Integrating online and offline teaching to promote creativity for STEM learners

This research extends previous findings by proposing an online and offline integrated teaching framework to enhance creativity for STEM learners. The framework integrates key elements from both modalities, featuring a combination of virtual and physical resources to support a comprehensive learning experience. The study introduces a "smart flowerpot" project as a practical application, detailing the instructional design, learning resources, and assessment strategies. It highlights the challenges in resource selection and the increased workload for teachers transitioning from traditional classroom settings. While the framework offers a promising approach, it acknowledges the need for empirical testing and consideration of external factors that may influence its effectiveness. The research advocates further exploration to validate the framework and its potential to transform STEM education

Cross Cultural Comparative Research of Online Consumer Reviews Intentions

A detailed literature review on motives of knowledge sharing in virtual communities is conducted. Moreover, the comparative study on intentions of consumer reviews between Amazon.com and Amazon.cn, based on an online open-ended survey through content analysis, is done. The analytical results show that users contribute their consumption experiences are mainly depended upon social motives, psychological motives and economic motives, which are deeply correlated and influenced by their national culture dimensions

Case report: A de novo Non-sense SOX9 mutation (p.Q417*) located in transactivation domain is Responsible for Campomelic Dysplasia

BackgroundCampomelic dysplasia (CD) is an autosomal dominant skeletal dysplasia syndrome characterized by shortness and bowing of lower extremities, and often accompanied by XY sex reversal. Heterozygous pathogenic variants of SOX9 or rearrangement involving the long arm of chromosome 17 are the causes of disease. However, evidence for pathogenesis of SOX9 haploinsufficiency is insufficient.MethodsWe enrolled a Chinese family where the fetus was diagnosed with CD. The affected fetus was selected for whole-exome sequencing to identify the pathogenic mutations in this family.ResultsAfter data filtering, a novel non-sense SOX9 variant (NM_000346.3; c.1249C > T; p.Q417*) was identified as the pathogenic lesion in the fetus. Further co-segregation analysis using Sanger sequencing confirmed that this novel SOX9 mutation (c.1249C > T; p.Q417*) was a de novo mutation in the affected fetus. This terminated codon mutation identified by bioinformatics was located at an evolutionarily conserved site of SOX9. The bioinformatics-based analysis predicted this variant was pathogenic and affected SOX9 transactivation activity.ConclusionCD is a rare condition, which connected with SOX9 tightly. We identified a novel heterozygous SOX9 variant (p.Q417*) in a Chinese CD family. Our study supports the putative reduced transactivation of SOX9 variants in the pathogenicity of CD

Mixed Eucalyptus plantations in subtropical China enhance phosphorus accumulation and transformation in soil aggregates

IntroductionThe production of Eucalyptus, a principal economic tree genus in China, is faced with challenges related to soil phosphorus (P) limitations. In this study, we explore variations in phosphorus content, storage, and transformation in Eucalyptus forests. We hypothesize that mixed forests augment soil aggregate stability and P content and that microaggregates are pivotal in determining P differences between mixed and pure forests. Additionally, we posit that mixed forests foster P transformation, enhancing its efficacy in the soil. Current research on the distribution and transformation of soil total P (TP) and P fractions at the soil aggregate level is limited.MethodsIn this study, we selected soil from a Eucalyptus-Mytilaria laosensis Lecomte mixed forest, Eucalyptus-Erythrophleum fordii Oliv mixed forest, and pure Eucalyptus forest in Chongzuo County, Guangxi, China, as the research objects. Using a dry-sieving method, we divided the soil collected in situ from the 0–40 cm layer into aggregates of >2, 1–2, 0.25–1, and <0.25 mm particle sizes, measured the TP and P fractions (resin-extractable inorganic P, bicarbonate-extractable inorganic P, bicarbonate-extractable organic P, sodium hydroxide-extractable inorganic P, sodium hydroxide-extractable organic P, dilute hydrochloric acid-extractable P, concentrated hydrochloric acid extractable inorganic P, concentrated hydrochloric acid-extractable organic P and residue-P) in different aggregates, and used redundancy analysis and PLS SEM to reveal key factors affecting soil P accumulation and transformation.ResultsThe results showed that compared to pure Eucalyptus forests, mixed Eucalyptus forests significantly enhanced the stability of soil aggregates and the content and storage of phosphorus, especially the Eucalyptus-Mytilaria laosensis mixed forest. The content of total soil phosphorus and its fractions decreased with increasing aggregate particle size, while the opposite trend was observed for stored P, with aggregates <0.25 mm being the main fraction influencing soil phosphorus accumulation. The transformation process of P fractions was primarily constrained by dissolution rates, mineralization rates, biological activity, including the action of microbes, fungi, and plant–root interactions, and other factors.DiscussionMixed forests increased the transformation of phosphorus in soil aggregates, effectivel enhancing the availability of soil phosphorus. In summary, this study provides important evidence for the systematic management of subtropical artificia Eucalyptus forests and the sustainable utilization of soil resources

