Miracle-dz/UniFAR-FTUs huggingface dataset:
A Numerical Study on the Erythrocyte Flow Path in I-Shaped Pillar DLD Arrays

Erythrocyte enrichment is needed for blood disease diagnosis and research. DLD arrays with an I-shaped pillar (I-pillar) sort erythrocytes in a unique, accurate, and low-reagent method. However, the existing I-shaped pillar DLD arrays for erythrocyte sorting have the drawbacks of higher flow resistance and more challenging fabrication. A two-dimensional erythrocyte simulation model and the arbitrary Lagrangian–Euler equations at the cell–fluid boundary were built based on the fluid–solid coupling method to investigate the influencing factors of the erythrocyte flow path in an I-pillar DLD array and find its optimization method. Three different sizes of I-pillars were built and multiple sets of corresponding arrays were constructed, followed by finite element simulations to separately investigate the effects of these arrays on the induction of erythrocyte motion paths. This work demonstrates the motion paths of erythrocyte models in a series of I-pillar arrays with different design parameters, aiming to summarize the variation modes of erythrocyte motion paths, which in turn provides some reference for designing and optimizing the pillar size and array arrangement methods for I-pillar array DLD chips.
Two-Plasmon-Decay Instability and Energetic Electron Generation in Direct-Drive Inertial Confinement Fusion

The two-plasmon-decay (TPD) instability is a significant concern in direct-drive inertial confinement fusion (ICF) experiments for its low threshold and highenergy electron generation. We study the TPD instability for parameters relevant to ICF using an existing particle-in-cell (PIC) code OSIRIS and a fluid code LTS developed in this thesis work. Both the linear and nonlinear regimes of TPD are explored. In the linear regime, a convective gain formula retaining the dependence on electron temperature and perpendicular mode number is derived and is shown in good agreement with the fluid simulation results. The growth rates and thresholds predicted by the linear theories are verified in both PIC and fluid simulations. Pump depletion due to convective modes’ domination are observed in the well-above-threshold PIC simulations. The PIC simulations show that both the absolute and convective modes saturate due to ion density fluctuations, which can suppress TPD by raising the instability threshold through mode coupling. A series of PIC simulations have been done to study the long-term (∼ 10ps) nonlinear behaviors of the TPD instability. The simulations have reached a quasi-steady state where the laser flux absorbed in the simulation box is balanced by the particle energy flux leaving the box. When the TPD threshold is exceeded, the simulation results show that significant laser absorption and energetic electron (> 50keV ) generation occur in the nonlinear stage. The hot electrons are stage-accelerated from the low-density region to the high-density region. New modes with small phase velocities develop in the low-density region after saturation. These modes
Development of a Non-Peptide Angiotensin II Type 1 Receptor Ligand by Structural Modification of Olmesartan as a Biased Agonist

As a biased agonist, peptide angiotensin II (Ang II) type 1 (AT1) receptor ligand antagonizes Ang II-stimulated G protein signaling but stimulates several kinase pathways. Here, we developed a non-peptide AT1 receptor compound as a biased ligand. We synthesized three non-peptide AT1 receptor ligands (R239470, R781253, and R794847) as candidates of biased ligands. Extracellular signal-regulated kinase (ERK) 1/2 activation and inositol phosphate (IP) production were measured using a cell system that overexpressed AT1 receptors (wild-type, L112A, Q257A, Y292A, and N295A receptors). We also examined the modes of receptor–ligand binding using a competition binding study. The Kd values of R239470, R781253, and R794847 for the AT1 wild-type receptor were 0.8, 21, and 48 nM, respectively, as assessed in a competition binding study. Those of R239470, R781253, and R794847 for the L112A receptor were 37, 23, and 31 nM, respectively. R781253 and R794847 decreased and increased IP production, respectively, whereas R239470 did not change IP production. R781253 and R794847, but not R239470, activated ERK1/2. In conclusion, R239470, R781253, and R794847 act as a neutral antagonist, an inverse agonist, and an agonist with regard to IP production, respectively. On the other hand, R781253 and R794847, but not R239470, are agonists toward ERK1/2 activation. Thus, we developed a non-peptide AT1 receptor compound as a biased ligand.
Iterative Shrinkage Thresholding Radar Forward-looking Imaging Method

