Perturbation estimation based nonlinear adaptive control of VSC flexible excitation system

A new type of flexible excitation system (FES) is proposed by using fully-controlled power electronic devices such as IGBTs to replace the half controlled devices in the conventional static excitation system, which has the merit of independent control of rotor angle and terminal voltage of the synchronous generator. This paper proposes nonlinear adaptive control (NAC) strategies for synchronous generator with FES in a single machine infinite bus system. External disturbances and the uncertainties of all parameters as well as modelling are defined as lumped perturbation terms and estimated by perturbation observers or state and perturbation observer. The estimated perturbation terms are used to compensate the real perturbations and achieve a model-independent and robust NAC. Merits of the FES against the conventional static excitation system and effectiveness of the proposed NAC scheme against the accurate model based multi-variable feedback linearisation control are verified via small-signal stability analysis and simulation studies. The simulation results have shown that the proposed NAC can achieve superior control performance with less states feedback during a three-phase short circuit and better robustness against parameter uncertainties, compared with linear control and multi-variable feedback linearisation control

Token-level Direct Preference Optimization

Fine-tuning pre-trained Large Language Models (LLMs) is essential to align them with human values and intentions. This process often utilizes methods like pairwise comparisons and KL divergence against a reference LLM, focusing on the evaluation of full answers generated by the models. However, the generation of these responses occurs in a token level, following a sequential, auto-regressive fashion. In this paper, we introduce Token-level Direct Preference Optimization (TDPO), a novel approach to align LLMs with human preferences by optimizing policy at the token level. Unlike previous methods, which face challenges in divergence efficiency, TDPO incorporates forward KL divergence constraints for each token, improving alignment and diversity. Utilizing the Bradley-Terry model for a token-based reward system, TDPO enhances the regulation of KL divergence, while preserving simplicity without the need for explicit reward modeling. Experimental results across various text tasks demonstrate TDPO\u27s superior performance in balancing alignment with generation diversity. Notably, fine-tuning with TDPO strikes a better balance than DPO in the controlled sentiment generation and single-turn dialogue datasets, and significantly improves the quality of generated responses compared to both DPO and PPO-based RLHF methods. Our code is open-sourced at https://github.com/Vance0124/Token-level-Direct-Preference-Optimization

Stage deformation characteristics of natural and saturated crushed gangue with large particle size

This study investigates the deformation characteristics and energy consumption patterns of natural and saturated crushed gangue with large particle size during loading-constant load stage through compression test. The results show that: 1) The deformation of natural and saturated crushed gangue in the loading stage accounts for more than 90% of the total deformation. The load gradient significantly affects the displacement deformation in the early stage, and the water also exerts major influence on the displacement deformation in the creep stage. 2) Under natural and saturated conditions, about 1/3 of the work is consumed by friction, while 2/3 by crushing; 3) Compared with the natural state, energy consumption and its variation rate are reduced in the full stage of saturated crushed gangue. The displacement curve shows an explicit three-stage pattern of sharp deformation, linear deformation and creep deformation. According to the first-order and second-order derivatives of the displacement curve, we proposed the judgment basis of the threestages of sharp-linear-creep deformation. When the deformation of crushed gangue exceeds 15%, we observed improved bearing capacity. By observing the gangue compression process, we found that the crushed gangue shows a more uniform internal force chain distribution in the saturated state, with a higher number of cracks, crack growth rate and secondary crushing rate than those in the natural state. Under natural and saturated conditions, when the top void ratio of crushed gangue exceeds 0.65, we observed the maximum secondary crushing rate, with the bottom void ratio of less than 0.45, as well as the minimum secondary crushing rate, with the middle void ratio remaining stable at about 0.5. The secondary crushing loss and the top sliding retention can offset each other. The present study could provide reference for the design, stability monitoring and prediction of coal gangue filling

Nano-Subsidence-Assisted Precise Integration of Patterned Two-Dimensional Materials for High-Performance Photodetector Arrays

The spatially precise integration of arrays of micropatterned two-dimensional (2D) crystals onto three-dimensionally structured Si/SiO2 substrates represents an attractive, low-cost system-on-chip strategy toward the realization of extended functions in silicon microelectronics. However, the reliable integration of such atomically thin arrays on planar patterned surfaces has proven challenging due to their poor adhesion to underlying substrates, as ruled by weak van der Waals interactions. Here, we report on an integration method utilizing the flexibility of the atomically thin crystals and their physical subsidence in liquids, which enables the reliable fabrication of the micropatterned 2D materials/Si arrays. Our photodiode devices display peak sensitivity as high as 0.35 A/W and external quantum efficiency (EQE) of ∼90%. The nano-subsidence technique represents a viable path to on-chip integration of 2D crystals onto silicon for advanced microelectronics

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Validation of a Chinese version of the Tolerance for Mental Pain Scale-10 with Chinese college students

We built and validated a Chinese version of the Tolerance for Mental Pain Scale-10 (TMPS-10). Participants were 840 college students in Jilin, China. The TMPS-10 consists of two dimensions: managing the pain and enduring the pain. In our study Cronbach's alphas were .80 and .83, respectively, and test–retest reliability coefficients were .78 and .72, respectively, for these two dimensions. Exploratory factor analysis results demonstrate that the two dimensions accounted for 61.58% of the total variance. Confirmatory factor analysis results show that the two-factor model fit the sample data well. As the Chinese version of the TMPS-10 meets the requirements for a psychometric tool, it can be used to evaluate Chinese college students' tolerance of psychological pain.</jats:p

Cross-Subject Lifelong Learning for Continuous Estimation From Surface Electromyographic Signal

The employment of surface electromyographic (sEMG) signals in the estimation of hand kinematics represents a promising non-invasive methodology for the advancement of human-machine interfaces. However, the limitations of existing subject-specific methods are obvious as they confine the application to individual models that are custom-tailored for specific subjects, thereby reducing the potential for broader applicability. In addition, current cross-subject methods are challenged in their ability to simultaneously cater to the needs of both new and existing users effectively. To overcome these challenges, we propose the Cross-Subject Lifelong Network (CSLN). CSLN incorporates a novel lifelong learning approach, maintaining the patterns of sEMG signals across a varied user population and across different temporal scales. Our method enhances the generalization of acquired patterns, making it applicable to various individuals and temporal contexts. Our experimental investigations, encompassing both joint and sequential training approaches, demonstrate that the CSLN model not only attains enhanced performance in cross-subject scenarios but also effectively addresses the issue of catastrophic forgetting, thereby augmenting training efficacy