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There are substantial differences between the Chinese and US education systems. One difference is in the design and use of assessment due to differences in educational policies. This study described the differences in student learning outcomes, instructional approaches, and learner motivation in physical education as consequences of the policies in the two countries. Objectively measured data on skill and knowledge achievement and instructional procedures, and self-report data on student motivation were collected from a random sample of 870 students in 24 whole classes from eight Chinese middle schools and 1213 students in 39 classes from 15 US middle schools. Multivariate analyses of variance on class means revealed that Chinese students outperformed their US peers in skills, perhaps because skills were part of the high-stake tests for advancement in schooling. They were outperformed by the US students in a fitness knowledge test, perhaps because knowledge was not part of the high-stake tests. The differences in learning outcomes, instructional approaches, and motivation seem to suggest strong differentiated influences from the two countries' respective educational environments and assessment policies.

Hyperspectral image (HSIs) denoising is a preprocessing step that plays a crucial role in many applications used in Earth observation missions. Low-rank tensor representation can be utilized to restore mixed-noise HSIs, such as those affected by mixed Gaussian, impulse, stripe, and deadline noises. Although there is a considerable body of research on spatial and spectral prior knowledge concerning subspace, the correlation between the spectral continuity and the nonlocal sparsity of the spectral and spatial factors is not yet fully understood. To address this deficiency, in the present study, we determined the correlation between these factors using a cascaded technique, and we describe in this paper the double-factor tensor cascaded-rank (DFTCR) minimization method that was used. The information existing in the nonlocal sparsity property of the spatial factor was employed to promote a geometrical feature representation, and a tensor cascaded-rank minimization approach was introduced as a nonlocal self-similarity to promote restoration quality. The continuity between the difference and nonlocal gradient sparsity constraints of the spectral factor was also introduced to learn the basis. Furthermore, to estimate the solutions of the proposed model, we developed an algorithm based on the alternating direction method of multipliers (ADMM). The performance of the DFTCR method was tested by a comparison with eleven established denoising methods for HSIs. The results showed that the proposed DFTCR method exhibited superior performance in the removal of mixed noise from HSIs. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) constitutes a pivotal physical parameter in the investigation of atmospheric, oceanic, and air–sea exchange processes. The retrieval of SST through satellite passive microwave (PMW) technology effectively mitigates the interference posed by cloud cover, addressing a longstanding challenge. Nevertheless, conventional functional representations often fall short in capturing the intricate interplay of factors influencing SST. Leveraging neural networks (NNs), known for their adeptness in tackling nonlinear and intricate problems, holds great promise in SST retrieval. Nonetheless, NNs exhibit a high sensitivity to initial weights and thresholds, rendering them susceptible to local optimization issues. In this study, we present a novel machine learning (ML) approach for SST retrieval using PMW measurements, drawing from the Sparrow Search Algorithm (SSA) and Back-Propagation neural network (BPNN) methodologies. The core premise involves the optimization of the BP neural network's initial weights and thresholds through an enhanced SSA algorithm employing various optimization strategies. This optimization aims to provide superior parameters for the training of the BP neural network. Employing AMSR2 brightness temperature data, sea surface wind speed data, and buoy SST measurements, we construct the ISSA-BP model for sea surface temperature retrieval. The validation of the ISSA-BP model against the test data is conducted and compared against the multiple linear regression (MLR) model, an unoptimized BP model, and an unimproved SSA-BP model. The results manifest an impressive R-squared (R2) value of 0.9918 and a root-mean-square error (RMSE) of 0.8268 °C for the ISSA-BP model, attesting to its superior accuracy. Furthermore, the ISSA-BP model was applied to retrieve global sea surface temperatures on 15 July 2022, yielding an R2 of 0.9926 and an RMSE of 0.7673 °C for the OISST product on the same day, underscoring its excellent concordance. The results indicate that SST can be efficiently and accurately retrieved using the model proposed in this paper, based on satellite PMW measurements. This finding underscores the potential of employing machine learning algorithms for SST retrieval and offers a valuable reference for future studies focusing on the retrieval of other sea surface parameters. [ABSTRACT FROM AUTHOR]

The purpose of this article is to describe published scholarly and research work to determine the extent to which they contributed to the physical education reform during 2000-2010 in China. Using an analytical reasoning approach, we analyzed 730 scholarly articles on K-12 physical education published in the 6 top kinesiology scholarly journals. Both conceptual synthesis and statistical reasoning approaches were used in the analysis. It is clear that variation in the number of empirical research fluctuated corresponding in time to important decisions made by the central government. The number of empirical research declined sharply after the central government published its initial guidelines for K-12 physical education. Statistical evidence suggests that empirical research should have made more contribution to formulating the new 2012 guidelines.

To be successful in learning, students need to be motivated to engage and learn. The domain-specificity motivation theory articulates that student motivation is often determined by the content being taught to them. The purpose of this study was to extend the theory by determining domain-specificity of situational interest and expectancy-value motivation in terms of engagement and achievement outcomes in physical education. A random student sample (N = 346) from eight Chinese middle schools provided data of situational interest, expectancy-value, engagement, and knowledge and skills acquired. Results from correlation, regression, and structural equation model analyses revealed causal inferences demonstrating differentiated effects of motivation components on the outcome measures: task values were specific to knowledge outcome, expectancy beliefs to skills, and situational interest to engagement. The findings imply that physical educators need to adopt motivation strategies compatible to specific learning outcomes to maximize student motivation for engagement and achievement.