Aimed at the airborne multi-channel scanning radar forward looking imaging problem,the mono-channel forward looking imaging method using iterative shrinkage thresholding algorithm is researched.An extended multi-channel iterative shrinkage thresholding algorithm is proposed for multi-channel forward-looking imaging problem.Its convergence is proven theoretically and a speed up method is also given.First,the optimal solution of multi-channel radar in the sense of minimum mean square error is obtained by the weighted superposition of each channel,and then the sparse solution access to the optimal solution in the corresponding sparse constraints is obtained using the target sparse representation.Theoretical analysis and simulation results show that the new method has obvious advantages in algorithm stability,scenes recovery ability and noise immunity compared with the pre-existing scanning radar forward-looking imaging methods.
Effectiveness of TaDreb-B1 and 1-FEH w3 KASP Markers in Spring and Winter Wheat Populations for Marker-Assisted Selection to Improve Drought Tolerance

Due to the advances in DNA markers, kompetitive allele-specific PCR (KASP) markers could accelerate breeding programs and genetically improve drought tolerance. Two previously reported KASP markers, TaDreb-B1 and 1-FEH w3, were investigated in this study for the marker-assisted selection (MAS) of drought tolerance. Two highly diverse spring and winter wheat populations were genotyped using these two KASP markers. The same populations were evaluated for drought tolerance at seedling (drought stress) and reproductive (normal and drought stress) growth stages. The single-marker analysis revealed a high significant association between the target allele of 1-FEH w3 and drought susceptibility in the spring population, while the marker–trait association was not significant in the winter population. The TaDreb-B1 marker did not have any highly significant association with seedling traits, except the sum of leaf wilting in the spring population. For field experiments, SMA revealed very few negative and significant associations between the target allele of the two markers and yield traits under both conditions. The results of this study revealed that the use of TaDreb-B1 provided better consistency in improving drought tolerance than 1-FEH w3.
TERL: Two-Stage Ensemble Reinforcement Learning Paradigm for Large-Scale Decentralized Decision Making in Transportation Simulation

Transportation simulation is non-trivial due to the co-existence of thousands of heterogeneous decision makers (or vehicles). Such large-scale decision making is intrinsically a complex decentralized problem, the resolution of which is at the forefront of transportation simulation. Despite many physical or mathematical models proposed to date, underlying them is usually a set of universal rules plus some random perturbations to characterize vehicular movements. Inspired by the decision-making mechanism of rational human beings (i.e., learning iteratively from experience), this study proposes a novel two-stage ensemble reinforcement learning (TERL) paradigm for large-scale decentralized decision making in transportation simulation, in order to enhance the computational efficiency and thus scalability of RL to practical applications at scale. After establishing a problem-specific Markov decision process, the first stage utilizes clustering to group heterogeneous vehicles into quasi-homogeneous clusters. A representative RL model (or agent) is employed for each cluster where the included vehicles share and jointly optimize the policy parameters. The second stage develops an ensemble control strategy based on representative RL models for vehicles isolated as noise during clustering. While vehicles are simultaneously simulated, RL models are separately trained with cluster-specific experience replay. Application of TERL to the classical multi-user dynamic route choice problem in a real-world network of the Gusu District in Suzhou, China demonstrates the effectiveness of the proposed approach in deriving desirable simulation results, compared with the classical shortest path model and the dynamic user equilibrium model.
Mixed Quantum-Classical Description of Excitation Energy Transfer in a Model Fenna-Matthews-Olsen Complex

