape, is required. However, ENs are often defined without a clear a-priori evaluation of their biodiversity and are seldom even monitored after their establishment. The objective of this study was to determine the adequate number of replicates to effectively characterize biodiversity content of natural habitats within the nodes of an EN in north-eastern Italy, based on vascular plant diversity. Plant communities within habitat types of the EN’s nodes were sampled through a hierarchical sampling design, evaluating both species richness and compositional dissimilarity. We developed an integrated method, consisting of multivariate measures of precision (MultSE), rarefaction curves and diversity partitioning approaches, which was applied to estimate the minimum number of replicates needed to characterize plant communities within the EN, evaluating also how the proposed optimization in sampling size affected the estimations of the characteristics of habitat types and nodes of the EN. We observed that reducing the total sampled replicates by 85.5% resulted to sufficiently characterize plant diversity of the whole EN, and by 72.5% to exhaustively distinguish plant communities among habitat types. This integrated method helped to fill the gap regarding the data collection to monitor biodiversity content within existing ENs, considering temporal and economic resources. We therefore suggest the use of this quantitative approach, based on probabilistic sampling, to conduct pilot studies in the context of ENs design and monitoring, and in general for habitat monitoring.

Water chemistry and not urbanization influences community structure of non-marine Ostracoda (Crustacea) in northern Belgium

Urbanization is one of the major causes of the destruction of natural habitats in the world. Cities are urban heat islands and can thus significantly influence populations of plants and animals. The research project SPEEDY investigated the effects of urbanization in northern Belgium with a nested sampling design at local and landscape scales for a variety of organisms. Here, we tested the effects of urbanization on non-marine ostracod communities, sampling 81 small pools in three urbanization categories, as defined by percentage built up cover (low, intermediate, high). We identified 17 ostracod species, together occurring in 60 of the 81 sampled pools. We found that urbanization per se had no significant effect on ostracod communities. Of all the measured local factors, ammonium and total phosphorus concentrations had a significant effect on the community structure. In contrast, water temperature had no significant effect, most likely because the ostracod species found in northern Belgium in the present survey mostly have wide temperature tolerances.

Improving random forest predictions in small datasets from two-phase sampling designs

Background While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases—a common situation in biomedical studies, which often have rare outcomes and covariates whose measurement is resource-intensive. Methods Using an immunologic marker dataset from a phase III HIV vaccine efficacy trial, we seek to optimize random forest prediction performance using combinations of variable screening, class balancing, weighting, and hyperparameter tuning. Results Our experiments show that while class balancing helps improve random forest prediction performance when variable screening is not applied, class balancing has a negative impact on performance in the presence of variable screening. The impact of the weighting similarly depends on whether variable screening is applied. Hyperparameter tuning is ineffective in situations with small sample sizes. We further show that random forests under-perform generalized linear models for some subsets of markers, and prediction performance on this dataset can be improved by stacking random forests and generalized linear models trained on different subsets of predictors, and that the extent of improvement depends critically on the dissimilarities between candidate learner predictions. Conclusion In small datasets from two-phase sampling design, variable screening and inverse sampling probability weighting are important for achieving good prediction performance of random forests. In addition, stacking random forests and simple linear models can offer improvements over random forests.