共享自动驾驶汽车使用意愿模型及其影响因素

为了构建共享自动驾驶汽车(shared autonomous vehicles，SAV) 的使用意愿模型并分析其影响因素，通过使用时机和使用频率来体现公众对SAV的使用意愿；采用验证性因子分析将态度潜变量转化为潜变量得分，以此将态度潜变量引入传统的有序Logit模型；提出SAV使用意愿的有序Logit模型构建方法，并建立基于个人属性、通勤特征、态度潜变量的SAV使用意愿模型.研究发现:是否使用过滴滴拼车、工作单位停车费、自动驾驶态度对使用时机和3种价格(1，2，3元/km) 下的使用频率有显著影响；使用过滴滴拼车、工作单位收取停车费、支持自动驾驶的群体倾向于频繁地、更早地使用SAV出行；公众期望以1元/km或 2元/km即不超过目前滴滴拼车的价格使用SAV.     

一种基于类不平衡学习的情感分析方法

针对网络评论中普遍存在的负面评论较少而影响力却较大的类不平衡问题, 提出一种基于类不平衡学习的情感分析方法. 该方法利用深度学习训练过程中的概率输出, 以计算样例的信息熵作为影响因子构建交叉信息熵损失函数. 在IMDB公开数据集上进行实验验证的结果表明, 基于集成信息熵损失函数的双向长短期记忆网络能处理类不平衡问题; 对数据的统计分析结果表明, 该策略能提升基于双向长短期记忆网络的评论情感极性分类性能. 针对AUC(area under curve)指标, 使用集成信息熵损失函数的双向长短期记忆网络模型比未考虑类不平衡的深度学习模型在中位数上最多提升15.3%.     

Blockage of the NLRP3 inflammasome by MCC950 improves anti-tumor immune responses in head and neck squamous cell carcinoma

The NLRP3 inflammasome is a critical innate immune pathway responsible for producing active interleukin (IL)-1β, which is associated with tumor development and immunity. However, the mechanisms regulating the inflammatory microenvironment, tumorigenesis and tumor immunity are unclear. Herein, we show that the NLRP3 inflammasome was over-expressed in human HNSCC tissues and that the IL-1β concentration was increased in the peripheral blood of HNSCC patients. Additionally, elevated NLRP3 inflammasome levels were detected in tumor tissues of Tgfbr1/Pten 2cKO HNSCC mice, and elevated IL-1β levels were detected in the peripheral blood serum, spleen, draining lymph nodes and tumor tissues. Blocking NLRP3 inflammasome activation using MCC950 remarkably reduced IL-1β production in an HNSCC mouse model and reduced the numbers of myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs) and tumor-associated macrophages (TAMs). Moreover, inhibiting NLRP3 inflammasome activation increased the numbers of CD4⁺ and CD8⁺ T cells in HNSCC mice. Notably, the numbers of exhausted PD-1⁺ and Tim3⁺ T cells were significantly reduced. A human HNSCC tissue microarray showed that NLRP3 inflammasome expression was correlated with the expression of CD8 and CD4, the Treg marker Foxp3, the MDSC markers CD11b and CD33, and the TAM markers CD68 and CD163, PD-1 and Tim3. Overall, our results demonstrate that the NLRP3 inflammasome/IL-1β pathway promotes tumorigenesis in HNSCC and inactivation of this pathway delays tumor growth, accompanied by decreased immunosuppressive cell accumulation and an increased number of effector T cells. Thus, inhibition of the tumor microenvironment through the NLRP3 inflammasome/IL-1β pathway may provide a novel approach for HNSCC therapy.     

General mechanisms of drought response and their application in drought resistance improvement in plants

Plants often encounter unfavorable environmental conditions because of their sessile lifestyle. These adverse factors greatly affect the geographic distribution of plants, as well as their growth and productivity. Drought stress is one of the premier limitations to global agricultural production due to the complexity of the water-limiting environment and changing climate. Plants have evolved a series of mechanisms at the morphological, physiological, biochemical, cellular, and molecular levels to overcome water deficit or drought stress conditions. The drought resistance of plants can be divided into four basic types-drought avoidance, drought tolerance, drought escape, and drought recovery. Various drought-related traits, including root traits, leaf traits, osmotic adjustment capabilities, water potential, ABA content, and stability of the cell membrane, have been used as indicators to evaluate the drought resistance of plants. In the last decade, scientists have investigated the genetic and molecular mechanisms of drought resistance to enhance the drought resistance of various crops, and significant progress has been made with regard to drought avoidance and drought tolerance. With increasing knowledge to comprehensively decipher the complicated mechanisms of drought resistance in model plants, it still remains an enormous challenge to develop water-saving and drought-resistant crops to cope with the water shortage and increasing demand for food production in the future.     

利用SRTM数据修测高山区地貌的探讨

在高海拔区域测制地形图,如青藏高原地区,所获取的遥感影像局部存在着大范围的高山阴影或云雪覆盖,造成立体观测地貌困难的现象,探讨应用SRTM数据对这类特殊区域地貌进行修测补绘。介绍了数据处理的作业过程,并对实验区SRTM与SPOT5影像立体测图成果进行实验对比分析,成果符合要求。     

迹为整数的3×3阶正交矩阵的谱

讨论了3×3阶正交矩阵的特征值和迹的关系,证明了迹为整数的3×3阶正交矩阵的谱可由迹确定,为应用广泛的3×3阶正交矩阵的谱的计算提供了简单实用的方法.     

基于高斯字典原子稀疏表示的高精度宽角SAR成像方法

为了提高从宽角合成孔径雷达(synthetic aperture radar, SAR)图像中提取目标后向散射各向异性特性的性能,在宽角SAR字典稀疏表示模型的基础上,提出一种基于高斯字典原子的高精度宽角SAR成像方法。在字典构造上,采用不同中心位置、相同方差的高斯函数。在求解稀疏表示系数上,采用广义最小最大凹惩罚稀疏重构算法求解。最后，根据稀疏表示系数的重构结果以及构造的字典得到目标的后向散射各向异性特性。通过仿真实验和Backhoe数据对算法进行验证,结果表明,该方法能够高精度地提取目标的后向散射各向异性特性。     

红树林保护与修复标准发展现状及对策

回顾近20年来中国对红树林的保护以及通过人工造林进行恢复的情况, 梳理我国红树林保护与修复的相关标准, 厘清现行标准存在的问题, 提出如下相应的建议与对策。1) 应结合国家碳中和战略及红树林保护与恢复规划目标, 制定完善的红树林保护与生态修复技术标准体系规划, 加快相关国家标准的出台; 2) 在编制红树林保护与修复相关标准的同时, 应注重红树林固碳能力和增汇效应的提高; 3) 建议制定退塘还林相关标准, 填补国内空白; 4) 应充分落实“自然恢复为主、人工修复为辅”的生态修复原则, 重视并加强红树林保护与修复标准的技术细节制定; 5) 标准的制定和实施应由红树林研究专业机构及专家深度参与, 提高造林成活率。     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.     

Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.