Seismic wavefield modeling is an important tool for the seismic interpretation. We consider modeling the wavefield in the frequency domain. This requires to solve a sequence of Helmholtz equations of ...wave numbers governed by the Nyquist sampling theorem. Inevitably, we have to solve Helmholtz equations of large wave numbers, which is a challenging task numerically. To address this issue, we develop two methods for modeling the wavefield in the frequency domain to obtain an alias-free result using lower frequencies of a number fewer than typically required by the Nyquist sampling theorem. Specifically, we introduce two ℓ1 regularization models to deal with incomplete Fourier transforms, which arise from seismic wavefield modeling in the frequency domain, and propose a new sampling technique to avoid solving the Helmholtz equations of large wave numbers. In terms of the fixed-point equation via the proximity operator of the ℓ1 norm, we characterize solutions of the two ℓ1 regularization models and develop fixed-point algorithms to solve these two models. Numerical experiments are conducted on seismic data to test the approximation accuracy and the computational efficiency of the proposed methods. Numerical results show that the proposed methods are accurate, robust and efficient in modeling seismic wavefield in the frequency domain with only a few low frequencies.
To investigate the function of gene PA2580 in Pseudomonas aeruginosa PAO1.
We constructed a PA2580 knockout mutant of PAO1 and a complemented strain of the mutant. We studied the function of the gene ...PA2580 using both genetic and biochemical methods, including antibiotic minimum inhibition concentration (MIC) comparison, measurement of gene expression levels in different conditions, protein expression and purification in vitro and enzymatic activity detection.
PA2580 mutant was more sensitive to carbenicillin, chloramphenicol and ciprofloxacin. PA2580 expression was regulated by sub-inhibitory concentrations of antibiotics. PA2580 protein reduced various quinones efficiently using NADPH as the electron donor. PA2580 mutant was more sensitive to hydrogen peroxide and the mutant showed decreased expression of catalase. These results indicate that PA2580 is involved in the tolerance of oxidative stress in P. aeruginosa.
The P. aeruginosa PA2580 protein physiologically functions as an NADPH quinone reductase whic
To study the robustness of complex networks while encountering random failures or deliberate attacks, the cascading failure model is constructed by considering failure propagation with probability, ...which can depict the dynamic failure process. In particular, the characteristics of time delay and repetitive failure are taken into account in our model, and the network comprehensive robustness index (RI) is further designed according to valid survival edges and nodes. Additionally, the probability recovery strategy is proposed as well, and it is implemented in four typical networks, including the BA network, WS network, NC network and ER network. Different parameters in our model, including α, f, R, and β, are applied in simulation experiments to reveal their effects on RI in the cascading failure process. The simulation results show that nodes’ recovery abilities increase with R, which reduce the impacts of cascading failures and produce good network robustness. Meanwhile, the time delay increases with parameter α, and the size of the cascading failure decreases accordingly, which indicates that the larger that the time delay is, the stronger the RI. Additionally, the speed of the cascading failure process and the size of the cascading failure both present an increasing trend when parameter f increases gradually in the cascading failure. This indicates that the failure probability apparently impacts the RI. We also analyze the turning point t for RI(t) during the cascading failure process.
•We construct a cascading failure model by considering time delay in failure propagation process.•The probability of repeating failure on node has negative relation with the times of failures.•We consider the node recovery probability that is related with the nodes’ degree.•We test the effects of different parameters on four types of networks robustness index.
We consider minimization of functions that are compositions of functions having closed-form proximity operators with linear transforms. A wide range of image processing problems including image ...deblurring can be formulated in this way. We develop proximity algorithms based on the fixed point characterization of the solution to the minimization problems . We further refine the proposed algorithms when the outer functions of the composed objective functions are separable. The convergence analysis of the developed algorithms is established. Numerical experiments in comparison with the well-known Chambolle-Pock algorithm and Zhang-Burger-Osher scheme for image deblurring are given to demonstrate that the proposed algorithms are efficient and robust.
We propose a constrained inpainting model to recover an image from its incomplete and/or inaccurate wavelet coefficients. The objective functional of the proposed model uses the ℓ0 norm to promote ...the sparsity of the resulting image in a tight framelet system. To overcome the algorithmic difficulty caused by the use of the ℓ0 norm, we approximate the ℓ0 norm by its Moreau envelope. A fixed-point proximity algorithm is developed to solve the new approximation optimization model and the convergence analysis of the algorithm is provided. The proposed algorithm can be accelerated by the FISTA technique and we also develop an adaptive method to determine the approximation parameter to further speed up the algorithm. We demonstrate that the rows of the discrete cosine transform matrix can generate a redundant tight framelet system with symmetric boundary condition, which has good ability to extract information from incomplete wavelet coefficients. Using the tight framelet system, our numerical experiments show that the proposed model and the related fixed-point algorithm can recover images with much higher quality in terms of the PSNR values and visual quality of the restored images than the models based on the ℓ1 norm and the total variation.
Recent studies have shown that subinhibitory antibiotics play important roles in regulating bacterial genes including virulence factor genes. In this study, the expression of 13 secreted virulence ...related gene clusters of Pseudomonas aeruginosa, an important opportunistic pathogen, was examined in the presence of subinhibitory concentrations of 4 antibiotics: vancomycin, tetracycline, ampicilin and azithromycin. Activation of gene expression was observed with phzA1, rhlAB, phzA2, lasB, exoY, and exoS. Subinhibitory concentrations of vancomycin resulted in snore than 10-fold increase of rhlAB and phzA2 transcription. Both rhamnolipid production and pyocyanin production were significantly elevated, correlating phenotypes with the increased transcription. P. aeruginosa swarming and swimming motility also increased. Similar results were observed with subinhibitory tetracycline, azithromycin and ampicillin. These results indicate that the antibiotics at low concentrations can up-regulate virulence factors and therefore influence bacterial pathogenesis.
