BG²VN toolbox generates Gaussian-based benchmark graphs with ground-truth vital nodes, offering the first standard test-bed for comparing vital-node mining algorithms

What would happen if farmers around the globe were to switch over to sustainable pest management? An international study headed by the University of Bonn and ETH Zurich focused on precisely this question. The study is based on assessments provided by more than 500 leading experts from around the world who work in various disciplines from ecology through to economics. Most of those surveyed believe that the consequences of such a transformation would be positive in the long term – even from an economic perspective. However, the main effects of this transformation will vary around the world depending on the region. The results were recently published in the journal Nature Communications. 

Recently, a collaborative team from multiple institutions, including CIOMP, published a review article in Light: Science & Applications, systematically expounding on the cutting-edge developments in Surface-Enhanced Raman Scattering (SERS)-integrated optical waveguide technology. By reviewing two major technical pathways—remote sensing probes and microfluidic sensing platforms—the study thoroughly analyzes key innovations such as optical fiber structure design, SERS substrate modification, and the integration of emerging technologies. It clarifies the core advantages of this technology in improving detection sensitivity, simplifying operational procedures, and enabling miniaturization. The research not only summarizes the technological breakthroughs and application achievements in this field but also identifies future challenges such as large-scale fabrication and specificity optimization. It provides important academic references for the development of ultra-sensitive trace liquid detection technologies and is expected to drive innovations in detection technologies in fields such as biomedicine and environmental monitoring.

A research paper by scientists from Tianjin University proposed a novel solution for high-speed steady-state visually evoked potential (SSVEP)-based brain–computer interfaces (BCIs), featuring a neural principle-based data augmentation technique (BGMix) and a Transformer-based model (AETF) to enhance EEG decoding efficiency.

The new research paper, published on October 7 in the journal Cyborg and Bionic Systems, presented the development, validation, and optimization of the BGMix strategy and AETF model, demonstrating their effectiveness in addressing data sparsity and improving the performance of SSVEP-based BCI systems.

In this paper, the existing AD methods for the PMSM drive system with LC sine wave filter are reviewed, including the modified AD methods based on inherent damping, conventional AD methods based on state variable feedback, modified AD methods with LPF and HPF based on state variable feedback and AD methods based on digital filter. A new expansion of AD method based on HPF-CCF is studied to ensure the effectiveness when the resonant frequency is around sixth of the sampling frequency. The stability, dynamic performance, robustness, and algorithm complexity of the AD methods are compared in detail and the suggestion of selecting the AD method in different industrial scenarios is summed as below.

1) When evaluating the stability of control system in terms of PM and GM, CCF, LPF-CCF, and the proposed HPF-CCF are comparatively more recommended.

2) In terms of the open-loop cutoff frequency, the proposed HPF-CCF is more recommended for realizing a better dynamic performance.

3) In terms of the Bode diagrams analysis and experimental results, LPF-CCF, HPF-MCF, and the proposed HPF-CCF are more recommended for ensuring control system robustness.

4) When considering the algorithmic complexity of the AD methods, only one parameter needs to be designed for CCF and ICF-SOGI.