RESUMEN
Memristor-based physical reservoir computing holds significant potential for efficiently processing complex spatiotemporal data, which is crucial for advancing artificial intelligence. However, owing to the single physical node mapping characteristic of traditional memristor reservoir computing, it inevitably induces high repeatability of eigenvalues to a certain extent and significantly limits the efficiency and performance of memristor-based reservoir computing for complex tasks. Hence, this work firstly reports an artificial light-emitting synaptic (LES) device with dual photoelectric output for reservoir computing, and a reservoir system with mixed physical nodes is proposed. The system effectively transforms the input signal into two eigenvalue outputs using a mixed physical node reservoir comprising distinct physical quantities, namely optical output with nonlinear optical effects and electrical output with memory characteristics. Unlike previously reported memristor-based reservoir systems, which pursue rich reservoir states in one physical dimension, our mixed physical node reservoir system can obtain reservoir states in two physical dimensions with one input without increasing the number and types of devices. The recognition rate of the artificial light-emitting synaptic reservoir system can achieve 97.22% in MNIST recognition. Furthermore, the recognition task of multichannel images can be realized through the nonlinear mapping of the photoelectric dual reservoir, resulting in a recognition accuracy of 99.25%. The mixed physical node reservoir computing proposed in this work is promising for implementing the development of photoelectric mixed neural networks and material-algorithm collaborative design.
RESUMEN
BACKGROUND: Post-vaccination safety is a major public health concern. The genetic predisposition on immune response has not been clearly identified. Clarifying whether individual genetic predisposition plays a role on adverse events (AEs) is critical for the prevention of AEs. METHODS: From July 2019 to June 2020, we performed a case-control study among children aged 3-24 months in seven Chinese provinces. Each child received a combination vaccination against diphtheria, tetanus, acellular pertussis, and Haemophilus influenzae type b (DTaP-Hib). Through daily telephone follow-up, we collected AEs within seven days. Oral swab samples were collected to investigate the effects of single nucleotide polymorphisms (SNPs) on the risk of AEs. RESULTS: 304 participants were included in the study. In univariate analysis, we discovered three protective SNPs (rs452204, OR = 0.67, P = 0.0352; rs9282763 and rs839, OR = 0.64, P = 0.0256) and one risk SNP (rs9610, OR = 2.20, P = 0.0397). In multivariate analysis, the effects of rs452204 and rs839 were found to be stable. The interaction between rs452204 and rs9610 was observed (OR = 7.25, 95% CI: 1.44-36.58, P = 0.0165). CONCLUSION: Genetic predisposition was associated with the risk of AEs after DTaP-Hib vaccination, emphasizing the potential application in the prevention of AEs.