Measurement of Flow Characteristics in a Bubbling Fluidized Bed Using Electrostatic Sensor Arrays

Fluidized beds are widely applied in a range of industrial processes. In order to maintain the efficient operation of a fluidized bed, the flow parameters in the bed should be monitored continuously. In this paper, electrostatic sensor arrays are used to measure the flow characteristics in a bubbling fluidized bed. In order to investigate the electrostatic charge distribution and the flow dynamics of solid particles in the dense region, time and frequency domain analysis of the electrostatic signals is conducted. In addition, the correlation velocities and weighted average velocity of Geldart A particles in the dense and transit regions are calculated, and the flow dynamics of Geldart A and D particles in the dense and transit regions are compared. Finally, the influence of liquid antistatic agents on the performance of the electrostatic sensor array is investigated. According to the experimental results, it is proved that the flow characteristics in the dense and transit regions of a bubbling fluidized bed can be measured using electrostatic sensor arrays

Particle velocity measurement of binary mixtures in the riser of a circulating fluidized bed by the combined use of electrostatic sensing and high-speed imaging

Zhang WB acknowledges the financial supports from the National Natural Science Foundation of China (No. 61403138) and Beijing Natural Science Foundation (No. 3202028). Zhan W and Wang CH acknowledge the research programme funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. Grant Number R-706-001-102–281, National University of Singapore.Peer reviewedPublisher PD

Dietary calcium requirements of bighead carp (Aristichthys nobilis)

To investigate dietary calcium requirement of bighead carp (Aristichthys nobilis), six purified diets were formulated to contain different concentrations of calcium (0.09% (control), 0.43%, 0.76%, 1.12%, 1.44%, and 1.79% of dry diets). Each diet was hand-fed to triplicate 30 fish with an average initial body weight (3.31 ± 0.09 g) for 60 days. The results showed that weight gain (WG) and specific growth rate (SGR) significantly increased when dietary calcium level was from 0.09% to 0.76% (P < 0.05). The phosphorus and calcium contents of whole fish body were highest in the 0.76% and 1.12% group, respectively (P < 0.05). The serum phosphorus content in the 1.79% group was significantly lower than those in other groups (P < 0.05). As dietary calcium content was from 0.09% to 0.76%, the activities of lipase and proteinase in the intestine had a significant increase (P < 0.05), while the glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) activities were significantly decreased (P < 0.05). Based on quadratic curve model analysis with WG and WGR as the appraising criteria, the appropriate dietary requirement of calcium for the bighead carp larvae (3.31 ± 0.09 g) was 1.01% - 1.02%

Lingo3DMol: Generation of a Pocket-based 3D Molecule using a Language Model

Structure-based drug design powered by deep generative models have attracted increasing research interest in recent years. Language models have demonstrated a robust capacity for generating valid molecules in 2D structures, while methods based on geometric deep learning can directly produce molecules with accurate 3D coordinates. Inspired by both methods, this article proposes a pocket-based 3D molecule generation method that leverages the language model with the ability to generate 3D coordinates. High quality protein-ligand complex data are insufficient; hence, a perturbation and restoration pre-training task is designed that can utilize vast amounts of small-molecule data. A new molecular representation, a fragment-based SMILES with local and global coordinates, is also presented, enabling the language model to learn molecular topological structures and spatial position information effectively. Ultimately, CrossDocked and DUD-E dataset is employed for evaluation and additional metrics are introduced. This method achieves state-of-the-art performance in nearly all metrics, notably in terms of binding patterns, drug-like properties, rational conformations, and inference speed. Our model is available as an online service to academic users via sw3dmg.stonewise.c