Publications by authors named "Zhenyue Zhang"

The rise of two-dimensional (2D) materials has provided a confined geometry and yielded methods for guiding electrons at the nanoscale level. 2D material-enabled electronic devices can interact and transduce the subtle charge perturbation and permit significant advancement in molecule discrimination technology with high accuracy, sensitivity, and specificity, leaving a significant impact on disease diagnosis and health monitoring. However, high-performance biosensors with scalable fabrication ability and simple protocols have yet to be fully realized due to the challenges in wafer-scale 2D film synthesis and integration with electronics.

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Phosphogypsum (PG), a byproduct during the phosphoric acid production process, also known as the wet process, contains complex and diverse impurities, resulting in low utilization and considerable accumulation. This leads to a massive waste of land resources and a series of environmental pollution problems. Given the current urgent ecological and environmental situation, developing impurity removal processes with low energy consumption and high efficiency, exploring valuable resource recovery, preparing high value-added PG products, and broadening the comprehensive utilization ways of PG are significant strategies to promote the sustainable consumption of PG and sustainable development of the phosphorus chemical industry.

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The ion-exchangeable ammonium (IE-A) that accounts for 60-90% of the total residual ammonium in rare earth tailings has great potential to pollute the surrounding environment, and much research has been done to seek an effective elution method. However, the current study mainly focused on the single salt solution, which made it hard to reach the desired elution efficiency. In this study, the efficient binary compound eluent was prepared, and the response surface experiments and dynamic elution were performed to optimize the elution condition and evaluate the practical application prospect.

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The increasing demand for rare earth elements (REEs), especially from new and innovative technology, has strained their supply, which makes the exploration of new REE sources necessary, for example, the recovery of REEs from phsophogypsum (PG). PG is a byproduct during the wet production of phosphoric acid, which is an attractive secondary resource for REEs due to a large amount of REEs locked in them. In most cases, REEs contained in PG are mainly encapsulated in the gypsum crystal, leading to a low leaching efficiency.

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Article Synopsis
  • - The study aimed to determine how the dispersion of bone cement affects pain levels following vertebral augmentation for osteoporotic fractures, focusing on two groups based on cement distribution: sufficient diffusion (Group A) and insufficient diffusion (Group B).
  • - Results showed that both groups experienced significant pain relief post-surgery, but Group A had notably better pain and disability scores compared to Group B, indicating the importance of adequate cement dispersion.
  • - There were measurable differences in cement volume and its ratio between the groups, with Group A having greater volumes, suggesting that more effective cement distribution leads to improved outcomes in pain management after the procedure.
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The utilization of symbiosis with beneficial microorganisms has considerable potential for increasing growth and resistance under abiotic stress. The endophytic root fungus Piriformospora indica has been shown to improve plant growth under salt and drought stress in diverse plant species, while there have been few reports of the interaction of P. indica with soybean under salt stress.

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Rare cold-inducible 2 (RCI2) genes from alfalfa ( L.) are part of a multigene family whose members respond to a variety of abiotic stresses by regulating ion homeostasis and stabilizing membranes. In this study, salt, alkali, and ABA treatments were used to induce and expression in alfalfa, but the response time and the expression intensity of the genes were different under specific treatments.

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Phosphate tailings (PTs) are solid waste, which is produced by phosphate flotation. In this work, PTs were used as raw materials for the preparation of diethylenetriamine pentamethronic acid (DTPMP) intercalated trimetal (Ca-Mg-Al) layered double hydroxides (TM-DTPMP LDHs) by co-precipitation method. TM-DTPMP LDHs were characterized by X-ray diffraction, fourier-transform infrared spectroscopy, scanning electron microscopy, differential thermal gravimetric analysis, X-ray photoelectron spectroscopy and applied as a flame retardant to improve the fire safety of epoxy resin (EP).

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Background: Zinc finger homeodomain (ZHD) protein is a plant-specific transcription factor and a potential regulator of phosphoenolpyruvate carboxylase (PEPCase)-coding genes, and it also participates in plant growth regulation and abiotic stress responses. To study the function of MsZF-HD genes in the alkaline stress response, this paper assessed biological information and performed transcriptome analysis of the MsZF-HD gene family by using the genomes of two different varieties of alfalfa (XinJiangDa Ye and Zhongmu No. 1).

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To reveal the ion-exchange mechanism in the leaching process of weathered crust elution-deposited rare earth ores with different leaching agents, the effects of a variety of cations and anions at different concentrations on the leaching process were investigated, including Al, Fe, Ca, Mg, Na, K, and Cl, , and . Meanwhile, the relationships between different concentrations of cations and anions and leaching efficiency were investigated, as was the relationship between different concentrations of cations and anions and zeta potential. The effect of different ions on the swelling of clay minerals during leaching process was also investigated.

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To strengthen the rare earth leaching process and weaken the hydration of clay minerals for preventing landslides, it is of great importance to adopt a green and sustainable leaching agent in the industry. In this work, the leaching process of weathered crust elution-deposited rare earth ores with formate salts (ammonium formate, potassium formate, and sodium formate) was investigated. The effects of formate salts on the linear swelling ratio and zeta potential of the clay minerals were studied.

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Take-all is a devastating soil-borne disease that affects wheat production. The continuous generation of disease-resistance germplasm is an important aspect of the management of this pathogen. In this study, we characterized the wheat- Keng ()-derived progeny H139 that exhibits significantly improved resistance to wheat take-all disease compared with its susceptible parent 7182.

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Semi-Supervised Domain Adaptation by Covariance Matching.

IEEE Trans Pattern Anal Mach Intell

November 2019

Transferring knowledge from a source domain to a target domain by domain adaptation has been an interesting and challenging problem in many machine learning applications. The key problem is how to match the data distributions of the two heterogeneous domains in a proper way such that they can be treated indifferently for learning. We propose a covariance matching approach DACoM for semi-supervised domain adaptation.

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Multi-view learning aims to integrate multiple data information from different views to improve the learning performance. The key problem is to handle the unconformities or distortions among view-specific samples or measurements of similarity or dissimilarity. This paper models the view-specific samples as a nonlinear mapping of uniform but latent intact samples for all the views, and the view-specific dissimilarity matrices or similarity matrices are estimated in terms of the uniform latent one.

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This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model.

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Adaptive manifold learning.

IEEE Trans Pattern Anal Mach Intell

February 2012

Manifold learning algorithms seek to find a low-dimensional parameterization of high-dimensional data. They heavily rely on the notion of what can be considered as local, how accurately the manifold can be approximated locally, and, last but not least, how the local structures can be patched together to produce the global parameterization. In this paper, we develop algorithms that address two key issues in manifold learning: 1) the adaptive selection of the local neighborhood sizes when imposing a connectivity structure on the given set of high-dimensional data points and 2) the adaptive bias reduction in the local low-dimensional embedding by accounting for the variations in the curvature of the manifold as well as its interplay with the sampling density of the data set.

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