Nothing but Being There Matters: Expectancy-Value Motivation Between U.S. and Chinese Middle School Students

Current literature theorizes that culture-induced expectancy beliefs and values in learning may engage learners of varied cultures in differentiated motivational processes. The purpose of the study was to determine the extent to which U.S. and Chinese middle school students differed in expectancy-value motivation in physical education. Middle school students from the U.S. (n = 813, 14 schools) and China (n = 806, 8 schools) provided data on expectancy-value motivation in physical education. A MANOVA with country as the independent factor and grade level as covariate revealed that the U.S. students held higher expectancy beliefs (p =.001, η2=.62), while the Chinese students showed stronger appreciation for the attainment (p =.001, η2=.33) and utility values (p =.001, η2=.35). The students from both countries equally appreciated the intrinsic value (p =.45). A canonical correlation analysis demonstrated that the expectancy-value motivation declined with age/grade increase at the same pace regardless of culture. These findings clarify for us the cultural influence or non-cultural influence on the expectancy-value motivation in middle school students. They inform us about the potential to develop intrinsic-value based across-cultural motivation strategies as well as the cultural sensitivity of applying motivation strategies focusing on expectancy of success, attainment value, and utility value

OccupancyDETR: Making Semantic Scene Completion as Straightforward as Object Detection

Visual-based 3D semantic occupancy perception (also known as 3D semantic scene completion) is a new perception paradigm for robotic applications like autonomous driving. Compared with Bird's Eye View (BEV) perception, it extends the vertical dimension, significantly enhancing the ability of robots to understand their surroundings. However, due to this very reason, the computational demand for current 3D semantic occupancy perception methods generally surpasses that of BEV perception methods and 2D perception methods. We propose a novel 3D semantic occupancy perception method, OccupancyDETR, which consists of a DETR-like object detection module and a 3D occupancy decoder module. The integration of object detection simplifies our method structurally - instead of predicting the semantics of each voxels, it identifies objects in the scene and their respective 3D occupancy grids. This speeds up our method, reduces required resources, and leverages object detection algorithm, giving our approach notable performance on small objects. We demonstrate the effectiveness of our proposed method on the SemanticKITTI dataset, showcasing an mIoU of 23 and a processing speed of 6 frames per second, thereby presenting a promising solution for real-time 3D semantic scene completion

Embarrassingly Parallel Acceleration of Global Tractography via Dynamic Domain Partitioning

Global tractography estimates brain connectivity by organizing signal-generating fiber segments in an optimal configuration that best describes the measured diffusion-weighted data, promising better stability than local greedy methods with respect to imaging noise. However, global tractography is computationally very demanding and requires computation times that are often prohibitive for clinical applications. We present here a reformulation of the global tractography algorithm for fast parallel implementation amendable to acceleration using multi-core CPUs and general-purpose GPUs. Our method is motivated by the key observation that each fiber segment is affected by a limited spatial neighborhood. In other words, a fiber segment is influenced only by the fiber segments that are (or can potentially be) connected to its two ends and also by the diffusion-weighted signal in its proximity. This observation makes it possible to parallelize the Markov chain Monte Carlo (MCMC) algorithm used in the global tractography algorithm so that concurrent updating of independent fiber segments can be carried out. Experiments show that the proposed algorithm can significantly speed up global tractography, while at the same time maintain or even improve tractography performance

Molten Salt Carbonization and Activation of Biomass to Functional Biocarbon

Functional carbon materials are useful for energy storage, catalysis, and pollutant adsorption, and are in high demand, for which biomass has become a valuable raw material. Molten salt carbonization and activation (MSCA) is a promising approach to converting biomass to functional biocarbon and reducing or neutralizing carbon impact on the environment. It uses a single thermal treatment and features high-efficiency conversion, rapid production, and low resource and processing costs. More importantly, in this process, the unmatched purely ionic environment at high temperatures can lead to in situ activation (pore generation) of the biocarbon and introduce desired ions into the carbon to enable unique functionalities. The biocarbon obtained possesses a fairly large specific surface area (SSA), balanced pore structure, and specific surface oxygen-containing groups for diverse applications. This review explains the fundamental and technological aspects of MSCA of biomass, focusing on the approaches, salt compositions (mixtures), processing conditions, and products. The properties of the obtained biocarbon are analyzed and compared in the context of practical applications. Areas for further investigation are also explored with the hope of this molten salt route becoming optimized and industrialized for a circular economy