Shanghai Jiao Tong University

About: Shanghai Jiao Tong University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Population & Cancer. The organization has 157524 authors who have published 184620 publications receiving 3451038 citations. The organization is also known as: Shanghai Communications University & Shanghai Jiaotong University.

Soft wall-climbing robots

Abstract: Existing robots capable of climbing walls mostly rely on rigid actuators such as electric motors, but soft wall-climbing robots based on muscle-like actuators have not yet been achieved. Here, we report a tethered soft robot capable of climbing walls made of wood, paper, and glass at 90° with a speed of up to 0.75 body length per second and multimodal locomotion, including climbing, crawling, and turning. This soft wall-climbing robot is enabled by (i) dielectric-elastomer artificial muscles that generate fast periodic deformation of the soft robotic body, (ii) electroadhesive feet that give spatiotemporally controlled adhesion of different parts of the robot on the wall, and (iii) a control strategy that synchronizes the body deformation and feet electroadhesion for stable climbing. We further demonstrate that our soft robot could carry a camera to take videos in a vertical tunnel, change its body height to navigate through a confined space, and follow a labyrinth-like planar trajectory. Our soft robot mimicked the vertical climbing capability and the agile adaptive motions exhibited by soft organisms.

Rapid aerosol particle growth and increase of cloud condensation nucleus activity by secondary aerosol formation and condensation: A case study for regional air pollution in northeastern China

Abstract: [1] This study was part of the international field measurement Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing-2006). We investigated a new particle formation event in a highly polluted air mass at a regional site south of the megacity Beijing and its impact on the abundance and properties of cloud condensation nuclei (CCN). During the 1-month observation, particle nucleation followed by significant particle growth on a regional scale was observed frequently (~30%), and we chose 23 August 2006 as a representative case study. Secondary aerosol mass was produced continuously, with sulfate, ammonium, and organics as major components. The aerosol mass growth rate was on average 19 μg m -3 h -1 during the late hours of the day. This growth rate was observed several times during the 1-month intensive measurements. The nucleation mode grew very quickly into the size range of CCN, and the CCN size distribution was dominated by the growing nucleation mode (up to 80% of the total CCN number concentration) and not as usual by the accumulation mode. At water vapor supersaturations of 0.07-0.86%, the CCN number concentrations reached maximum values of 4000-19,000 cm -3 only 6-14 h after the nucleation event. During particle formation and growth, the effective hygroscopicity parameter κ increased from about 0.1-0.3 to 0.35-0.5 for particles with diameters of 40-90 nm, but it remained nearly constant at ~0.45 for particles with diameters of ~190 nm. This result is consistent with aerosol chemical composition data, showing a pronounced increase of sulfate.

Investigating the Structure and Meaning of Public Service Motivation across Populations: Developing an International Instrument and Addressing Issues of Measurement Invariance

Abstract: The growth in international research on public service motivation (PSM) raises a number of important questions about the degree to which the theory and research developed in one country can contribute to our understanding of PSM in other counties. To help address this issue, this study revisits the conceptual and operational definitions of PSM to address weaknesses previously noted in the literature. Although some important steps have been taken to both improve and internationalize the PSM scale, this work has been done incrementally. In contrast, this study takes a more systematic and comprehensive approach by combining the efforts of international PSM scholars to develop and then test a revised measurement instrument for PSM in 12 countries. Although the resulting four dimensional 16-item measure of PSM reported here provides a better theoretical and empirical foundation for the measurement of PSM, our results suggest that the exact meaning and scaling of PSM dimensions are likely to differ across cultures and languages. These results raise serious concerns regarding the ability to develop a single universal scale of PSM, or making direct comparisons of PSM across countries. Its earlier versions were delivered at the Annual Conference of the European Group for Public Administration, Toulouse, France, September 8–10, 2010, and at the 11th National Public Management Research Conference at Syracuse University, Syracuse, NY, June 2–4, 2011. Address correspondence to the author at smook@

News impact on stock price return via sentiment analysis

Abstract: Financial news articles are believed to have impacts on stock price return. Previous works model news pieces in bag-of-words space, which analyzes the latent relationship between word statistical patterns and stock price movements. However, news sentiment, which is an important ring on the chain of mapping from the word patterns to the price movements, is rarely touched. In this paper, we first implement a generic stock price prediction framework, and plug in six different models with different analyzing approaches. To take one step further, we use Harvard psychological dictionary and Loughran–McDonald financial sentiment dictionary to construct a sentiment space. Textual news articles are then quantitatively measured and projected onto the sentiment space. Instance labeling method is rigorously discussed and tested. We evaluate the models' prediction accuracy and empirically compare their performance at different market classification levels. Experiments are conducted on five years historical Hong Kong Stock Exchange prices and news articles. Results show that (1) at individual stock, sector and index levels, the models with sentiment analysis outperform the bag-of-words model in both validation set and independent testing set; (2) the models which use sentiment polarity cannot provide useful predictions; (3) there is a minor difference between the models using two different sentiment dictionaries.

IoT-Based Smart Rehabilitation System

Abstract: Internet of Things (IoT) makes all objects become interconnected and smart, which has been recognized as the next technological revolution. As its typical case, IoT-based smart rehabilitation systems are becoming a better way to mitigate problems associated with aging populations and shortage of health professionals. Although it has come into reality, critical problems still exist in automating design and reconfiguration of such a system enabling it to respond to the patient's requirements rapidly. This paper presents an ontology-based automating design methodology (ADM) for smart rehabilitation systems in IoT. Ontology aids computers in further understanding the symptoms and medical resources, which helps to create a rehabilitation strategy and reconfigure medical resources according to patients' specific requirements quickly and automatically. Meanwhile, IoT provides an effective platform to interconnect all the resources and provides immediate information interaction. Preliminary experiments and clinical trials demonstrate valuable information on the feasibility, rapidity, and effectiveness of the proposed methodology.