Poisson image fusion based on Markov random field fusion model

In this paper, we present a gradient domain image fusion framework based on the Markov Random Field (MRF) fusion model. In this framework, the salient structures of the input images are fused in the gradient domain, then the final fused image is reconstructed by solving a Poisson equation which forces the gradients of the fused image to be close to the fused gradients. To fuse the structures in the gradient domain, an effective MRF-based fusion model is designed based on both the per-pixel fusion rule defined by the local saliency and also the smoothness constraints over the fusion weights, which is optimized by graph cut algorithm. This MRF-based fusion model enables the accurate estimation of region-based fusion weights for the salient objects or structures. We apply this method to the applications of multi-sensor image fusion, including infrared and visible image fusion, multi-focus image fusion and medical image fusion. Extensive experiments and comparisons show that the proposed fusion model is able to better fuse the multi-sensor images and produces high-quality fusion results compared with the other state-of-the-art methods.     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

基于BP网络的机场助航故障灯检测

恒流调光器是为飞机起降提供目视引导的关键设备。对回路中故障灯的准确及时检测是调光器的重要功能。有关调光器的国际标准以及国标对该设备的功能均有严格要求,然而相关资料尚属鲜见难于借鉴。文中对这一课题进行了探讨,利用BP神经网络对调光器回路中的故障,进行监测并测算故障灯数目。实践表明,文章所用方法能有效地监测调光器故障,并能准确报告故障灯数目。     

Siamese transformer network-based similarity metric learning for cross-source remote sensing image retrieval

Neural Computing and Applications - As a fundamental technique for mining and analysis of remote sensing (RS) big data, content-based remote sensing image retrieval (CBRSIR) has received a lot of...     

Biomedical applications of mRNA nanomedicine

As an attractive alternative to plasmid DNA, messenger RNA (mRNA) has recently emerged as a promising class of nucleic acid therapeutics for biomedical applications. Advances in addressing the inherent shortcomings of mRNA and in the development of nanoparticle-based delivery systems have prompted the development and clinical translation of mRNA-based medicines. In this review, we discuss the chemical modification strategies of mRNA to improve its stability, minimize immune responses, and enhance translational efficacy. We also highlight recent progress in nanoparticle-based mRNA delivery. Considerable attention is given to the increasingly widespread applications of mRNA nanomedicine in the biomedical fields of vaccination, protein-replacement therapy, gene editing, and cellular reprogramming and engineering.     

Entrapping multifunctional dendritic nanoparticles into a hydrogel for local therapeutic delivery and synergetic immunochemotherapy

Nano Research - Developing multifunctional nanoparticles to support new therapy models is a promising and challenging task to address the current dilemma on antitumor treatment. Herein, we...     

Aggregation-induced emission luminogen-assisted stimulated emission depletion nanoscopy for super-resolution mitochondrial visualization in live cells

Nano Research - Aggregation-induced emission luminogens (AIEgens) are fluorescent agents that are ideal for bioimaging and have been widely used for organelle targeting, cellular mapping, and...     

Escherichia coli prlC gene encodes a trypsin-like proteinase regulating the cell cycle

BACKGROUND AND PURPOSE: Mood disorders are common after stroke and may impede physical, functional, and cognitive recovery, making early identification and treatment of potential importance. We aimed to compare the accuracy of the General Health Questionnaire (GHQ-30) and the Hospital Anxiety and Depression (HAD) Scale in detecting psychiatric morbidity after stroke and to determine the most suitable cutoff points for different purposes. METHODS: One hundred five hospital-referred stroke patients completed both the GHQ-30 and HAD Scale 6 months after onset before a blinded psychiatric assessment in which the Schedule for Affective Disorders and Schizophrenia with some supplementary questions was used to determine a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) diagnosis. Measures were compared in terms of sensitivity, specificity, and receiver operating characteristic curves. RESULTS: No significant differences were found between the GHQ-30 and the HAD Scale in identifying those patients with any DSM-IV diagnosis (P=0.95), grouped depression (P=0.56), or anxiety (P=0.25) disorders. The previously recommended cutoff points for identifying "cases" for the GHQ (4/5) and for the HAD Scale (8/9 and 11/12) were found to be suboptimal in this population. CONCLUSIONS: The GHQ-30 and HAD scale exhibited similar levels of sensitivity and specificity. Data are presented, taking into account the "cost" of false-positives and negatives, to allow a choice of cutoff points suitable for differing situations.