Optimizing the face paradigm of BCI system by modified mismatch negative paradigm

Many recent studies have focused on improving the performance of event-related potential (ERP) based brain computer interfaces (BCIs). The use of a face pattern has been shown to obtain high classification accuracies and information transfer rates (ITRs) by evoking discriminative ERPs (N200 and N400) in addition to P300 potentials. Recently, it has been proved that the performance of traditional P300-based BCIs could be improved through a modification of the mismatch pattern. In this paper, a mismatch inverted face pattern (MIF-pattern) was presented to improve the performance of the inverted face pattern (IF-pattern), one of the state of the art patterns used in visual-based BCI systems. Ten subjects attended in this experiment. The result showed that the mismatch inverted face pattern could evoke significantly larger vertex positive potentials (p < 0.05) and N400s (p < 0.05) compared to the inverted face pattern. The classification accuracy (mean accuracy is 99.58%) and ITRs (mean bit rate is 27.88 bit/min) of the mismatch inverted face pattern was significantly higher than that of the inverted face pattern (p < 0.05)

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning

Trajectory modeling refers to characterizing human movement behavior, serving as a pivotal step in understanding mobility patterns. Nevertheless, existing studies typically ignore the confounding effects of geospatial context, leading to the acquisition of spurious correlations and limited generalization capabilities. To bridge this gap, we initially formulate a Structural Causal Model (SCM) to decipher the trajectory representation learning process from a causal perspective. Building upon the SCM, we further present a Trajectory modeling framework (TrajCL) based on Causal Learning, which leverages the backdoor adjustment theory as an intervention tool to eliminate the spurious correlations between geospatial context and trajectories. Extensive experiments on two real-world datasets verify that TrajCL markedly enhances performance in trajectory classification tasks while showcasing superior generalization and interpretability.Comment: The paper has been accepted by IJCAI 202

Blockchain technologies empowering peer‐to‐peer trading in multi‐energy systems:From advanced technologies towards applications

In efforts to decarbonise electricity, transport, and heating sectors, policy makers facilitate the integration of renewable energy sources and demand side management in multi-energy systems. With the support of the smart grid, an increasing number of consumers start to produce, store, and consume energy using zero-carbon electricity and heating sources, for example, solar panels, electric vehicles, and air source heat pumps, giving them the new role of multi-energy prosumers. A flexible local energy market structure and intelligent operations of smart grid are crucial factors for accommodating the role of multi-energy prosumers. The blockchain technologies, for example, smart contracts and hypothetical technology, pave the path for the peer-to-peer (P2P) energy markets, which are open and accessible to prosumers with enhanced automation, security, and privacy. The state-of-the-art research and scientific innovations bring these advanced blockchain technologies towards applications into multi-energy systems. This special issue aims to solicit the innovative research on the blockchain empowering peer-to-peer trading in multi-energy systems. The scope of the research includes a single (multiple) energy vector(s) (e.g., electricity, gas, or heat), technologies (e.g., blockchain, smart contracts, or machine learning), theories (e.g., P2P trading mechanisms, pricing schemes, communication protocols, or consensus mechanisms) and applications (e.g., blockchain platforms or prosumer-centric energy scheduling)

Complete sequencing of the mitochondrial genome of tea plant Camellia sinensis cv. ‘Baihaozao’: multichromosomal structure, phylogenetic relationships, and adaptive evolutionary analysis

IntroductionThis study reports for the first time the complete sequence characteristics of the mitochondrial genome of the tea plant cultivar Camellia sinensis cv. ‘Baihaozao’. It systematically unveils its multi-chromosomal structure, RNA editing patterns, and adaptive evolutionary mechanisms, providing critical theoretical insights into the structural complexity and evolutionary mechanisms of the tea plant mitochondrial genome.MethodsThe mitochondrial genome was fully analyzed using genome sequencing and annotation techniques. RNA editing sites were predicted to evaluate editing patterns. Codon usage bias analysis was conducted to identify high-frequency codons. Repeat sequence analysis was used to characterize dispersed and tandem repeats. Adaptive evolutionary analysis, based on Ka/Ks ratios, was performed to investigate gene selection pressures.ResultsThe mitochondrial genome consists of 11 linear chromosomes, with a total length of 909,843 bp and a GC content of 45.62%. A total of 73 functional genes were annotated, among which 14 variable genes (e.g., ribosomal protein coding genes) retain intact functions without pseudogenization, which is rare among Theaceae plants. RNA editing site prediction revealed significant spatial heterogeneity, with the cox1 gene being a hotspot containing 19 editing sites. Approximately 58.49% of editing events were concentrated on the second base of codons, and 48.61% of the sites resulted in amino acid changes from hydrophilic to hydrophobic. Codon usage bias analysis showed significant enrichment of high-frequency codons, including UUU (phenylalanine), AUU (isoleucine), and UUC (phenylalanine). The genome’s repeat sequences were predominantly dispersed repeats (70.6%), with forward and palindromic repeats of 30–40 bp being dominant. Tandem repeats exhibited significant distribution heterogeneity among chromosomes. Adaptive evolution analysis showed that most PCGs (protein-coding genes) had Ka/Ks ratios below 1 (ranging from 0.07 to 0.78), with the atp9 gene showing the lowest ratio (0.07), while the mttB gene exhibited a significantly higher Ka/Ks ratio of 3.48. Additionally, 1.62% of the mitochondrial genome sequence was homologous to the chloroplast genome, carrying 26 complete functional genes, including 15 tRNA and 2 rRNA genes.DiscussionCodon usage bias may be related to mutation pressure due to the high AT content of the genome or reflect adaptive selection pressures for translational efficiency. The Ka/Ks results align with the widespread purifying selection observed in mitochondrial genomes, while the high Ka/Ks ratio of the mttB gene suggests it might be under positive selection to adapt to environmental pressures. The evolutionary evidence of inter-organelle gene transfer highlights the homologous sequences between mitochondria and chloroplasts. Overall, these findings systematically elucidate the adaptive evolutionary mechanisms and functional regulation of the tea plant mitochondrial genome