Perceptual image preview

Image preview is a convenient way to browse large or multiple images on small displays. However, current signal-level image resampling algorithms may remove many features of interest in the preview image. In this paper, we propose perceptual image preview which retains more perceptual features such that users can inspect features of interest by viewing the preview image only and without zooming in. This technology has two components, structure enhancement and perceptual feature visualization. Structure enhancement enhances the image structure while suppressing subtle details using a gradient modulation method, thus making the succedent perceptual features more apparent. For perceptual feature visualization, features of interest detected in the picture is visualized on the structure enhanced preview image. We demonstrate with two examples of most commonly used image quality features, image blur and noise. The effectiveness of the proposed method is validated by experimental results.     

安徽省地震会商系统软件界面设计研究

基于ARCGis9.2的安徽省地震会商系统不仅需要强大的技术功能,还需要友好和一目了然的界面,这样不仅让会商报告者思路清晰,也能使会商观众更加清晰了解地震预报会商内容,从而为决策者更好应对不同地点和不同大小的地震发生可能性做出科学的决策;引入flash8作为软件系统的界面,用flash调用各个模块,无论从界面和功能上都较好的解决了这一问题。     

Extracting Takagi-Sugeno Fuzzy Rules with Interpretable Submodels via Regularization of Linguistic Modifiers

In this paper, a method for constructing Takagi-Sugeno (TS) fuzzy system from data is proposed with the objective of preserving TS submodel comprehensibility, in which linguistic modifiers are suggested to characterize the fuzzy sets. A good property held by the proposed linguistic modifiers is that they can broaden the cores of fuzzy sets while contracting the overlaps of adjoining membership functions (MFs) during identification of fuzzy systems from data. As a result, the TS submodels identified tend to dominate the system behaviors by automatically matching the global model (GM) in corresponding subareas, which leads to good TS model interpretability while producing distinguishable input space partitioning. However, the GM accuracy and model interpretability are two conflicting modeling objectives, improving interpretability of fuzzy models generally degrades the GM performance of fuzzy models, and vice versa. Hence, one challenging problem is how to construct a TS fuzzy model with not only good global performance but also good submodel interpretability. In order to achieve a good tradeoff between GM performance and submodel interpretability, a regularization learning algorithm is presented in which the GM objective function is combined with a local model objective function defined in terms of an extended index of fuzziness of identified MFs. Moreover, a parsimonious rule base is obtained by adopting a QR decomposition method to select the important fuzzy rules and reduce the redundant ones. Experimental studies have shown that the TS models identified by the suggested method possess good submodel interpretability and satisfactory GM performance with parsimonious rule bases.     

基于经济的网格资源调度算法研究

网格使构建虚拟组织,在全世界范围内共享资源成为现实.但是,在网格环境下的资源管理和调度是一项相当复杂的工作,这主要是由于资源分布在世界各地,隶属于不同的组织,各个资源拥有者都有不同的使用和访问策略、开销模型、不断变化的负载和可用性.为了满足网格计算环境中资源调度的复杂需要,可以将现实世界中的经济原理和模型应用到网格环境下的任务调度中,并据此提出了几种经济资源调度算法.     

Two-dimensional Kerr-Fourier imaging of translucent phantoms in thick turbid media

Translucent scattering phantoms hidden inside a 5.5-cm-thick Intralipid solution were imaged as a function of phantom scattering coefficients by the use of a picosecond time- and space-gated Kerr-Fourier imaging system. A 2-mm-thick translucent phantom with a 0.1% concentration (scattering coefficient) difference from the 55-mm-thick surrounding scattering host can be distinguished at a signal level of ~10(-10) of the incidence illumination intensity.     

Analysis of light propagation characteristic in the aero-optic flow field of cone-headed vehicle with side window

Aero-optic imaging deviation research is carried out for infrared-guided vehicle with cone-head side window, with a focus on the propagation characteristics of light in an aero-optic flow field. When the light entering the aero-optic flow field from the free-stream should be close to the normal, numerous data indicate that the light is refracted away from the normal. This paper divides the aero-optic flow field into two parts and uses the gas density distribution in the aero-optic flow field to ...     

2D Bi2O2Te Semiconductor with Single-Crystal Native Oxide Layer

Following logic in the silicon semiconductor industry, the existence of native oxide and suitable fabrication technology is essential for 2D semiconductors in planar integronics, which are surface-sensitive to typical coating technologies. To date, very few types of integronics are found to possess this feature. Herein, the 2D Bi₂O₂Te developed recently is reported to possess large-area synthesis and controllable thermal oxidation behavior toward single-crystal native oxides. This shows that surface-adsorbed oxygen atoms are inclined to penetrate across [Bi₂O₂]_n²ⁿ⁺ layers and bond with the underlying [Te]_n²ⁿ⁻ at elevated temperatures, transforming directly into [TeO₄]_n²ⁿ⁻ with the basic architecture remaining stable. The oxide can be adjusted to form in an accurate layer-by-layer manner with a low-stress sharp interface. The native oxide Bi₂TeO₆ layer (bandgap of ≈2.9 eV) exhibits visible-light transparency and is compatible with wet-chemical selective etching technology. These advances demonstrate the potential of Bi₂O₂Te in planar-integrated functional nanoelectronics such as tunnel junction devices, field-effect transistors, and memristors.     

Voltage Decay of Li-Rich Layered Oxides: Mechanism,Modification Strategies,and Perspectives

Li-rich layered oxides (LLOs) have been considered as the most promising cathode materials for achieving high energy density Li-ion batteries. However, they suffer from continuous voltage decay during cycling, which seriously shortens the lifespan of the battery in practical applications. This review comprehensively elaborates and summarizes the state-of-the-art of the research in this field. It is started from the proposed mechanism of voltage decay that refers to the phase transition, microscopic defects, and oxygen redox or release. Furthermore, several strategies to mitigate the voltage decay of LLOs from different scales, such as surface modification, elemental doping, regulation of components, control of defect, and morphology design are summarized. Finally, a systematic outlook on the real root of voltage decay is provided, and more importantly, a potential solution to voltage recovery from electrochemistry. Based on this progress, some effective strategies with multiple scales will be feasible to create the conditions for their commercialization in the future.     

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.     

Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.