Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

Effect of time spent outdoors at school on the development of myopia among children in China a randomized clinical trial

Abstract: Importance Myopia has reached epidemic levels in parts of East and Southeast Asia. However, there is no effective intervention to prevent the development of myopia. Objective To assess the efficacy of increasing time spent outdoors at school in preventing incident myopia. Design, Setting, and Participants Cluster randomized trial of children in grade 1 from 12 primary schools in Guangzhou, China, conducted between October 2010 and October 2013. Interventions For 6 intervention schools (n = 952 students), 1 additional 40-minute class of outdoor activities was added to each school day, and parents were encouraged to engage their children in outdoor activities after school hours, especially during weekends and holidays. Children and parents in the 6 control schools (n = 951 students) continued their usual pattern of activity. Main Outcomes and Measures The primary outcome measure was the 3-year cumulative incidence rate of myopia (defined using the Refractive Error Study in Children spherical equivalent refractive error standard of ≤−0.5 diopters [D]) among the students without established myopia at baseline. Secondary outcome measures were changes in spherical equivalent refraction and axial length among all students, analyzed using mixed linear models and intention-to-treat principles. Data from the right eyes were used for the analysis. Results There were 952 children in the intervention group and 951 in the control group with a mean (SD) age of 6.6 (0.34) years. The cumulative incidence rate of myopia was 30.4% in the intervention group (259 incident cases among 853 eligible participants) and 39.5% (287 incident cases among 726 eligible participants) in the control group (difference of −9.1% [95% CI, −14.1% to −4.1%]; P P = .04). Elongation of axial length was not significantly different between the intervention group (0.95 mm) and the control group (0.98 mm) (difference of −0.03 mm [95% CI, −0.07 to 0.003 mm]; P = .07). Conclusions and Relevance Among 6-year-old children in Guangzhou, China, the addition of 40 minutes of outdoor activity at school compared with usual activity resulted in a reduced incidence rate of myopia over the next 3 years. Further studies are needed to assess long-term follow-up of these children and the generalizability of these findings. Trial Registration clinicaltrials.gov Identifier:NCT00848900

Nanomaterials in Targeting Cancer Stem Cells for Cancer Therapy.

Abstract: Cancer stem cells (CSCs) have been identified in almost all cancers and give rise to metastases and can also act as a reservoir of cancer cells that may cause a relapse after surgery, radiation or chemotherapy. Thus they are obvious targets in therapeutic approaches and also a great challenge in cancer treatment. The threat presented by CSCs lies in their unlimited proliferative ability and multidrug resistance. These findings have necessitated an effective novel strategy to target CSCs for cancer treatment. Nanomaterials are on the route to providing novel methods in cancer therapies. Although there have been a large number of excellent work in the field of targeted cancer therapy, it remains an open question how nanomaterials can meet future demands for targeting and eradicating of cancer stem cells. In this review, we summarized recent and highlighted future prospects for targeting CSCs for cancer therapies by using a variety of nanomaterials.

Water-evaporation-induced electricity with nanostructured carbon materials

Abstract: Water evaporation from the surface of cheap carbon-black materials can be used to generate sustained voltages of up to 1 V under ambient conditions.

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

Abstract: Ubiquitous sensors and smart devices from factories and communities are generating massive amounts of data, and ever-increasing computing power is driving the core of computation and services from the cloud to the edge of the network. As an important enabler broadly changing people’s lives, from face recognition to ambitious smart factories and cities, developments of artificial intelligence (especially deep learning, DL) based applications and services are thriving. However, due to efficiency and latency issues, the current cloud computing service architecture hinders the vision of “providing artificial intelligence for every person and every organization at everywhere”. Thus, unleashing DL services using resources at the network edge near the data sources has emerged as a desirable solution. Therefore, edge intelligence , aiming to facilitate the deployment of DL services by edge computing, has received significant attention. In addition, DL, as the representative technique of artificial intelligence, can be integrated into edge computing frameworks to build intelligent edge for dynamic, adaptive edge maintenance and management. With regard to mutually beneficial edge intelligence and intelligent edge , this paper introduces and discusses: 1) the application scenarios of both; 2) the practical implementation methods and enabling technologies, namely DL training and inference in the customized edge computing framework; 3) challenges and future trends of more pervasive and fine-grained intelligence. We believe that by consolidating information scattered across the communication, networking, and DL areas, this survey can help readers to understand the connections between enabling technologies while promoting further discussions on the fusion of edge intelligence and intelligent edge , i.e., Edge DL.