The recently proposed tensor correlated total variation (t-CTV) has achieved success in tensor completion. It utilizes the low-rank structure of the gradient tensor under a unified linear transform ...to jointly encode low-rankness and smoothness priors. However, fixed linear transforms have inherent limitations in fully characterizing gradient tensors in different directions and adapting them to tensors from diverse categories. In this work, we propose the nonlinear tensor correlated total variation (NTCTV) regularization term that leverages the low-rank correlations of the gradient tensor under the learnable nonlinear transformation, providing a more natural approach to fuse the low-rankness and smoothness priors. Specifically, our approach learns the optimal nonlinear implicit low-rank structure of the gradient tensor along different modes separately, and then achieves the expression of fused prior information in a coupled manner. Furthermore, we propose the NTCTV-based tensor completion model and design the proximal alternating minimization (PAM) algorithm to efficiently solve the optimization model. Moreover, we provide a theoretical proof of the global convergence of the algorithm to a critical point. Comprehensive experimental results for hyperspectral images, medical images, multispectral images, and videos demonstrate that the proposed method achieves substantial quantitative and qualitative improvements over many state-of-the-art tensor completion techniques.
•We propose a nonlinear tensor correlated total variation (NTCTV).•We propose a NTCTV-based tensor completion model and design a solution algorithm.•We prove that the iterative point sequence converges to a critical point.•The proposed method outperforms competitive methods, yielding superior results.
•The hydrogel promotes skull defect repair through synergistic effects of immunomodulation, angiogenesis and osteogenesis.•The moldable hydrogel can be adapted to the skull defect with any irregular ...shape or fissure damage.•Zn5%/F10%-HAp has a three-in-one function of angiogenesis, osteogenic differentiation, and biomineralization via ion release.•Modified sericin achieves immunoregulation by inducing M2 polarization of macrophages, breaking the delay in skull defect repair.
Skull defect repair typically involves multiple stages, including immunomodulation, angiogenesis, osteogenic differentiation, and biomineralization, etc. Most existing therapeutic biomaterials fail to show functional effects across all these stages, leading to unsatisfactory repair effects. To address this challenge, an organic–inorganic hybrid HT(SA)HAp moldable hydrogel with the aforementioned functional properties was developed. The moldable hydrogel consisted of phenylboronic acid-grafted hyaluronic acid, tannic acid, alendronate sodium-grafted sericin (Ser-AL), and hydroxyapatite co-doped with 5 % Zn and 10 % F (Zn5%/F10%-HAp). These materials were cross-linked due to phenylborate ester bonds, metal-phenol interactions, and the AL-mediated chelation of divalent metal cations. Sericin-mediated immunomodulation serves as a precursor to micro-environmental regulation, reducing inflammation at the site of injury and creating an environment conducive to angiogenesis and osteogenic differentiation. The degradation products of the hydrogel’s organic skeleton promoted the proliferation of mesenchymal stem cells and vascular endothelial cells. The enhanced paracrine effect of mesenchymal stem cells and the release of Zn2+ from modified Zn5%/F10%-HAp promoted angiogenesis, while the degradation products of these materials ensured continued promotion of osteogenic differentiation and biomineralization. This organic–inorganic hybrid hydrogel had the synergistic effects of immunoregulation, enhanced angiogenesis, osteogenic differentiation, and biomineralization, which could significantly accelerate the repair of skull defects, and demonstrate completely repaired skull defects at 8 weeks. Thus, this multifunctional moldable hydrogel provided an effective and stable treatment strategy for the rapid repair of skull defects.
This note is to study the proximity operator of hp=‖⋅‖1p, the power function of the ℓ1 norm. For general p, computing the proximity operator requires solving a system of potentially highly nonlinear ...inclusions. For p=1, the proximity operator of h1 is the well known soft-thresholding operator. For p=2, the function h2 serves as a penalty function that promotes structured solutions to optimization problems of interest; the computation of the proximity operator of h2 has been discussed in recent literature. By examining the properties of the proximity operator of the power function of the ℓ1 norm, we will develop a simple and well-justified approach to compute the proximity operator of hp with p>1. In particular, for the squared ℓ1 norm function, our approach provides an alternative, yet explicit way to finding its proximity operator. We also discuss how the structure of hp represents a class of relative sparsity promoting functions.
Quorum sensing is a global gene-regulatory mechanism in bacteria that enables individual bacterial cells to communicate and coordinate their population behaviors. Quorum sensing is central to the ...pathogenesis of many bacterial pathogens including Pseudomonas aeruginosa and therefore has been exploited as a target for developing novel antipathogenic drugs. In P. aeruginosa, three intertwined quorum-sensing systems, las, rhl, and the 2-alkyl-4(1H)-quinolone system, which includes the Pseudomonas quinolone signal (PQS), control virulence factor production, and pathogenesis processes. Previously, we obtained a mutant with diminished expression of the phzA1B1C1D1E1F1G1 operon that is involved in the production of virulence factor phenazine compounds. In this study, the mutant was further characterized, and evidence indicating that the disrupted gene PA1196 in the mutant is a potential regulator of the rhl and PQS systems is presented. PA1196 positively controls the expression of the rhl and PQS systems and affects bacterial motility and multiple virulence factor expression via the quorum-sensing systems. This adds an important new player in the complex quorum-sensing network in P. aeruginosa.
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