The Fenna−Matthews−Olsen (FMO) complex has recently become a paradigmatic model system in terms of understanding the long-lived electronic quantum coherence that has been experimentally observed in photosynthetic systems. In this article we investigate the quantum dynamics of an FMO model within a mixed quantum-classical dynamics approach known as the Poisson bracket mapping equation (PBME), and explore the consequences of adopting this approximate description by simulating population transfer and electronic coherence. The results obtained via the Poisson bracket mapping formalism are explicitly compared with a selection of recent results on the FMO complex. The PBME is shown to be in excellent agreement with benchmark computational results at physiological temperature, and thus provides a computationally efficient and physically consistent algorithm that may be easily integrated in all-atom molecular dynamics simulations.
Functional Objects in Urban Walking Environments and Pedestrian Trajectory Modelling

Functional objects are large and small physical entities installed in urban environments to offer specific functionalities to visitors, such as shops, escalators, and information kiosks. Instances of the novel notion are focal points of human activities and are significant in pedestrian movement. Pedestrian trajectory modelling in an urban scene is a challenging problem because of the complex patterns resulting from social interactions of the crowds and the diverse relation between pedestrians and functional objects. Many data-driven methods have been proposed to explain the complex movements in urban scenes. However, the methods considering functional objects in their formulation are rare. This study aims to reduce the knowledge gap by demonstrating the importance of pedestrian–object relations in the modelling task. The proposed modelling method, called pedestrian–object relation guided trajectory prediction (PORTP), uses a dual-layer architecture that includes a predictor of pedestrian–object relation and a series of relation-specific specialized pedestrian trajectory prediction models. The experiment findings indicate that the inclusion of pedestrian–object relation results in more accurate predictions. This study provides an empirical foundation for the novel notion and a strong baseline for future work on this topic.
Hard-Core Bosons on a Two-Dimensional Square Optical Superlattice

In this work,we theoretically study hard-core bosons on a two-dimensional square optical superlattice at T = 0.First of all,we present the mean field phase diagram of this model in terms of the chemical potential μ and the alternating potential strength △. Besides a superfluid(SF) phase at △ = 0 and a charge density wave(CDW)phase in the large △ at half filling,we demonstrate that a supersolid(SS) phase emerges in the moderate △. Then,we focus on the μ = 0,e.g.,half filling case,using large-S semi-classical spin-wave approximation to study the SS to CDW quantum phase transition.In particular,we calculate the ground-state energy and the superfluid density at the level of1/S correction.We then compare the spin-wave results with the large scale quantum Monte Carlo(QMC) simulations using the cluster stochastic series expansion(CSSE) algorithm,and find that while the spin wave method is intuitive with clear physical pictures,the quantum critical point is quite different from that of numerical results which is believed to be accurate.We suggest that as simple as it is,this model still exhibits strong quantum fluctuations near the quantum critical point beyond the power of semiclassical spin-wave approach.
Tensor Spectral k-Support Norm Minimization for Detecting Infrared Dim and Small Target Against Urban Backgrounds

In the low-altitude urban background with heavy interference, especially in the face of corner interference with higher intensity than the target, infrared (IR) dim and small target is extremely lack of prior information (i.e., size, shape, and contrast information). In such case, the existing detection methods usually suffer from high false alarm or even failure. To deal with this situation, we develop a novel spatial–temporal tensor model with tensor spectral $k$ -support norm minimization (STTM-TSNM) for detecting IR dim and small target. First, the spatial–temporal information of the original image sequence can be preserved completely by constructing the holistic STTM. Then, according to the spatial–temporal related prior knowledge of the target and background, the target detection task is customized as an optimization problem of low-rank and sparse (LRS) tensor recovery. To better preserve the internal structure and capture more global information, the tensor spectral $k$ -support norm minimization is introduced as the regularization term of the constraint background. Finally, draw support from the framework of alternating direction method of multipliers (ADMM) algorithm, the precise separation of target and background is achieved. In addition, to promote the prosperity of sequential detection methods, we released to the scientific community a small IR target dataset containing six image sequences with urban background. The experimental results on six real IR sequences demonstrate that our method outputs the most outstanding detection performance compared with the latest sequential detection methods.
Direction-of-Arrival Estimation Method Based on Neural Network with Temporal Structure for Underwater Acoustic Vector Sensor Array

