11 research outputs found
Further analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds
This work presents a theoretical analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds based on the simple one-dimensional dispersion model. The analysis is validated by comparison with the experimental results reported in the literature. It concludes that gas flows can be considered near-plug flow only when: 1) the gas RTD curve is symmetrically shaped; 2) the product of RTD peak height E(t)(h) and variance sigma(t) (i.e., E(t)(h)sigma(t)) approximates 0.4; and 3) E(t)h is greater than 1.0 s(-1) (dimensionless E-theta,E-max > 2.82) or sigma(2)(t) 0.02). This work further improves the criterion for the near-plug flow of gas in micro fluidized beds originally proposed by Geng et al. (CEJ, 351 (2018) 110-118).(C) 2022 Elsevier B.V. All rights reserved
Further analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds
This work presents a theoretical analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds based on the simple one-dimensional dispersion model. The analysis is validated by comparison with the experimental results reported in the literature. It concludes that gas flows can be considered near-plug flow only when: 1) the gas RTD curve is symmetrically shaped; 2) the product of RTD peak height E(t)(h) and variance sigma(t) (i.e., E(t)(h)sigma(t)) approximates 0.4; and 3) E(t)h is greater than 1.0 s(-1) (dimensionless E-theta,E-max > 2.82) or sigma(2)(t) 0.02). This work further improves the criterion for the near-plug flow of gas in micro fluidized beds originally proposed by Geng et al. (CEJ, 351 (2018) 110-118).(C) 2022 Elsevier B.V. All rights reserved
A Deep Learning Approach for Wireless Network Performance Classification Based on UAV Mobility Features
The unmanned aerial vehicle (UAV) has drawn attention from the military and researchers worldwide, which has advantages such as robust survivability and execution ability. Mobility models are usually used to describe the movement of nodes in drone networks. Different mobility models have been proposed for different application scenarios; currently, there is no unified mobility model that can be adapted to all scenarios. The mobility of nodes is an essential characteristic of mobile ad hoc networks (MANETs), and the motion state of nodes significantly impacts the network’s performance. Currently, most related studies focus on the establishment of mathematical models that describe the motion and connectivity characteristics of the mobility models with limited universality. In this study, we use a backpropagation neural network (BPNN) to explore the relationship between the motion characteristics of mobile nodes and the performance of routing protocols. The neural network is trained by extracting five indicators that describe the relationship between nodes and the global features of nodes. Our model shows good performance and accuracy of classification on new datasets with different motion features, verifying the correctness of the proposed idea, which can help the selection of mobility models and routing protocols in different application scenarios having the ability to avoid repeated experiments to obtain relevant network performance. This will help in the selection of mobility models for drone networks and the setting and optimization of routing protocols in future practical application scenarios
The B‐box protein BBX19 suppresses seed germination via induction of ABI5
Seed germination is a fundamental process in the plant life cycle and is regulated by functionally opposing internal and external inputs. Here we explored the role of a negative regulator of photomorphogenesis, a B-box-containing protein (BBX19), as a molecular link between the inhibitory action of the phytohormone abscisic acid (ABA) and the promoting role of light in germination. We show that seeds of BBX19-overexpressing lines, in contrast to those of BBX19 RNA interference lines, display ABA hypersensitivity, albeit independently of elongated hypocotyl 5 (HY5). Moreover, we establish that BBX19 functions neither via perturbation of GA signaling, the ABA antagonistic phytohormone, nor through interference with the DELLA protein germination repressors. Rather, BBX19 functions as an inducer of ABA INSENSITIVE5 (ABI5) by binding to the light-responsive GT1 motifs in the gene promoter. In summary, we identify BBX19 as a regulatory checkpoint, directing diverse developmental processes and tailoring adaptive responses to distinct endogenous and exogenous signals
MOESM6 of An efficient transient expression system for gene function analysis in rose
Additional file 6: Table S1. List of primers used
MOESM7 of An efficient transient expression system for gene function analysis in rose
Additional file 7: Fig. S6. The outline of multiple BP and LR reactions to generate expression vectors for protein-protein interaction assay. PCR primers were designed to include 22- and 25-bp attB and attBr sites followed by at least 18 to 25Â bp of gene-specific sequences, then the BP reactions were performed with PCR products and corresponding donor vector pDONR221 P1-P4, pDONR221 P4r-P3r, and pDONR221 P3-P2 to generate pENTR vectors L1-35S-L4, R4-RoKSN-R3, R4-RoFT-R3, L3-LUC-N-L2, and L3-LUC-C-L2. Multiple LR reactions were subsequently executed to construct the expression plasmids 35S:RoKSN:LUC-N, 35S:RoFT:LUC-C and 35S:RoFD:LUC-C by using pB7WG as destination vector
Variation between Antiferromagnetism and Ferrimagnetism in NiPS3 by Electron Doping
How to electrically control magnetic properties of a magnetic material is promising towards spintronic applications, where the investigation of carrier doping effects on antiferromagnetic (AFM) materials remains challenging due to their zero net magnetization. In this work, we found electron doping dependent variation of magnetic orders of a two-dimensional (2D) AFM insulator NiPS3, where doping concentration is tuned by intercalating various organic cations into the van der Waals gaps of NiPS3 without introduction of defects and impurity phases. The doped NiPS3 shows an AFM-ferrimagnetic (FIM) transition at doping level of 0.2-0.5 electrons/cell and a FIM-AFM transition at doping level of ≥0.6 electrons/cell. We propose that the found phenomenon is due to competition between Stoner exchange dominated inter-chain ferromagnetic order and super-exchange dominated inter-chain AFM order at different doping level. Our studies provide a viable way to exploit correlation between electronic structures and magnetic properties of 2D magnetic materials for realization of magnetoelectric effect