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BackgroundImproving the understandability of health information can significantly increase the cost-effectiveness and efficiency of health education programs for vulnerable populations. There is a pressing need to develop clinically informed computerized tools to enable rapid, reliable assessment of the linguistic understandability of specialized health and medical education resources. This paper fills a critical gap in current patient-oriented health resource development, which requires reliable and accurate evaluation instruments to increase the efficiency and cost-effectiveness of health education resource evaluation. ObjectiveWe aimed to translate internationally endorsed clinical guidelines to machine learning algorithms to facilitate the evaluation of the understandability of health resources for international students at Australian universities. MethodsBased on international patient health resource assessment guidelines, we developed machine learning algorithms to predict the linguistic understandability of health texts for Australian college students (aged 25-30 years) from non-English speaking backgrounds. We compared extreme gradient boosting, random forest, neural networks, and C5.0 decision tree for automated health information understandability evaluation. The 5 machine learning models achieved statistically better results compared to the baseline logistic regression model. We also evaluated the impact of each linguistic feature on the performance of each of the 5 models. ResultsWe found that information evidentness, relevance to educational purposes, and logical sequence were consistently more important than numeracy skills and medical knowledge when assessing the linguistic understandability of health education resources for international tertiary students with adequate English skills (International English Language Testing System mean score 6.5) and high health literacy (mean 16.5 in the Short Assessment of Health Literacy-English test). Our results challenge the traditional views that lack of medical knowledge and numerical skills constituted the barriers to the understanding of health educational materials. ConclusionsMachine learning algorithms were developed to predict health information understandability for international college students aged 25-30 years. Thirteen natural language features and 5 evaluation dimensions were identified and compared in terms of their impact on the performance of the models. Health information understandability varies according to the demographic profiles of the target readers, and for international tertiary students, improving health information evidentness, relevance, and logic is critical.

This article investigates the geometric and topologic of warped product submanifolds in Riemannian warped product Qεm×R{{\mathbb{Q}}}_{\varepsilon }^{m}\times {\mathbb{R}}. In this respect, we obtain the first Chen inequality that involves extrinsic invariants like the length of the warping functions and the mean curvature. This inequality involves two intrinsic invariants (sectional curvature and δ\delta -invariant). In addition, an integral bound is provided for the Bochner operator formula of compact warped product submanifolds in terms of the Ricci curvature gradient. We aim to apply this theory to many structures and obtain Dirichlet eigenvalues for problem applications. Some new results regarding the vanishing mean curvature are presented as a partial solution, and this can be considered for the well-known problem given by Chern.

This study is mainly designed to evaluate a popular learning method: previewing material before classes and to answer two research questions on the learning method. The research questions are "Does previewing have benefits in promoting future learning?" and "Do people have correct metacognitive judgements on the effects of previewing?" The hypothesis states that previewing is beneficial in ways other than directly pre-stating answers (e.g., providing context information or keywords) and that, in general, individuals' judgements on the effects of previewing are correct. This experiment found that participants who read preview materials before watching a brief lecture do not perform significantly better on post-tests than participants who have not read the preview. At the same time, most people who read preview materials see the preview as beneficial to their understanding of the topic, which is an incorrect metacognitive judgement. This study indicates that the importance of preview for learning performance may be a myth and reveals how people misjudge the benefits of previewing. These findings can lead to an improved understanding of better ways to conduct self-cognitive study.

Saxifraga Tourn. ex L. is rich in species diversity with about 440-500 species and broad distribution. The taxonomical issues of this genus have been continuously concerned by the botanists. Saxifraga has important ornamental and medicinal values. Some of European countries have made great efforts on the exploitation and utilization of its ornamental resources. China is one of the diversity centers of Saxifraga, but it has been lagged far behind Europe, USA and even Japan in exploitation and utilization on ornamental value of this genus. The world breeding work in Saxifraga started 150 years ago. By the end of 2022, the 1 692 names of cultivars had been on-line listed by The Saxifrage Society, but only one came from China. In this paper, the germplasm resources of Saxifraga, and progress on its classification and breeding are reviewed, and also the utilization of its ornamental resources is briefly introduced, which will provide an important reference for taxonomical research, breeding and application of this genus in China. The results are as follows: (1) Saxifraga is rich in germplasms, but many scientific issues remain in the evolutionary relationships of its subordinate systems, which require a systematic and in-depth investigation by integrating morphological and molecular biology methods. (2) The cultivars of this genus are mainly raised through cross-breeding and mutant selection, and the majority of cultivars are from the UK, Czech Republic, Germany, and the Netherlands. (3) The breeding of Saxifraga started very late in China, with only few cultivars from one breeding method.