A Unified-Field Monolithic Fictitious Domain-Finite Element Method for Fluid-Structure-Contact Interactions and Applications to Deterministic Lateral Displacement Problems

Based upon two overlapped, body-unfitted meshes, a type of unified-field monolithic fictitious domain-finite element method (UFMFD-FEM) is developed in this paper for moving interface problems of dynamic fluid-structure interactions (FSI) accompanying with high-contrast physical coefficients across the interface and contacting collisions between the structure and fluidic channel wall when the structure is immersed in the fluid. In particular, the proposed novel numerical method consists of a monolithic, stabilized mixed finite element method within the frame of fictitious domain/immersed boundary method (IBM) for generic fluid-structure-contact interaction (FSCI) problems in the Eulerian-updated Lagrangian description, while involving the no-slip type of interface conditions on the fluid-structure interface, and the repulsive contact force on the structural surface when the immersed structure contacts the fluidic channel wall. The developed UFMFD-FEM for FSI or FSCI problems can deal with the structural motion with large rotational and translational displacements and/or large deformation in an accurate and efficient fashion, which are first validated by two benchmark FSI problems and one FSCI model problem, then by experimental results of a realistic FSCI scenario -- the microfluidic deterministic lateral displacement (DLD) problem that is applied to isolate circulating tumor cells (CTCs) from blood cells in the blood fluid through a cascaded filter DLD microchip in practice, where a particulate fluid with the pillar obstacles effect in the fluidic channel, i.e., the effects of fluid-structure interaction and structure collision, play significant roles to sort particles (cells) of different sizes with tilted pillar arrays.Comment: 32 pages, 42 figures, 5 tables, 66 reference

Deep Learning-based Marine Target Detection Method with Multiple Feature Fusion

Considering the problem of radar target detection in the sea clutter environment, this paper proposes a deep learning-based marine target detector. The proposed detector increases the differences between the target and clutter by fusing multiple complementary features extracted from different data sources, thereby improving the detection performance for marine targets. Specifically, the detector uses two feature extraction branches to extract multiple levels of fast-time and range features from the range profiles and the range-Doppler (RD) spectrum, respectively. Subsequently, the local-global feature extraction structure is developed to extract the sequence relations from the slow time or Doppler dimension of the features. Furthermore, the feature fusion block is proposed based on adaptive convolution weight learning to efficiently fuse slow-fast time and RD features. Finally, the detection results are obtained through upsampling and nonlinear mapping to the fused multiple levels of features. Experiments on two public radar databases validated the detection performance of the proposed detector

Machine learning method for 12^{12}C event classification and reconstruction in the active target time-projection chamber

Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine learning methods to the analysis of data obtained from an active target time projection chamber. Specifically, we investigate the effectiveness of Visual Geometry Group (VGG) and the Residual neural Network (ResNet) models for event classification and reconstruction in decays from the excited $2^+_2$ state in $^{12}$C Hoyle rotation band. The results show that machine learning methods are effective in identifying $^{12}$C events from the background noise, with ResNet-34 achieving an impressive precision of 0.99 on simulation data, and the best performing event reconstruction model ResNet-18 providing an energy resolution of $\sigma_E<77$ keV and an angular reconstruction deviation of $\sigma_{\theta}<0.1$ rad. The promising results suggest that the ResNet model trained on Monte Carlo samples could be used for future classifying and predicting experimental data in active target time projection chambers related experiments.Comment: 9 pages, 10 figures, 9 table

Visfatin and 25-Hydroxyvitamin D ₃ Levels Affect Coronary Collateral Circulation Development in Patients with Chronic Coronary Total Occlusion