Acoustic vector sensor (AVS) is a kind of sensor widely used in underwater detection. Traditional methods use the covariance matrix of the received signal to estimate the direction-of-arrival (DOA), which not only loses the timing structure of the signal but also has the problem of weak anti-noise ability. Therefore, this paper proposes two DOA estimation methods for underwater AVS arrays, one based on a long short-term memory network and attention mechanism (LSTM-ATT), and the other based on Transformer. These two methods can capture the contextual information of sequence signals and extract features with important semantic information. The simulation results show that the two proposed methods perform much better than the multiple signal classification (MUSIC) method, especially in the case of low signal-to-noise ratio (SNR), the DOA estimation accuracy has been greatly improved. The accuracy of the DOA estimation method based on Transformer is comparable to that of the DOA estimation method based on LSTM-ATT, but the computational efficiency is obviously better than that of the DOA estimation method based on LSTM-ATT. Therefore, the DOA estimation method based on Transformer proposed in this paper can provide a reference for fast and effective DOA estimation under low SNR.
Improved Salp Swarm Algorithm for the Calibration of the Underwater Transponder

Traditional transponder calibration methods are deficient in depth estimation. Especially in the absence of a depth gauge (DG), this method will directly lead to the decline of spatial positioning accuracy. In order to optimize this problem, this article improves the conventional salp swarm algorithm (SSA) algorithm and proposes an improved SSA (ISSA) algorithm for underwater target locations. ISSA has an excellent performance in depth estimation, and in the absence of DG, the horizontal positioning accuracy is comprehensively ahead of the traditional algorithms, and there is no doubt that its spatial positioning ability is also optimal. In order to verify the superiority of ISSA, several sets of simulation experiments and Yangtze River experiments are designed. The experimental results show that the proposed ISSA is superior to the common algorithms in underwater transponder calibration, not only in deep positions, but also the horizontal and spatial positioning.
Surface-Modified TiO2@SiO2 Nanocomposites for Enhanced Dispersibility and Optical Performance to Apply in the Printing Process as a Pigment

The grafted modification TiO2@SiO2 composite was fabricated by a liquid-phase deposition method with Na2SiO3 and a grafting reaction with a silane coupling agent. First, the TiO2@SiO2 composite was prepared, and the effect of deposition rate and silica content on the morphology, particle size, dispersibility, and pigmentary property of TiO2@SiO2 composites was investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy, energy-dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), and ζ-potential. The islandlike TiO2@SiO2 composite had a good particle size and printing performance compared with the dense TiO2@SiO2 composite. The presence of Si was confirmed by EDX elemental analysis and XPS, and a peak at 980 cm–1 belonging to Si–O was observed in the FTIR spectrum, confirming the presence of SiO2 anchored at TiO2 surfaces via Si–O–Ti bonds. Then, the islandlike TiO2@SiO2 composite was modified by grafting with a silane coupling agent. The effect of the silane coupling agent on the hydrophobicity and dispersibility was investigated. The peaks at 2919 and 2846 cm–1 belong to CH2 in the FTIR spectrum, and Si–C in the XPS confirmed the grafting of silane coupling agent to the TiO2@SiO2 composite. The grafted modification of the islandlike TiO2@SiO2 composite using 3-triethoxysilylpropylamine endowed it with weather durability, dispersibility, and good printing performance.
Multi-direction-based Nelder–Mead method

