Batch process fault detection for multi-stage broad learning system.

In the real industrial production process, some minor faults are difficult to be detected by multivariate statistical analysis methods with mean and variance as detection indicators due to the aging equipment and catalyst deactivation. With structural characteristics, deep neural networks can better extract data features to detect such faults. However, most deep learning models contain a large number of connection parameters between layers, which causes the training time-consuming and thus makes it difficult to achieve a fast-online response.

Pupillometric decoding of high-level musical imagery.

Humans report imagining sound where no physical sound is present: we replay conversations, practice speeches, and "hear" music all within the confines of our minds. Research has identified neural substrates underlying auditory imagery; yet deciphering its explicit contents has been elusive. Here we present a novel pupillometric method for decoding what individuals hear "inside their heads".

Pupil dilation patterns spontaneously synchronize across individuals during shared attention.

Human social behavior relies on the coupling of minds. Here we show that patterns of pupil dilations reveal mental coupling between speakers and listeners. Speakers were videotaped and eye-tracked as they discussed positive and negative autobiographical memories.

Semantic Structural Alignment of Neural Representational Spaces Enables Translation between English and Chinese Words.

Two sets of items can share the same underlying conceptual structure, while appearing unrelated at a surface level. Humans excel at recognizing and using alignments between such underlying structures in many domains of cognition, most notably in analogical reasoning. Here we show that structural alignment reveals how different people's neural representations of word meaning are preserved across different languages, such that patterns of brain activation can be used to translate words from one language to another.

Pupil dilation patterns reflect the contents of consciousness.

The study of human consciousness has historically depended on introspection. However, introspection is constrained by what can be remembered and verbalized. Here, we demonstrate the utility of high temporal resolution pupillometry to track the locus of conscious attention dynamically, over a single trial.

Pupil dilation dynamics track attention to high-level information.

It has long been thought that the eyes index the inner workings of the mind. Consistent with this intuition, empirical research has demonstrated that pupils dilate as a consequence of attentional effort. Recently, Smallwood et al.