Net Primary Productivity and Management Potential of Artificial Pinus tabulaeformis Forest in Shanxi Province

The dynamic variation of net primary productivity of artificial Pinus tabulaeformis forest was studied in Shanxi Province, and potential productivity of artificial forest was predicted to provide reference for improving quality of regional forest stand. The regression equation was established by using the stratification and harvesting method with the relative growth model. Cumulative method and Thornthwaite Memorial model was used to estimate the actual and potential productivity of the forest. The productivity of P. tabulaeformis forest increased with the increase of age and started decrease with the mature period. The actual productivity of P. tabulaeformis forest was 4.462 t/(ha•a); the contribution rate of trees was 72.17% of the total productivity, and with the increase of age, the total biomass increased but productivity decreased at late near-mature forest; the contribution rate of herb layer was 21.16% in the young forest stage, and then decreased gradually. On the contrary, the contribution rate of shrub layer increased gradually, and the contribution rate of the grassland was more than that of the herb layer, so as the key period of structural management; the average potential productivity of forest was 8.422 t/(ha•a), and the potential space of P. tabulaeformis was at least 32% in Shanxi Province. In conclusion, the potential space of productivity of P. tabulaeformis was at least 32%, and the primary limiting factor of P. tabulaeformis forest productivity in Shanxi Province was rainfall

Broadband Vortex Beam Modulating System Based on Electrically Controlled Liquid Crystal Devices

Vortex beams with helical phase wavefronts have recently emerged as a research hotspot because of their widespread applications such as ultra-high dimensional information encoding, quantum entanglement, and data transmission due to their unique properties. Research, as of yet, on the easy preparation of vector vortex beams is hindered by technical bottlenecks such as large mechanical modulation errors and limited bandwidths of meta-structured devices in spite of the massive experimental and theoretical breakthroughs in the generation of vortex beams that have been made. To make up for the deficiency in this area, we propose here a broadband vortex beam modulating system based on electrically controlled liquid crystal (LC) devices. An electrically controlled LC q-plate and an LC broadband polarization grating (PG) are integrated in the system as the crux devices. The system enables pure vortex-phase modulation within a wide spectral range in the visible spectrum and electrical control on the output beam intensity of the vortex and Gaussian components. Experiments at different voltages of 533 nm and 632.8 nm were conducted for validation. This system overcomes the complexity and stringent optical path requirements of traditional methods for generating vortex beams, offering an efficient, convenient, and rapidly tunable approach for generating vortex beams that is easily and highly integrable

A Novel Data Augmentation Method for Improving the Accuracy of Insulator Health Diagnosis

Performing ultrasonic nondestructive testing experiments on insulators and then using machine learning algorithms to classify and identify the signals is an important way to achieve an intelligent diagnosis of insulators. However, in most cases, we can obtain only a limited number of data from the experiments, which is insufficient to meet the requirements for training an effective classification and recognition model. In this paper, we start with an existing data augmentation method called DBA (for dynamic time warping barycenter averaging) and propose a new data enhancement method called AWDBA (adaptive weighting DBA). We first validated the proposed method by synthesizing new data from insulator sample datasets. The results show that the AWDBA proposed in this study has significant advantages relative to DBA in terms of data enhancement. Then, we used AWDBA and two other data augmentation methods to synthetically generate new data on the original dataset of insulators. Moreover, we compared the performance of different machine learning algorithms for insulator health diagnosis on the dataset with and without data augmentation. In the SVM algorithm especially, we propose a new parameter optimization method based on GA (genetic algorithm). The final results show that the use of the data augmentation method can significantly improve the accuracy of insulator defect identification