Background: Coronary collateral circulation (CCC) plays a vital role in the myocardial blood supply, especially for ischemic myocardium. Evidence suggests that the visfatin and 25-hydroxyvitamin D 3 [25(OH)D 3] levels are related to the degree and incidence of vascular stenosis associated with coronary artery disease; however, few studies have evaluated the effect of visfatin and 25(OH)D 3 on CCC development in patients with chronic total occlusion (CTO). This study aimed to evaluate the relationship between the serum visfatin and 25(OH)D 3 levels and CCC in patients with CTO. Methods: A total of 189 patients with CTO confirmed by coronary angiography were included. CCC was graded from 0 to 3 according to the Rentrop-Cohen classification. Patients with grade 0 or grade 1 collateral development were included in the poor CCC group ( n=82), whereas patients with grade 2 or grade 3 collateral development were included in the good CCC group ( n=107). The serum visfatin and 25(OH)D 3 levels were measured by ELISA. Results: The visfatin level was significantly higher in the poor CCC group than in the good CCC group, and the 25(OH)D 3 level was significantly lower in the poor CCC group than in the good CCC group (P=0.000). Correlation analysis showed that the Rentrop grade was negatively correlated with the visfatin level ( r=−0.692, P=0.000) but positively correlated with the 25(OH)D 3 level ( r=0.635, P=0.000). Logistic regression analysis showed that the visfatin and 25(OH)D 3 levels were independent risk factors for CCC (odds ratio 1.597, 95% confidence interval 1.300–1.961, P=0.000 and odds ratio 0.566, 95% confidence interval 0.444–0.722, P=0.000, respectively). The visfatin and 25(OH)D 3 levels can effectively predict the CCC status. Conclusion: Serum visfatin and 25(OH)D 3 levels are related to CCC development and are independent predictors of poor CCC. </p

A transcription factor of the NAC family regulates nitrate-induced legume nodule senescence

17 Pags.- 7 Figs. © 2023 The AuthorsLegumes establish symbioses with rhizobia by forming nitrogen-fixing nodules. Nitrate is amajor environmental factor that affects symbiotic functioning. However, the molecularmechanism of nitrate-induced nodule senescence is poorly understood. Comparative transcriptomic analysis reveals an NAC-type transcription factor inLotus japo-nicus, LjNAC094, that acts as a positive regulator in nitrate-induced nodule senescence.Stable overexpression and mutant lines ofNAC094were constructed and used for phenotypiccharacterization. DNA-affinity purification sequencing was performed to identify NAC094targeting genes and results were confirmed by electrophoretic mobility shift and transactiva-tion assays. Overexpression ofNAC094induces premature nodule senescence. Knocking outNAC094partially relieves nitrate-induced degradation of leghemoglobins and abolishes nodule expres-sion of senescence-associated genes (SAGs) that contain a conserved binding motif forNAC094. Nitrate-triggered metabolic changes in wild-type nodules are largely affected innac094mutant nodules. Induction ofNAC094and its targetingSAGswas almost blocked inthe nitrate-insensitivenlp1,nlp4, andnlp1 nlp4mutants. We conclude that NAC094 functions downstream of NLP1 and NLP4 by regulating nitrate-induced expression ofSAGs. Our study fills in a key gap between nitrate and the execution ofnodule senescence, and provides a potential strategy to improve nitrogen fixation and stresstolerance of legumes.This work was supported by the National Natural Science Foundation of China (32000192, 31870220), the Foundation of Hubei Hongshan Laboratory (2022hszd014), Fundamental Research Funds for the Central Universities (2662020SKPY007), and MCIN/AEI/10.13039/501100011033 (grant PID2020-113985GB-I00). We also thank the BaiChuan fellowship of College of Life Science and Technology, Huazhong Agricultural University, for funding support.Peer reviewe

Heme catabolism mediated by heme oxygenase in uninfected interstitial cells enables efficient symbiotic nitrogen fixation in Lotus japonicus nodules