The original Nelder–Mead (NM) method tends to be used to optimize low-dimensional functions. This article provides a modified NM that has the capability of large-scale optimization. The modification of NM is characterized by (a) working with a population of points, (b) mining multiple search directions through two strategies – point-grouping and variable-centroid multi-direction (VCMD), thus giving rise to VCMD plus grouping (VCMDg) and (c) introducing random coefficients into NM and performing mutation on best-points, producing a random NM (NMr). The combination of NMr and VCMDg, NMr-VCMDg, is just the modified NM in this work.
Transcriptional Interactions of Single B-Subgenome Chromosome with C-Subgenome in B. oleracea-nigra Additional Lines

Serial monosomic alien addition lines (MAALs) provide an ideal system to elucidate the transcriptomic interactions between the alien chromosomes and recipient genome under aneuploidy. Herein, five available Brassica oleracea-nigra MAALs (CCB1, CCB4, CCB5, CCB6, CCB8), their derived B. oleracea plants (non-MAALs), and two parents were analyzed for their gene expressions by using high-throughput technology. Compared to parental B. oleracea, all MAALs showed various numbers of DEGs, but CCB8 gave much higher DEGs; the number of downregulated DEGs was slightly higher than the number of upregulated ones, except for in relation to CCB8. All derived B. oleracea plants also gave certain numbers of DEGs, despite these being much lower than in the respective MAALs. Compared to B. nigra, in all five MAALs more DEGs were downregulated than upregulated. Trans-effects were likely more prevailing than cis-effects, and these DEGs were predominantly associated with material transport by dysregulating the cellular component. Meanwhile, the orthologous genes on alien chromosomes could only play a feeble compensatory role for those gene pairs in C-subgenome, and different levels of the expressed genes had a greater tendency towards downregulation. These results revealed transcriptional aneuploidy response patterns between two genomes and suggested that cis- and trans-mechanisms synergistically regulated alien gene transcriptions after distant hybridization.
Trajectories of Drug Use and Depressive Symptoms among Latinx Youth and Sexual Minority Youth

Drug use and depression co-occur and disproportionately affect Latinx sexual minority youth relative to their heterosexual Latinx peers. However, heterogeneity in co-occurring patterns of drug use and depressive symptoms is unknown. The objective of the current study was to identify patterns of drug use and depressive symptom trajectories and examine how these patterns varied between Latinx sexual minority youth and Latinx non-sexual minority youth. Latent class trajectory analysis identified distinct patterns of drug use and depressive symptom trajectories among 231 Latinx adolescents (Latinx sexual minority youth: n = 46, 21.4%; Latinx non-sexual minority youth: n = 169, 78.6%). After identifying class mean trajectories, we examined differences in mean trajectories across groups. A 3-class model was selected as the optimal class trajectory model for both groups, yet classes and trajectories differed. There were differences in initial levels of depression and drug use trajectories between both groups, as well as differences in patterns of drug use trajectories between both groups in two of the three classes. Given the variation in trajectory patterns, there is a need for practitioners to consider the unique needs of both groups to inform the development of preventive interventions for these two populations.
Practical Panel Conditional Logit Estimators for Binary, Ordered Discrete and Multinomial Responses

This chapter reviews panel conditional logit estimators (PCLE’s) mainly for binary responses. The main part is then generalized for ordered discrete responses, time-varying parameters and multinomial responses. The review covers the underlying theories leading to PCLE’s as well as their practical implementations, focusing on easy-to-apply estimators that converge well in practice. Simulations and empirical illustrations are provided.
The Relationship between Force and Length Change with Temperature Changes in the Synthetic Muscle of Complex Nylons

Artificial muscle benefits from outstanding properties and is widely used in numerous industries. The new type of this muscle is made of nylon and provides more advantages than the previous ones. The mechanism is such that by giving heat, it causes a change in the length of the muscle. The study analyzes the muscle and calculates the changes in length and force by giving heat, and the relationship between changes in length and force with temperature changes is determined. For this purpose, three diameters are considered and their efficiency is compared