Regularized RKHS-Based Subspace Learning for Motor Imagery Classification.

Brain-computer interface (BCI) technology allows people with disabilities to communicate with the physical environment. One of the most promising signals is the non-invasive electroencephalogram (EEG) signal. However, due to the non-stationary nature of EEGs, a subject's signal may change over time, which poses a challenge for models that work across time. Recently, domain adaptive learning (DAL) has shown its superior performance in various classification tasks. In this paper, we propose a regularized reproducing kernel Hilbert space (RKHS) subspace learning algorithm with K-nearest neighbors (KNNs) as a classifier for the task of motion imagery signal classification. First, we reformulate the framework of RKHS subspace learning with a rigorous mathematical inference. Secondly, since the commonly used maximum mean difference (MMD) criterion measures the distribution variance based on the mean value only and ignores the local information of the distribution, a regularization term of source domain linear discriminant analysis (SLDA) is proposed for the first time, which reduces the variance of similar data and increases the variance of dissimilar data to optimize the distribution of source domain data. Finally, the RKHS subspace framework was constructed sparsely considering the sensitivity of the BCI data. We test the proposed algorithm in this paper, first on four standard datasets, and the experimental results show that the other baseline algorithms improve the average accuracy by 2-9% after adding SLDA. In the motion imagery classification experiments, the average accuracy of our algorithm is 3% higher than the other algorithms, demonstrating the adaptability and effectiveness of the proposed algorithm.

Large-scale detection and analysis of adenosine-to-inosine RNA editing during development in Plutella xylostella.

Adenosine-to-inosine (A-to-I) RNA editing is site-specific modification of RNAs that increases the diversity of the transcriptome and proteome. Most insects undergo complete metamorphosis, including four life cycle stages: egg, larva, pupa and adult. Many previous studies have confirmed that RNA-editing events occur in a development-specific manner; in other words, RNA-editing levels change during metamorphosis. Here, we describe an effort to identify the developmental specificity of RNA-editing events using a large-scale computational analysis of RNA-seq data derived from four developmental stages of the diamondback moth, Plutella xylostella. One thousand one hundred and eighty-seven A-to-I RNA-editing sites were predicted to be developmental stage specific (false-discovery rate <0.01) and 1,094 of these sites were located in protein-coding regions. Editing of 152 sites resulted in an altered amino acid residue. A putative adult-specific A-to-I RNA-editing site was verified by comparing cDNA sequences with its corresponding genomic locus at different stages of the P. xylostella life cycle. Our findings will help elucidate the role of A-to-I RNA editing in the regulation of metamorphosis. Further studies detailing changes in the extent of editing are needed to establish how as yet unknown regulatory factors are involved in the editing mechanism and what biological functions' editing serves.

Full-waveform tomography reveals iron spin crossover in Earth's lower mantle.

Three-dimensional models of Earth's seismic structure can be used to identify temperature-dependent phenomena, including mineralogical phase and spin transformations, that are obscured in 1-D spherical averages. Full-waveform tomography maps seismic wave-speeds inside the Earth in three dimensions, at a higher resolution than classical methods. By providing absolute wave speeds (rather than perturbations) and simultaneously constraining bulk and shear wave speeds over the same frequency range, it becomes feasible to distinguish variations in temperature from changes in composition or spin state. We present a quantitative joint interpretation of bulk and shear wave speeds in the lower mantle, using a recently published full-waveform tomography model. At all depths the diversity of wave speeds cannot be explained by an isochemical mantle. Between 1000 and 2500 km depth, hypothetical mantle models containing an electronic spin crossover in ferropericlase provide a significantly better fit to the wave-speed distributions, as well as more realistic temperatures and silica contents, than models without a spin crossover. Below 2500 km, wave speed distributions are explained by an enrichment in silica towards the core-mantle boundary. This silica enrichment may represent the fractionated remains of an ancient basal magma ocean.

iPathCons and iPathDB: an improved insect pathway construction tool and the database.

Insects are one of the most successful animal groups on earth. Some insects, such as the silkworm and honeybee, are beneficial to humans, whereas others are notorious pests of crops. At present, the genomes of 38 insects have been sequenced and made publically available. In addition, the transcriptomes of dozens of insects have been sequenced. As gene data rapidly accumulate, constructing the pathway of molecular interactions becomes increasingly important for entomological research. Here, we developed an improved tool, iPathCons, for knowledge-based construction of pathways from the transcriptomes or the official gene sets of genomes. Considering the high evolution diversity in insects, iPathCons uses a voting system for Kyoto Encyclopedia of Genes and Genomes Orthology assignment. Both stand-alone software and a web server of iPathCons are provided. Using iPathCons, we constructed the pathways of molecular interactions of 52 insects, including 37 genome-sequenced and 15 transcriptome-sequenced ones. These pathways are available in the iPathDB, which provides searches, web server, data downloads, etc. This database will be highly useful for the insect research community. Database URL: http://ento.njau.edu.cn/ipath/