Nebulized Gadolinium‐Based Nanoparticles: A Theranostic Approach for Lung Tumor Imaging and Radiosensitization

Lung cancer is the most common and most fatal cancer worldwide. Thus, improving early diagnosis and therapy is necessary. Previously, gadolinium‐based ultra‐small rigid platforms (USRPs) were developed to serve as multimodal imaging probes and as radiosensitizing agents. In addition, it was demonstrated that USRPs can be detected in the lungs using ultrashort echo‐time magnetic resonance imaging (UTE‐MRI) and fluorescence imaging after intrapulmonary administration in healthy animals. The goal of the present study is to evaluate their theranostic properties in mice with bioluminescent orthotopic lung cancer, after intrapulmonary nebulization or conventional intravenous administration. It is found that lung tumors can be detected non‐invasively using fluorescence tomography or UTE‐MRI after nebulization of USRPs, and this is confirmed by histological analysis of the lung sections. The deposition of USRPs around the tumor nodules is sufficient to generate a radiosensitizing effect when the mice are subjected to a single dose of 10 Gy conventional radiation one day after inhalation (mean survival time of 112 days versus 77 days for irradiated mice without USRPs treatment). No apparent systemic toxicity or induction of inflammation is observed. These results demonstrate the theranostic properties of USRPs for the multimodal detection of lung tumors and improved radiotherapy after nebulization.     

Adaptive Multimodal In‐Vehicle Information System for Safe Driving

This paper proposes an adaptive multimodal in‐vehicle information system for safe driving. The proposed system filters input information based on both the priority assigned to the information and the given driving situation, to effectively manage input information and intelligently provide information to the driver. It then interacts with the driver using an adaptive multimodal interface by considering both the driving workload and the driver's cognitive reaction to the information it provides. It is shown experimentally that the proposed system can promote driver safety and enhance a driver's understanding of the information it provides by filtering the input information. In addition, the system can reduce a driver's workload by selecting an appropriate modality and corresponding level with which to communicate. An analysis of subjective questionnaires regarding the proposed system reveals that more than 85% of the respondents are satisfied with it. The proposed system is expected to provide prioritized information through an easily understood modality.     

Imaging‐Guided Combined Photothermal and Radiotherapy to Treat Subcutaneous and Metastatic Tumors Using Iodine‐131‐Doped Copper Sulfide Nanoparticles

Combining different therapeutic strategies to treat cancer by overcoming limitations of conventional cancer therapies has shown great promise in both fundamental and clinical studies. Herein, by adding ¹³¹I when making iodine‐doped CuS nanoparticles, CuS/[¹³¹I]I nanoparticles are obtained, which after functionalization with polyethylene glycol (PEG) are used for radiotherapy (RT) and photothermal therapy (PTT), by utilizing their intrinsic high near‐infrared absorbance and the doped ¹³¹I‐radioactivity, respectively. The combined RT and PTT based on CuS/[¹³¹I]I‐PEG is then conducted, achieving remarkable synergistic therapeutic effects as demonstrated in the treatment of subcutaneous tumors. In the meanwhile, as revealed by bimodal nuclear imaging and computed tomography (CT) imaging, it is found that CuS/[¹³¹I]I‐PEG nanoparticles after being injected into primary solid tumors could migrate to and retain in their nearby sentinel lymph nodes. Importantly, the combined RT and PTT applied on those lymph nodes to assist surgical resection of primary tumors results in remarkably inhibited cancer metastasis and greatly prolonged animal survival. In vivo toxicology studies further reveal that our CuS/I‐PEG is not obviously toxic to animals at fourfold of the treatment dose. This work thus demonstrates the potential of combining RT and PTT using a single nanoagent for imaging‐guided treatment of metastatic tumors.     

基于改进遗传算法的多式联运网络优化

在对多种运输方式比较分析的基础上,从运输成本、换装成本及时间惩罚成本3个角度,建立多式联运网络模型,采用改进遗传算法进行模型求解,在标准遗传算法基础上引入移民算子,保证了种群多样性,避免了局部最优,增强了算法搜索能力.采用MATLAB计算平台对模型进行案例求解,结果表明,采用多式联运网络运作模型的成本降低了45.8%,从而验证了多式联运网络运作模型的有效性和实用性.     

基于遗传算法的多峰函数优化

目前,对于整体优化问题已经进行了大量理论研究,并提出了许多基于导数的解析方法和其他非解析的数值优化技术。但是,在实际领域中存在着各种高度复杂的优化问题,其目标函数可能表现为非连续或非处处可微、非凸、多峰和带噪声等各种形式,这类复杂优化问题不适合于采用解析方法,同时用传统上的搜索技术求解也会遇到许多困难。针对上述问题,提出利用遗传算法求解多峰函数的优化方法,新方法利用遗传算法的鲁棒性,对多峰函数进行优化,并用Matlab进行仿真,实验结果表明,遗传算法可以快速稳定地搜索到多峰函数的最优解。     

Towards automatic evaluation of multimodal user interfaces

The evaluation of the usability and the learnability of a computer system may be performed with predictive models during the design phase. It may be done on the executable code as well as by observing the user in action. In the latter case, data collected in vivo must be processed. The goal is to provide software supports for performing this difficult and time consuming task.

The paper presents an early analysis of, and experience relating to, the automatic evaluation of multimodal user interfaces. With this end in view, a generic Wizard of Oz platform has been designed to allow the observation and automatic recording of subjects' behavior while they interact with a multimodal interface. It is then shown how recorded data can be analyzed to detect behavioral patterns, and how deviations of such patterns from a data-flow-oriented task model can be exploited by a software usability critic.     

一种多式联运网络运输方式的组合优化模式

针对我国多式联运目前普遍存在的信息化水平不高,缺乏相应的决策支持系统的现状,首先对多种运输方式的运输特性进行了分析,通过对比,得出了运输方式的选择依据;然后建立了多式联运虚拟运输网络;最后在运输方式选择依据和运输网络的基础上得出了多种运输方式组合优化模型,并给出了求解算法。     

Multimodal Interfaces for Cell Phones and Mobile Technology

By modeling users' natural spoken and multimodal communication patterns, more powerful and highly reliable interfaces can be designed that support emerging mobile technology. In this paper, we highlight three different examples of research that is advancing state-of-the-art mobile technology. The first is the development of fusion-based multimodal systems, such as ones that combine speech and pen or touch input, which are substantially improving the robustness and stability of system recognition. The second is modeling of multimodal communication patterns to establish open-microphone engagement techniques that work in challenging multi-person mobile settings. The third is new approaches to adaptive processing, which are able to transparently guide user input to match system processing capabilities. All three research directions are contributing to the design of more reliable, usable, and commercially promising mobile systems of the future.     

基于非均匀采样的多模型红外三维目标跟踪

针对红外三维目标跟踪过程中目标姿态变化导致跟踪器失效的问题,提出了一种基于非均匀采样的多模型方法.首先用若干个原型视图表征三维目标,将这些原型视图对应的原型形状作为目标的多模型形状表示,并建立了这些原型形状之间的转移概率矩阵.在粒子滤波框架下,以对数极坐标变换下的原型视图中目标的灰度分布特征作为参考目标模型.通过对形状转移概率采样,实现了样本形状的转移与传播.此方法提高了跟踪器对于姿态变化的鲁棒性,同时具有非均匀采样特性的对数极坐标变换可以抑制图像尺度、旋转造成的畸变,并起到压缩周边的计算量的作用.仿真结果表明,这种算法对三维目标有较好的跟踪效果.