Southwest University

About: Southwest University is a education organization based out in Chongqing, China. It is known for research contribution in the topics: Gene & Population. The organization has 29772 authors who have published 27755 publications receiving 409441 citations. The organization is also known as: Southwest University in Chongqing & SWU.

Robust prediction of individual creative ability from brain functional connectivity

Abstract: People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis

Abstract: This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex systems from the perspective of data processing. As a matter of fact, an FDD system is a data-processing system on the basis of information redundancy, in which the data and human's understanding of the data are two fundamental elements. Human's understanding may be an explicit input-output model representing the relationship among the system's variables. It may also be represented as knowledge implicitly (e.g., the connection weights of a neural network). Therefore, FDD is done through some kind of modeling, signal processing, and intelligence computation. In this paper, a variety of FDD techniques are reviewed within the unified data-processing framework to give a full picture of FDD and achieve a new level of understanding. According to the types of data and how the data are processed, the FDD methods are classified into three categories: model-based online data-driven methods, signal-based methods, and knowledge-based history data-driven methods. An outlook to the possible evolution of FDD in industrial automation, including the hybrid FDD and the emerging networked FDD, are also presented to reveal the future development direction in this field.

Threshold Dynamics for Compartmental Epidemic Models in Periodic Environments

Abstract: The basic reproduction ratio and its computation formulae are established for a large class of compartmental epidemic models in periodic environments. It is proved that a disease cannot invade the disease-free state if the ratio is less than unity and can invade if it is greater than unity. It is also shown that the basic reproduction number of the time-averaged autonomous system is applicable in the case where both the matrix of new infection rate and the matrix of transition and dissipation within infectious compartments are diagonal, but it may underestimate and overestimate infection risks in other cases. The global dynamics of a periodic epidemic model with patch structure is analyzed in order to study the impact of periodic contacts or periodic migrations on the disease transmission.

Self-assembled, aptamer-tethered DNA nanotrains for targeted transport of molecular drugs in cancer theranostics

Abstract: Nanotechnology has allowed the construction of various nanostructures for applications, including biomedicine. However, a simple target-specific, economical, and biocompatible drug delivery platform with high maximum tolerated doses is still in demand. Here, we report aptamer-tethered DNA nanotrains (aptNTrs) as carriers for targeted drug transport in cancer therapy. Long aptNTrs were self-assembled from only two short DNA upon initiation by modified aptamers, which worked like locomotives guiding nanotrains toward target cancer cells. Meanwhile, tandem “boxcars” served as carriers with high payload capacity of drugs that were transported to target cells and induced selective cytotoxicity. aptNTrs enhanced maximum tolerated dose in nontarget cells. Potent antitumor efficacy and reduced side effects of drugs delivered by biocompatible aptNTrs were demonstrated in a mouse xenograft tumor model. Moreover, fluorophores on nanotrains and drug fluorescence dequenching upon release allowed intracellular signaling of nanotrains and drugs. These results make aptNTrs a promising targeted drug transport platform for cancer theranostics.