基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

Ni,Cr, and Fe surfaces corroded by molten ZnCl2

Understanding the corrosion of molten ZnCl₂ on metal surfaces is significant for the corrosion protection of metals, sustainable use of molten salts, preparation of ZnO coatings, and so on. In this paper, surfaces of pure Ni, Cr, and Fe corroded by molten ZnCl₂ were investigated. The results show that Ni suffered very slight corrosion, while Cr experienced more serious corrosion than Ni, but lighter corrosion than Fe. The morphology of the corrosion of Cr and Fe, respectively, presented pitting and intergranular corrosion characteristics. Furthermore, nanostructured ZnO coatings were obtained on the surfaces of Ni and Fe, but not on the surface of Cr. The ZnO coating on the Ni surface was doped with a small amount of Zn₅(OH)₈Cl₂, and the ZnO coating on the Fe surface was doped with ZnFe₂O₄ and Zn₂OCl₂. The coatings on the Ni and Fe surfaces had an average thickness of 1.5 and 50 μm, respectively.     

秸秆微晶纤维素用作片剂崩解剂的初步评价

对实验室自制秸秆微晶纤维素用作片剂崩解剂进行了初步评价。参照《中国药典》(2010版)中微晶纤维素的有关规定,评估自制秸秆微晶纤维素的质量;以阿司匹林为模型药物,以市售微晶纤维素(PH-101)为对照,测定秸秆微晶纤维素的溶胀性、崩解性。结果表明,自制的秸秆微晶纤维素质量符合《中国药典》有关规定,且溶胀性和崩解性优于市售微晶纤维素(PH-101),可用作片剂崩解剂。在秸秆微晶纤维素含量为20%时,崩解速度最快。     

含煤盆地深层“超饱和”煤层气形成条件

中国深层煤层气资源丰富，但总体勘探和认识程度较低，尚未形成较为系统的深层煤层气地质理论。通过解剖分析准噶尔盆地白家海凸起和鄂尔多斯盆地临兴区块深层"超饱和"煤层气井的试气/生产动态，估算原地游离气的含气量，分析了深层"超饱和"煤层气的形成条件。研究表明：①深层"超饱和"煤层气储层中除吸附气外，还含有原地游离气，用常规试气方法可直接获得气流，煤层气的产出不明显依赖于排水降压；②埋藏超过一定深度，在煤阶和温度的综合作用下，煤的吸附能力将随埋深的继续增加而降低，煤层中吸附气的饱和度有增加的趋势，在达到吸附饱和后，出现原地游离气并形成"超饱和"煤层气，盆地深层具有"超饱和"煤层气形成的优势条件；③由于地温梯度和压力梯度的不同，不同盆地"超饱和"煤层气出现的临界深度不同，异常高压和异常高热流可以降低深层"超饱和"煤层气形成的临界深度；④深层"超饱和"煤层气开发具有大大缩短见气时间、充分利用地层能量和累积产水量低等优势，有望成为未来煤层气勘探开发的一个重要领域。     

煤矿工业场地道路照明接地系统问题探讨

文章简要介绍了煤矿工业场地的特点和低压配电系统接地方式分类,从安全性、经济性的角度分析了TN接地系统和TT接地系统在道路照明回路中的优缺点。通过对比TN-S系统与TT系统的接地故障电流差异、TN-S接地系统用于道路照明的等电位联结困难程度,总结出煤矿工业场地的道路照明配电系统适宜采用TT接地方式。并且详细阐述了TT接地系统剩余电流动作保护器保护整定方法和灵敏度校验方法,列举了煤矿工业场地道路照明选用TT系统时需要注意的中性线不可重复接地的问题。     

5-二茂铁基噁唑的合成研究

以二茂铁甲醛和对甲苯磺酰基异氰(TOSMIC)为原料,经过Van Leusen反应,一步合成目标化合物5-二茂铁基噁唑,通过~1HNMR、~(13)CNMR和ESI-MS对其结构进行表征,并对影响收率的主要因素进行考察。结果表明,在物料比n(TOSMIC)∶n(二茂铁甲醛)为1.1∶1、反应溶剂为甲醇、K_2CO_3用量即n(K_2CO_3)∶n(二茂铁甲醛)为2.0∶1、反应温度为65℃、反应时间为8 h的最佳条件下,目标化合物收率达到74.7%。该方法具有原料廉价易得、反应操作简单、收率高等优点,具有一定的应用价值。     

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。