基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

陕北风沙滩区浅层地下水环境演化和发展趋势

陕北风沙滩区生态脆弱,但在风沙滩区及周边人类大量的活动,使该区域地下水环境发生了很大变化.利用风沙滩区浅层长系列地下水观测数据,结合区域水文地质条件,从内外动力地质和人为活动共同作用来分析浅层地下水赋存空间环境演化规律,预测发展趋势.完成了对浅层地下水环境多角度多层次演化的分析,并从风沙滩区植被、降落漏斗、海子面积、水质等多方面进行了发展趋势预测.得出陕北风沙滩区浅层地下水环境在人为破坏和人为保护双向发力下,向相反的方向演化,并表现出时好时坏.总之在人为破坏没有停止之前,人为保护虽有作用,但不治本.     

Indoor solid fuel use for heating and cooking with blood pressure and hypertension: A cross-sectional study among middle-aged and older adults in China

A cross-sectional study was conducted to investigate the impact of solid fuel use for heating and cooking on blood pressure (BP) and hypertension, using data from the China Health and Retirement Longitudinal Study (CHARLS). The primary fuels used for indoor heating and cooking were collected by questionnaires, respectively. Hypertension was defined based on self-report of physician's diagnosis, and/or measured BP, and/or anti-hypertensive medication use. Multivariate logistic regression models were constructed to assess the associations. Among 10 450 eligible participants, 68.2% and 57.2% used indoor solid fuel for heating and cooking, respectively. Compared with none/clean fuel users, solid fuel for heating was associated with elevated BP (adjusted β: 2.02, 95% CI: 1.04–3.01 for systolic BP; adjusted β: 1.36, 95% CI: 0.78–1.94 for diastolic BP) and increased risk of hypertension (adjusted odds ratio: 1.15, 95% CI: 1.03–1.29). The impact of indoor solid fuel for heating on BP was more evident in rural and north residents, and hypertensive patients. We did not detect any significant associations between solid fuel use for cooking and BP/hypertension. Indoor solid fuel use is prevalent in China, especially in the rural areas. Its negative impact on BP suggested that modernization of household fuel use may help to reduce the burden of hypertension in China.     

Preparation and characterization of calcium phosphate cement with enhanced tissue adhesion for bone defect repair

Anti-washout and tissue adhesion properties are essential for the clinical application of injectable bone materials. In this study, we prepared calcium phosphate cement (CPC) with anti-washout and tissue adhesion properties and attempted to build covalent bonds between CPC and the amino groups in bone tissue under a self-regulating pH system in the CPC (acidic to basic). The results of push-out tests demonstrated that a significant enhancement (from 6.42 ± 0.76 N to 61.5 ± 4.09 N) in tissue adhesion was obtained with the addition of 6% (w/w) oxidized sodium alginate (OSA) in CPC. The FTIR, XRD, anti-washout test, XPS, pH test, and SEM results suggested that the synergistic effect of OSA-citric acid (CA) led to the formation of a three-dimensional gel network structure in the CPC, and the Schiff base reaction between aldehyde and amino groups induced adhesion between CPC and the bone tissue. Further, the addition of less OSA had no significant negative effect on the hydration properties of CPC. Our work aims to promote the development of injectable bone material in clinical applications.     

高光谱激光雷达谱位合一的角度效应分析

高光谱激光雷达以其谱位合一的技术优势为实现超三维精准遥感观测提供了可行途径,因此成为当前激光雷达与高光谱遥感领域共同大力推进的前沿发展方向。目前已有多型原型系统研发出来并得到了原理性验证,然而针对其数据处理核心环节问题的基础技术仍较为欠缺。典型问题之一是不同波段回波信号受激光入射角度的影响,该角度效应限制了高光谱激光雷达实现高性能遥感。以芬兰空间信息研究所高光谱激光雷达原型系统扫描桦树树干为例探讨了该角度效应,发现了不同激光波段对不同入射角度的回波强度响应模式,推导出了角度效应的基本规律及其精细尺度的统计规律,为后续该方向的系统研发、数据处理及信息提取等提供了可借鉴的底层机理与技术基础。     

井工转露天采区顶板厚度不足诱发滑坡问题研究

井工转露天开采是安全生产遇到的新问题。以紫金山金铜矿为背景，利用数值模拟法系 统研究了井 工转露天开采工况下顶板厚度从 68 m 逐渐减小至 44 m 时顶板的安全性，界定出顶板最小安 全厚度为 45 m。同时 系统研究了顶板厚度变化对上部边坡应力场的影响特点，得出随着顶板变薄坡脚处塑性破坏区 增大，导致边坡稳 定性变小的规律，并通过边坡稳定性分析计算验证其正确性。因此在井工转露天开采过程中， 为了确保安全生产 需要确保顶板有足够的厚度，避免作业设备和工作人员坠入老井采区及滑坡灾害发生。     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.