Students' different perceptions of task values influence their learning experience and achievement in physical education. Framed using the subjective task value construct, this study was conducted to determine the extent to which male and female Chinese middle schoolers with different body sizes differed in their perception of the task values. A second goal of the study was to identify the extent to which the task values along with gender and body size predicted students' performance on knowledge and physical skill tests. Data from a random sample of students (N = 860) from eight Chinese middle schools revealed that the boys appreciated intrinsic (p = 0.001) and utility values (p = 02); both boys and girls, however, equally appreciated the attainment value (p = 0.73). The boys performed better in physical skill tests than the girls (p = 0.001), whereas the girls scored higher in knowledge tests than the boys (p = 0.04). Regression analyses revealed that gender is the only predictor for performance on both knowledge and skill tests. Utility value and body size were predictors for skill, not for knowledge. These findings indicate that Chinese middle school boys and girls differed in valuing and achieving in physical education. The findings imply that Chinese boys need to strengthen cognitive learning and girls need to strengthen psychomotor skill development in physical education. (Contains 6 tables.)

The sparsity regularization based on the L1 norm can significantly stabilize the solution of the ill-posed sparsity inversion problem, e.g., azimuth super-resolution of radar forward-looking imaging, which can effectively suppress the noise and reduce the blurry effect of the convolution kernel. In practice, the total variation (TV) and TV-sparsity (TVS) regularizations based on the L1 norm are widely adopted in solving the ill-posed problem. Generally, however, the existence of bias is ignored, which is incomplete in theory. This paper places emphasis on analyzing the partially biased property of the L1 norm. On this basis, we derive the partially bias-corrected solution of TVS and TV, which improves the rigor of the theory. Lastly, two groups of experimental results reflect that the proposed methods with partial bias correction can preserve higher quality than those without bias correction. The proposed methods not only distinguish the adjacent targets, suppress the noise, and preserve the shape and size of targets in visual terms. Its improvement of Peak Signal-to-Noise Ratio, Structure-Similarity, and Sum-Squared-Errors assessment indexes are overall 2.15%, 1.88%, and 4.14%, respectively. As such, we confirm the theoretical rigor and practical feasibility of the partially bias-corrected solution with sparsity regularization based on the L1 norm. [ABSTRACT FROM AUTHOR]

Marathon performance is influenced by factors such as aerobic capacity and those related to neuromuscular function. Complex training (CPX) is a multicomponent training method, wherein heavy strength and plyometric exercises alternate within a single session and is an effective method to improve neuromuscular adaptations. This study compared the effects of CPX, heavy strength training (HST) and endurance-strength (EST) combined with running endurance training on neuromuscular adaptations and running performance in 38 recreational marathoners (age:31.4 ± 3.8 years, VO2max:57.6 ± 6.8 ml·kg−1·min−1). Athletes were allocated in 3 groups: CPX, HST and EST and were tested for one maximum repetition strength (1RM), squat jump and countermovement jumps (SJ, CMJ), leg press (LP) concentric and eccentric strength, running economy (RE) and velocity at VO2max (vVO2max) before and after the 6-week intervention. CPX and HST were performed 2 times per week in conjunction with the running endurance training. RE and vVO2max improved in CPX and HST groups (p < 0.01, RE: −5% to −6.4%, vVO2max: 5.7% and 4.2%, respectively) with no change in EST. Similarly, all neuromuscular performance indicators improved in CPX and HST (p < 0.0167, 1RM strength:19.7% to 25.1%, SJ and CMJ: 5.3% to 11.6%, LP concentric and eccentric strength: 5.5% to 18.0%). In summary, 6-week of concurrent CPX or HST and endurance training resulted in similar improvement in maximum strength, RE, and vVO2max. Importantly, both CPX and HST training resulted in greater improvements in eccentric strength and RE compared to EST that performed concurrent endurance-strength and endurance training. [ABSTRACT FROM AUTHOR]

The purpose of this article is to describe published scholarly and research work to determine the extent to which they contributed to the physical education reform during 2000–2010 in China. Using an analytical reasoning approach, we analyzed 730 scholarly articles on K–12 physical education published in the 6 top kinesiology scholarly journals. Both conceptual synthesis and statistical reasoning approaches were used in the analysis. It is clear that variation in the number of empirical research fluctuated corresponding in time to important decisions made by the central government. The number of empirical research declined sharply after the central government published its initial guidelines for K–12 physical education. Statistical evidence suggests that empirical research should have made more contribution to formulating the new 2012 guidelines. [ABSTRACT FROM PUBLISHER]

There are substantial differences between the Chinese and US education systems. One difference is in the design and use of assessment due to differences in educational policies. This study described the differences in student learning outcomes, instructional approaches, and learner motivation in physical education as consequences of the policies in the two countries. Objectively measured data on skill and knowledge achievement and instructional procedures, and self-report data on student motivation were collected from a random sample of 870 students in 24 whole classes from eight Chinese middle schools and 1213 students in 39 classes from 15 US middle schools. Multivariate analyses of variance on class means revealed that Chinese students outperformed their US peers in skills, perhaps because skills were part of the high-stake tests for advancement in schooling. They were outperformed by the US students in a fitness knowledge test, perhaps because knowledge was not part of the high-stake tests. The differences in learning outcomes, instructional approaches, and motivation seem to suggest strong differentiated influences from the two countries' respective educational environments and assessment policies. [ABSTRACT FROM AUTHOR]