Microenvironment and related genes predict outcomes of patients with cervical cancer: evidence from TCGA and bioinformatic analysis

Cervical cancer (CESC) is one of the most common cancers and affects the female genital tract. Consistent HPV infection status has been determined to be a vital cause of tumorigenesis. HPV infection may induce changes to the immune system and limit the host’s immune response. Immunotherapy is therefore essential to improving the overall survival of both locally advanced and recurrent CESC patients. Using 304 relevant samples from TCGA, we assessed immune cell function in CESC patients to better understand the status of both tumor micro-environment cells and immune cells in CESC. Functional enrichment analysis, pathway enrichment analysis, and PPI network construction were performed to explore the differentially expressed genes (DEGs). The analysis identified 425 DEGs, which included 295 up-regulated genes and 130 down-regulated genes. We established that upregulation of CCL5 was correlated with significantly better survival, meaning that CCL5 expression could serve as a novel prognostic biomarker for CESC patients. We further focused on CCL5 as a hub gene in CESC, as it had significant correlations with increased numbers of several types of immune cells. Cell-type fractions of M1 macrophages were significantly higher in the high-immune-scores group, which was associated with better overall survival. Finally, we concluded that CCL5 is a promising prognostic biomarker for CESC, as well as a novel chemotherapeutic target.     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。     

曲沃县水资源开发利用现状及对策

文中对曲沃县水资源开发利用现状进行了认真分析，并从思想观念、管理体制、管理模式上提出了问题，为解决问题提出了相应对策。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

氯甲烷在镁修饰的ZSM-5分子筛催化剂上催化转化研究

在镁修饰的ZSM-5分子筛催化剂上,氯甲烷可以被催化转化为烃类产品。分别采用了离子交换和浸渍的方法来修饰ZSM-5分子筛。离子交换的Mg-ZSM-5催化剂和浸渍的Mg/ZSM-5催化剂都可以提高反应产物中的低碳烯烃的选择性,降低烷烃的选择性,并且保持较高的反应活性,但高的浸渍量对反应活性有一定的影响。NH3-TPD的结果表明,浸渍镁的ZSM-5催化剂的强酸中心数目明显减少。镁的修饰对催化剂酸性的影响导致了产物中低碳烯烃的增加。浸渍Mg的ZSM-5催化剂是潜在氯甲烷转化生成低碳烯烃的催化剂。     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

从频谱监测和国际协调探讨短波广播频段扩展的可行性

短波广播能够实现远距离和大范围的覆盖，至今仍是进行地区性、全国性及国际性广播覆盖的最好手段之一。ITU在2001年4月批准的1514建议书《30MHz以下广播频段的数字声音广播系统》，正式确定了DRM系统为全球统一的数字广播系统。在短波广播由模拟向数字化过渡的进程中，如何解决短波广播频谱短缺的问题，本文根据国家相关的频谱监测和国际短波频率协调的情况，对短波广播中4～10MHz频谱的扩展可行性进行初步分析。