Primary education is an essential stage and has an important impact on students’ learning attitudes throughout the coming school years. The research explored the attitudes towards science, technology, engineering and mathematics among students through all grade levels in primary school. The Project-based Integrated STEM Program was proposed to study the changes of primary students’ attitudes towards STEM. An assessment of S-STEM which consists of the STEM subscale and the 21st century skills subscale was utilized for both pre-test and post-test. The results showed that primary students exhibited little different attitudes on the S-STEM in the pre-test, regardless of gender and grade level. As evident from the comparison between the pre-test and post-test, the Project-based Integrated STEM Program had a positive effect on student attitudes towards STEM. It is encouraging if there are more STEM-related programs implemented at all educational stages covering the primary level. Keywords: gender differences, grade levels, project-based integrated STEM program, school students, STEM education.

Background: This study explored the effects of multi-component exercise training on the physical and cognitive function of the elderly with mild cognitive impairment (MCI). Methods: A total of 90 older adults with MCI were chosen from screened volunteers and randomly assigned into 2 groups (n=45), and 84 completed the 6-month follow-up. Participants in the control group received general community health instruction, while the multi-component exercise training performed on the other group. The multi-component exercise training performed on these participants was designed to suit Chinese elderly based on advice from the nursing specialist and sports medicine specialist after the preliminary experiment. The Chinese version Mini-Physical Performance Test (CM-PPT), the Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA) scores were examined by repeated measures analysis of variance to evaluate the physical and cognitive function of adults with MCI before and at 3 and 6 months after the intervention. The follow-up data collectors were blinded to group allocation. P<0.05 was considered statistically significant. Results: (I) The average score of CM-PPT was increased from 11.36±2.69 to 11.88±2.40 and 12.83±2.19 in 3 and 6 months respectively after intervention, while control group was decreased from 10.79±2.73 to 10.24±2.62 in 3 months and 9.21±2.09 in 6 months. CM-PPT scores with the main intervention effect and the interaction between intervention and time were both statistically significant (P<0.05), indicating that the physical function of participants with MCI were improved after intervention. (II) The average score of MoCA was increased from 21.52±2.05 to 23.48±1.47 (3 months) and 25.19±1.29 (6 months) after intervention, while control group was decreased from 21.14.79±1.97 to 20.21±1.88 and 19.45±2.00 in 3 and 6 months. The score of MMSE showed the same trend with the score of MoCA. The MoCA score with main intervention effect and the MMSE and MoCA scores with the effect of time, the MMSE and MoCA scores with the interaction between the intervention and time were all statistically significant (P<0.05), showing that the cognitive function of participants with MCI was improved by the intervention. Conclusions: Multi-component exercise training could significantly improve physical function and cognitive function of the elderly with MCI.

Image splicing is one of the most common image tampering operations, where the content of the tampered image usually significantly differs from that of the original one. As a consequence, forensic methods aiming to locate the spliced areas are of great realistic significance. Among these methods, the noise based ones, which utilize the fact that images from different sources tend to have various noise levels, have drawn much attention due to their convenience to implement and the relaxation of some operation specific assumptions. However, the performances of the existing noise based image splicing localization methods are unsatisfactory when the noise difference between the original and spliced regions is relatively small. In this paper, through incorporation of a recent developed noise level estimation algorithm, we propose an effective image splicing localization method. The proposed method performs blockwise noise level estimation of a test image with principal component analysis (PCA)-based algorithm, and segments the tampered region from the original region by kmeans clustering. The experimental results demonstrate the superiority of the proposed method over several state-of-the-art methods, especially for practical image splicing, where the noise difference between the original and spliced regions is typically small.

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