国有企业计算机网络管理

本论文在简单了解了计算机网络的相关内容后,对国有企业的计算机网络进行了简单的介绍,并举例说明了某国有企业的网络管理结构及功能。     

Herfindahl index applied to Fourier analysis

Since the harmonic components in the signal to be analyzed are uncertain and diverse, it is difficult to make the sampling frequency and the signal length be harmonically related to the component frequencies included in the signal, and the leakage is produced in the discrete Fourier transform. Based on the definition of the Herfindahl index in economics, the spectrum concentration can be defined and computed. The appropriate number of points can be decided according to the peak location of the spectrum concentration. The method and the examples are specified in detail in the paper.     

Minimizing Energy Barrier in Intermediate Connection Layer for Monolithic Tandem WPeLEDs with Wide Color Gamut

Perovskite light-emitting diodes (PeLEDs) show promising prospects in the wide color gamut display owing to their ultra-narrow full width at half maximum (FWHM). However, up to now, all perovskite white LEDs integrated by standard red, green, and blue perovskite emitters, namely, monolithic white PeLEDs (WPeLEDs), have been rarely reported, owing to facing some issues, e.g., solvent incompatibility in solution technique, ion exchange, and energy transfer between different emission centers. Herein, centered on these issues, an optimal intermediate connection layer (ICL) of Po-T2T/LiF/Ag/HAT-CN/MoO₃ is adopted to successfully develop monolithic tandem multicolor PeLEDs and WPeLEDs for the first time. The multicolor PeLEDs can achieve the best external quantum efficiency of 1.8% and the highest luminance of 4844 cd m⁻². Besides, the red/green/blue (R/G/B) monolithic tandem WPeLED shows a standard white International Commission on Illumination coordinate of (0.33, 0.33) and achieves an extremely wide color gamut reaching  National Television Standards Committee of 130%. This study is the first to realize the standard R/G/B co-electroluminescence in a monolithic perovskite device and offers a feasible strategy for developing wide-color gamut perovskite displays.     

Macrophage Membrane-Coated Nanoparticles Sensitize Glioblastoma to Radiation by Suppressing Proneural–Mesenchymal Transformation in Glioma Stem Cells

Radiotherapy is identified as a crucial treatment for patients with glioblastoma, but recurrence is inevitable. The efficacy of radiotherapy is severely hampered partially due to the tumor evolution. Growing evidence suggests that proneural glioma stem cells can acquire mesenchymal features coupled with increased radioresistance. Thus, a better understanding of mechanisms underlying tumor subclonal evolution may develop new strategies. Herein, data highlighting a positive correlation between the accumulation of macrophage in the glioblastoma microenvironment after irradiation and mesenchymal transdifferentiation in glioblastoma are presented. Mechanistically, elevated production of inflammatory cytokines released by macrophages promotes mesenchymal transition in an NF-κB-dependent manner. Hence, rationally designed macrophage membrane-coated porous mesoporous silica nanoparticles (MMNs) in which therapeutic anti-NF-κB peptides are loaded for enhancing radiotherapy of glioblastoma are constructed. The combination of MMNs and fractionated irradiation results in the blockage of tumor evolution and therapy resistance in glioblastoma-bearing mice. Intriguingly, the macrophage invasion across the blood-brain barrier is inhibited competitively by MMNs, suggesting that these nanoparticles can fundamentally halt the evolution of radioresistant clones. Taken together, the biomimetic MMNs represent a promising strategy that prevents mesenchymal transition and improves therapeutic response to irradiation as well as overall survival in patients with glioblastoma.     

Semi-supervised transformable architecture search for feature distillation

Pattern Analysis and Applications - The designed method aims to perform image classification tasks efficiently and accurately. Different from the traditional CNN-based image classification methods,...     

Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks

International Journal of Computer Vision - Visual tracking of generic objects is one of the fundamental but challenging problems in computer vision. Here, we propose a novel fully convolutional...     

Decomposed-distance weighted optimal transport for unsupervised domain adaptation

Applied Intelligence - Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a label-rich source domain to an unlabeled target domain with a different but related distribution....