An Action Research on Enacting Play-based Pedagogy in a Pre-service Teachers\u27 Art Classroom

As a school-based art educator, I advocate for an educational environment that embraces and values concepts of play and play-based pedagogy and encourage understandings of the significant role of play in teaching and learning and its relation to art, artifacts, and multiculturalism. This thesis documents an action research project, reflecting a dialogue about play-based art education in a college classroom. As a social constructivist and an advocate for multiculturalism, I introduced knowledge on play-based pedagogy and its benefits to college students and studied my practices in relation to student learning, especially those students in pre-service teacher education programs. Concepts associated with play included true or authentic play, material rich environmental learning, integration of play with art and other disciplines, and multiculturalism and in relation to social and cultural contexts. The role of art and artifacts was used to build a sense of the connection between art and play and its relations. This action research helped me build a sense of practice in relationship to learners in my classroom and through two cycles of reflection on how play could be used as learning tool and as an integral of a curriculum for young children. Data was collected over the course of one semester and explored using narrative analysis, focusing on values and beliefs associated with play-based art education

QuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars

Real-time tracking of human body motion is crucial for interactive and immersive experiences in AR/VR. However, very limited sensor data about the body is available from standalone wearable devices such as HMDs (Head Mounted Devices) or AR glasses. In this work, we present a reinforcement learning framework that takes in sparse signals from an HMD and two controllers, and simulates plausible and physically valid full body motions. Using high quality full body motion as dense supervision during training, a simple policy network can learn to output appropriate torques for the character to balance, walk, and jog, while closely following the input signals. Our results demonstrate surprisingly similar leg motions to ground truth without any observations of the lower body, even when the input is only the 6D transformations of the HMD. We also show that a single policy can be robust to diverse locomotion styles, different body sizes, and novel environments

A unified formulation for circle and polygon concrete-filled steel tube columns under axial compression

Current design practice of concrete-filled steel tube (CFST) columns uses different formulas for different section profiles to predict the axial load bearing capacity. It has always been a challenge and practically important issue for researchers and design engineers who want to find a unified formula that can be used in the design of the columns with various sections, including solid, hollow, circular and polygonal sections. This has been driven by modern design requirements for continuous optimization of structures in terms of not only the use of materials, but also the topology of structural components. This paper extends the authors’ previous work [1] on a unified formulation of the axial load bearing capacity for circular hollow and solid CFST columns to, now, including hollow and solid CFST columns with regular polygonal sections. This is done by taking a circular section as a special case of a polygonal one. Finally, a unified formula is proposed for calculating the axial load bearing capacity of solid and hollow CFST columns with either circular or polygonal sections. In addition, laboratory tests on hollow circular and square CFST long columns are reported. These results are useful addition to the very limited open literature on testing these columns, and are also as a part of the validation process of the proposed analytical formulas

Methyl mercury concentrations in seafood collected from Zhoushan Islands, Zhejiang, China, and their potential health risk for the fishing community

Seafood is an important exposure route for mercury, especially methyl mercury (MeHg). Therefore, we quantified MeHg concentrations in 69 species of seafood including fish, crustaceans and mollusks collected from Zhoushan Islands, China. MeHg concentrations ranged from 1. The daily dietary intake and hazard quotient for MeHg were calculated to estimate exposure and health risk through seafood consumption by local inhabitants. The calculated HQ was lower than 1, thus indicating that the exposure was below the risk threshold of related chronic diseases. However, higher MeHg concentrations in fish species such as Scoliodon sorrakowah and Auxis thazard are concerning and may pose health risk through continuous consumption by local inhabitants.China Spark Program (2015GA700094); Medical Health Science Foundation Program of the Health Department of Zhejiang Province (2020RC137); Science and technology Program of Zhoushan City (2017C32089); Medical Health Science Foundation Program of the Health Department of Zhoushan City (2018G02)) and the Chinese Academy of Sciences Fellowships under the Chinese Academy of Sciences President's International Fellowship for Visiting Scientists (2018VCC0002).info:eu-repo/semantics/publishedVersio

Understanding the Drivers’ Continuous Intention of Online Car Booking Service

Based upon commitment theory, this study explores the effect of organizational commitment on drivers’ continuous intention to provide online car booking service. We further investigate the antecedent factors of the drivers’ organizational commitment. Online survey is utilized to collect data from the drivers who are providing service current from various companies in China. The results show that affective commitment and normative commitment serve as the crucial determinants to affect drivers’ continuous intention. Besides, social interaction ties with company, with customers, drivers’ rewards, as well as their sense of self-value cultivate their organizational commitment perception. We then propose our theoretical and practical implications according to the findings of this study

DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics

Synthesizing realistic human movements, dynamically responsive to the environment, is a long-standing objective in character animation, with applications in computer vision, sports, and healthcare, for motion prediction and data augmentation. Recent kinematics-based generative motion models offer impressive scalability in modeling extensive motion data, albeit without an interface to reason about and interact with physics. While simulator-in-the-loop learning approaches enable highly physically realistic behaviors, the challenges in training often affect scalability and adoption. We introduce DROP, a novel framework for modeling Dynamics Responses of humans using generative mOtion prior and Projective dynamics. DROP can be viewed as a highly stable, minimalist physics-based human simulator that interfaces with a kinematics-based generative motion prior. Utilizing projective dynamics, DROP allows flexible and simple integration of the learned motion prior as one of the projective energies, seamlessly incorporating control provided by the motion prior with Newtonian dynamics. Serving as a model-agnostic plug-in, DROP enables us to fully leverage recent advances in generative motion models for physics-based motion synthesis. We conduct extensive evaluations of our model across different motion tasks and various physical perturbations, demonstrating the scalability and diversity of responses.Comment: SIGGRAPH Asia 2023, Video https://youtu.be/tF5WW7qNMLI, Website: https://stanford-tml.github.io/drop