Incentive systems and control in a gamified era

Incentives and control systems are one of the most important research areas for management accounting. Mobilising classic psychological theories, this thesis sheds light on the possibility and potential of gamification as an approach to designing incentives and control systems. On the one hand, this thesis raises the attention of management accounting scholars to further explore the motivational effects of gamification. On the other hand, it also sparks designers of gamification in organisations to consider their current use of gamification to incentivise their employees or users. In the first chapter, a netnographic study is conducted in an online on-demand delivery platform to explain how the gamified incentive system motivates delivery riders to perform and how the gamified incentive system helps create a sense of community among riders, as an incentive factor, to further motivate and retain riders on this platform. In the second chapter, in the same field setting, a survey study is conducted to examine the moderation effect of social comparison orientation and the mediation effect of occupational self-efficacy from the relative performance information in riders’ gamified leaderboards. In the third chapter, another netnographic study is conducted in an online learning platform to explain how the platform uses gamification to change users’ behaviour through the internalisation of external gamified elements and how these internalisations further complement the intrinsic motivation to satisfy the users’ three basic psychological needs autonomy, competence, and relatedness

Exploring Crowdfunding Success in Cross-Culture Framework

With the rapid development of reward-based crowdfunding, how to make creative projects stand out is of great significance to entrepreneurs and other stakeholders. This study tends to explore the impact of the number of projects within the same category on crowdfunding success and the impact of spatial clustering effect on crowdfunding success. We draw upon a sample of 11,576,590 daily observations of 331,104 projects from Kickstarter, finding a negative association exists between the number of projects within the same category (NPSC) and crowdfunding success, which means that the concurrent impact of the number of projects within the same category (NPSC) on crowdfunding success displays the much larger competitive effects. The preliminary findings are discussed, and it is hoped that this work can be used to explore the key factors influencing the fundraising success of reward-based crowdfunding projects

Brown adipocytes can display a mammary basal myoepithelial cell phenotype in vivo

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13030000) and the CAS-Novonordisk Foundation, as well as grants from the ‘1000 talents’ recruitment program, and a ‘Great-wall professorship’ from the CAS-Novonordisk Foundation all to JRS. We are grateful to all the members of Molecular Energetics Group for their support and discussion of the results. We would like to thank the Center for Biological Imaging from Institute of Biophysics Chinese Academy of Sciences and Professor Zhaohui Wang's Lab from Institute of Genetics and Developmental Biology Chinese Academy of Sciences for confocal microscopy and the Center for Developmental Biology from Institute of Genetics and Developmental Biology Chinese Academy of Sciences and Dr. Jai from Core Facility for Protein Research from Institute of Biophysics Chinese Academy of Sciences for flow cytometry. We are grateful to Dr. Kuang from Purdue University and Dr. Zhu from Chinese Academy of Medical Sciences Peking Union Medical College for the kind donation of Myf5-Cre mice and Dr. Wolfrum from the Institute of Food Nutrition and Health at the ETH Zurich for the kind donation of the Ucp1-DTR mice. Xun Huang provided valuable comments on previous versions of the manuscript.Peer reviewedPublisher PD

A Stealthy and Robust Fingerprinting Scheme for Generative Models

This paper presents a novel fingerprinting methodology for the Intellectual Property protection of generative models. Prior solutions for discriminative models usually adopt adversarial examples as the fingerprints, which give anomalous inference behaviors and prediction results. Hence, these methods are not stealthy and can be easily recognized by the adversary. Our approach leverages the invisible backdoor technique to overcome the above limitation. Specifically, we design verification samples, whose model outputs look normal but can trigger a backdoor classifier to make abnormal predictions. We propose a new backdoor embedding approach with Unique-Triplet Loss and fine-grained categorization to enhance the effectiveness of our fingerprints. Extensive evaluations show that this solution can outperform other strategies with higher robustness, uniqueness and stealthiness for various GAN models

Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding

Answer grounding aims to reveal the visual evidence for visual question answering (VQA), which entails highlighting relevant positions in the image when answering questions about images. Previous attempts typically tackle this problem using pretrained object detectors, but without the flexibility for objects not in the predefined vocabulary. However, these black-box methods solely concentrate on the linguistic generation, ignoring the visual interpretability. In this paper, we propose Dual Visual-Linguistic Interaction (DaVI), a novel unified end-to-end framework with the capability for both linguistic answering and visual grounding. DaVI innovatively introduces two visual-linguistic interaction mechanisms: 1) visual-based linguistic encoder that understands questions incorporated with visual features and produces linguistic-oriented evidence for further answer decoding, and 2) linguistic-based visual decoder that focuses visual features on the evidence-related regions for answer grounding. This way, our approach ranked the 1st place in the answer grounding track of 2022 VizWiz Grand Challenge.Comment: Accepted to CVPR 2022 VizWiz Worksho

A Eulerian–Lagrangian Coupled Method for the Simulation of Submerged Granular Column Collapse

From MDPI via Jisc Publications RouterHistory: accepted 2021-05-29, pub-electronic 2021-06-03Publication status: PublishedA two-fluid Eulerian–Lagrangian coupled model is developed to investigate the complex interactions between solid particles and the ambient water during the process of submerged granular column collapse. In this model, the water phase is considered to be a Newtonian fluid, whereas the granular column is modeled as an elastic–perfectly plastic material. The water flow field is calculated by the mesh-based Eulerian Finite Volume Method (FVM), with the free surface captured by the Volume-of-Fluid (VOF) technique. The large deformation of the granular material is simulated by the mesh-free, particle-based Lagrangian Smoothed Particle Hydrodynamics method (SPH). Information transfer between Eulerian nodes and Lagrangian particles is performed by the aid of the SPH interpolation function. Both dry and submerged granular column collapses are simulated with the proposed model. Experiments of the submerged cases are also conducted for comparison. Effects of dilatancy (compaction) of initially dense (loose) packing granular columns on the mixture dynamics are investigated to reveal the mechanisms of different flow regimes. Pore water pressure field and granular velocity field are in good agreement between our numerical results and experimental observations, which demonstrates the capability of the proposed Eulerian–Lagrangian coupled method in dealing with complex submerged water–granular mixture flows

No seasonal variation in physical activity of Han Chinese living in Beijing

Acknowledgements We are also grateful for the support of all the volunteers who participated in our study. We are grateful to Beijing Urban Ecosystem Research Station provided the hourly temperature and PM 2.5 data. We are grateful to the USA CDC for the loan of some of the GT3X accelerometers used in this study. Funding This study was funded by National Natural Science Foundation of China (NSFC 91431102) and International Cooperation Program of Chinese Academy of Sciences (GJHZ1660). John R. Speakman was supported by the 1000 talents program of the Chinese government and a Wolfson merit award from the Royal Society.Peer reviewedPublisher PD