South China University of Technology

About: South China University of Technology is a education organization based out in Guangzhou, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 62343 authors who have published 69468 publications receiving 1251592 citations. The organization is also known as: SCUT & Huánán Lǐgōng Dàxué.

Effect of degree of hydrolysis on the antioxidant activity of loach (Misgurnus anguillicaudatus) protein hydrolysates.

Abstract: Loach ( Misgurnus anguillicaudatus ) proteins were hydrolysed by papain and Protamex, the antioxidant activity of loach protein hydrolysates (LPH) was investigated. The results demonstrated that extensive hydrolysis by papain and Protamex led to the browning of the hydrolysates. When the degree of hydrolysis (DH) was 23%, hydrolysates prepared by papain (HA) exhibited the strongest antioxidant activity. The maximum values of the hydroxyl, 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging activities and the reducing power were 56.1%, 95.5%, 2.80 mM and 1.46, respectively. The hydrolysates prepared by Protamex (HB) showed the strongest hydroxyl radical scavenging activity (55.0%) at DH 28%, DPPH radical scavenging activity (92.2%) and ABTS radical scavenging activity (2.81 mM) at DH 23%, and the reducing power (1.17) at DH 33%. At the same DH value, there were significant ( p Industrial relevance Loach has long been employed as a traditional Chinese medicine for the treatment of many kinds of diseases. From our previous work, loach was determined to be a good source of protein (accounts for approximately 17% (w/w) of the body weight). In this work, loach proteins were hydrolyzed by papain and Protamex to specific extent. The effect of DH on the antioxidant activities of hydrolysates was investigated. The results indicated that loach protein hydrolysates were potent antioxidants which were significantly affected by DH. This research is helpful for extensive development of loach product.

Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives

Abstract: This paper proposes an enhanced robot skill learning system considering both motion generation and trajectory tracking. During robot learning demonstrations, dynamic movement primitives (DMPs) are used to model robotic motion. Each DMP consists of a set of dynamic systems that enhances the stability of the generated motion toward the goal. A Gaussian mixture model and Gaussian mixture regression are integrated to improve the learning performance of the DMP, such that more features of the skill can be extracted from multiple demonstrations. The motion generated from the learned model can be scaled in space and time. Besides, a neural-network-based controller is designed for the robot to track the trajectories generated from the motion model. In this controller, a radial basis function neural network is used to compensate for the effect caused by the dynamic environments. The experiments have been performed using a Baxter robot and the results have confirmed the validity of the proposed methods.

Building the sequence map of the human pan-genome

Abstract: Here we integrate the de novo assembly of an Asian and an African genome with the NCBI reference human genome, as a step toward constructing the human pan-genome. We identified ∼5 Mb of novel sequences not present in the reference genome in each of these assemblies. Most novel sequences are individual or population specific, as revealed by their comparison to all available human DNA sequence and by PCR validation using the human genome diversity cell line panel. We found novel sequences present in patterns consistent with known human migration paths. Cross-species conservation analysis of predicted genes indicated that the novel sequences contain potentially functional coding regions. We estimate that a complete human pan-genome would contain ∼19–40 Mb of novel sequence not present in the extant reference genome. The extensive amount of novel sequence contributing to the genetic variation of the pan-genome indicates the importance of using complete genome sequencing and de novo assembly.

A survey of human-centered intelligent robots: issues and challenges

Abstract: Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning

Abstract: Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.