18 Pags.- 8 Figs. © 2023 The Authors. New Phytologist.Legume nodules produce large quantities of heme required for the synthesis of leghemoglobin (Lb) and other hemoproteins. Despite the crucial function of Lb in nitrogen fixation and the toxicity of free heme, the mechanisms of heme homeostasis remain elusive. Biochemical, cellular, and genetic approaches were used to study the role of heme oxygenases (HOs) in heme degradation in the model legume Lotus japonicus. Heme and biliverdin were quantified and localized, HOs were characterized, and knockout LORE1 and CRISPR/Cas9 mutants for LjHO1 were generated and phenotyped. We show that LjHO1, but not the LjHO2 isoform, is responsible for heme catabolism in nodules and identify biliverdin as the in vivo product of the enzyme in senescing green nodules. Spatiotemporal expression analysis revealed that LjHO1 expression and biliverdin production are restricted to the plastids of uninfected interstitial cells. The nodules of ho1 mutants showed decreased nitrogen fixation, and the development of brown, rather than green, nodules during senescence. Increased superoxide production was observed in ho1 nodules, underscoring the importance of LjHO1 in antioxidant defense. We conclude that LjHO1 plays an essential role in degradation of Lb heme, uncovering a novel function of nodule plastids and uninfected interstitial cells in nitrogen fixation.This work was supported by the Ministry of Science and Technology of the People’s Republic of China (2021YFA0910800), National Natural Science Foundation of China (31870220), the Foundation of Hubei Hongshan Laboratory (2022hszd014), HZAU-AGIS Cooperation Fund (SZYJY2022005), and MCIN/AEI/10.13039/ 501100011033 of Spain (grant PID2020-113985GB-I00).Peer reviewe

Single cell-type transcriptome profiling reveals genes that promote nitrogen fixation in the infected and uninfected cells of legume nodules

2 Pags.- 1 Fig. © 2022 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use,distribution and reproduction in any medium, provided the original work is properly cited.Excessive application of nitrogen fertilizers has inevitably resultedin environmental problems. The symbiotic nitrogen fixation (SNF) that occurs in the root nodules of leguminous plants provides asustainable source of reduced nitrogen in agricultural ecosystems. More than 200 genes have been reported to regulate SNF, including rhizobial infection, nodule organogenesis and senescence (Royet al., 2020). Mature nodules consist mainly of twocell types: infected cells (IC) that contain nitrogen-fixing bac-teroids and uninfected cells (UC) that mediate active metabolismand nutrient transport. Although it is well known that SNFrequires functional specialization, the specific genes responsiblefor transcriptional regulation and carbon/nitrogen metabolismand transport in IC and UC remain largely unexplored.Single-cell transcriptomics has emerged as a powerful tech-nique for investigating spatiotemporal patterns of gene expression.This work was supported by the National Natural Science Foundation of China (31870220, 32000192), the China Post-doctoral Science Foundation (2020M680103), Fundamental Research Funds for the Central Universities 2662020SKPY007 and MCIN/AEI/10.13039/501100011033 (grant PID2020-113985GB-I00)Peer reviewe

Boosting Palladium Catalyzed Aryl–Nitro Bond Activation Reaction by Understanding the Electronic, Electrostatic and Polarization Effect: A Computational Study from Basic Understanding to Ligand Design

Although cross coupling reaction with nitroarene as the electrophilic partner has gained high interest recently, the palladium catalyzed aryl–nitro bond activation reaction still requires rather high temperature and hash condition. In this work, based on Nakao’s nitrogen heterocyclic carbene (NHC) ligand, we systematically explored the substituent effect on the oxidative addition step, the known rate determining step of the whole reaction, by density functional theory (DFT) calculation. The key aryl ring on the ligand skeleton, namely Ring A, acts as a π-donor and stabilizes the palladium center of the transition state, as shown by Extended Transition State Natural Orbital of Chemical Valance (ETS-NOCV) analysis, and thus an electron-rich Ring A is expected to lower the barrier. On the other hand, however, the polarization and electrostatic effects were shown to be as or even more important, although they were often ignored before. These effects originate from through-space interaction with the nitro group in the resting state, and the overall effect is that any polarizable or partly negative group nearby the ortho- or meta¬- site of Ring A is harmful for the reaction. Based on these discoveries, we proposed a list of guidelines for successful ligand development, and designed several new ligands. These ligands exhibit significantly lower barrier than the reported Nakao’s ligand by as large as ~5 kcal/mol in both gas phase and solvation, and might be good candidates for further experimental study