Developmental and Reproductive Effects of Iron Oxide Nanoparticles in Arabidopsis thaliana

Increasing use of iron oxide nanoparticles in medicine and environmental remediation has led to concerns regarding exposure of these nanoparticles to the public. However, limited studies are available to evaluate their effects on the environment, in particular on plants and food crops. Here, we investigated the effects of positive (PC) and negative (NC) charged iron oxide (Fe₂O₃) nanoparticles (IONPs) on the physiology and reproductive capacity of Arabidopsis thaliana at concentrations of 3 and 25 mg/L. The 3 mg/L treated plants did not show evident effects on seeding and root length. However, the 25 mg/L treatment resulted in reduced seedling (positive-20% and negative-3.6%) and root (positive-48% and negative-negligible) length. Interestingly, treatment with polyethylenimine (PEI; IONP-PC coating) also resulted in reduced root length (39%) but no change was observed with polyacrylic acid (PAA; IONP-NC coating) treatment alone. However, treatment with IONPs at 3 mg/L did lead to an almost 5% increase in aborted pollen, a 2%–6% reduction in pollen viability and up to an 11% reduction in seed yield depending on the number of treatments. Interestingly, the treated plants did not show any observable phenotypic changes in overall size or general plant structure, indicating that environmental nanoparticle contamination could go dangerously unnoticed.     

高温氢工质热物理性质计算分析

氢工质在新能源与动力、航天推进、化工材料等领域有着广泛应用。通过开展高温氢工质热力学与输运性质研究，建立了原子态氢、分子态氢、热解平衡态氢的热物理性质计算模型，开发了热物性计算程序Prop_H_H2，适用范围为温度100~3 500 K、压力104~5×107 Pa 。验证表明，Prop_H_H2在适用范围内计算氢工质的物性参数合理可靠，在温度200~3 000 K、压力104~107 Pa范围内，程序预测值更加准确，相对偏差在±5%左右。本研究可为氢工质相关的航天推进、应用物理学、能源动力等行业的科研和应用提供支持借鉴。     

高瓦斯突出矿井底抽巷一巷多用技术研究与实践

胡底煤业为高瓦斯高突出高矿压的三高矿井。对高瓦斯高突出的治理，该矿采用“地面网络预抽、区域模块降量、底抽穿层保掘、高位顺层保采”的四级模式，施工底抽巷，实现“底抽穿层消突、区域模块降量、异巷探测增效、多巷通风治患、循环排矸减压”等“一巷多用”。该4种方法已在1303（上）、1305（上）工作面应用并推广，取得了良好的效果，大大提高了掘进效率且满足抽放、探放水、通风需要；回填矸石初步设计现已经完善，待下一步掘进将实现填矸作用。     

锚杆锯切设备自动化改造技术应用

通过对锚杆锯切设备的设计、改进情况进行总结，详细介绍了自动化改造前后的设备工作原理、结构组成以及各部分工作过程动作描述等内容，根据改造前后的各项数据统计分析，列出了自动化改造后产品质量、生产效率和企业的利润的变化，同时还有设备故障率、工人劳动强度、设备操作人员数量的减少以及工厂生产环境由污染型转变成节能环保型企业等相关内容，展示所取得的有益效果。     

水热法一步合成磷酸铁锂及其性能研究

为优化液相法一步制备磷酸铁锂（LiFePO₄）技术,以七水合硫酸亚铁、磷酸二氢铵、一水合氢氧化锂为原料,通过添加十二烷基苯磺酸钠（SDBS）作为表面活性剂,采用液相水热法合成技术,一步合成了LiFePO₄正极材料。研究了水热法一步合成技术对LiFePO₄材料的组成、结构、形貌、粒度等的影响,通过电感耦合等离子体发射光谱仪（ICP-OES）、X射线衍射仪（XRD）、扫描电镜（SEM）、粒度分析仪等对材料进行了表征分析,并测试了材料的电化学性能。研究结果表明,合成得到的LiFePO₄材料为微米级球形颗粒形貌的正交晶系非化学计量比的Li_1.02Fe_0.994PO₄材料。电化学性能测试结果表明,在0.1C倍率下首次充、放电比容量分别为162.0、159.9 mA·h/g,库伦效率达到98.7%、倍率性能（以1C/0.1C保持率计）为92.3%,0.1C倍率循环100次容量保持率为96.4%,展现出良好的电化学性能。     

燃料电池空气电极的孔道结构调控

燃料电池是将化学能转化成电能的装置，其空气电极催化层的设计，既要包含丰富的、易于接近的反应活性位，也要具备高度连通的电子、质子以及反应物、产物传质通道，因此电极必须具有特定三维几何结构形貌和有序分布的各功能化孔道，确保催化活性位得以充分利用以及反应可以连续进行。针对催化剂孔道的几何结构调控，本文调研了最近报道的一系列研究工作，从模板法、高温相变法、模板/相变复合方法以及基于金属有机框架材料进行孔道设计等四种主要方法出发，综述了该领域的最新研究进展。     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

一种北斗联合低轨星座的导航增强方法研究

单纯依靠北斗导航系统提供定位导航授时服务,存在卫星信号落地功率低、易受遮蔽和阻断的不足。针对此问题,研究了一种北斗联合低轨星座实现导航增强的系统架构;提出了一种新的适应严重遮蔽或干扰条件下,基于到达时间(TOA)和到达频率(FOA)联合观测的定位解算算法;对高中低轨混合星座条件下的覆盖特性和精度衰减因子进行了仿真分析。分析结果表明,用户可见星数平均增加了64.2%,位置精度衰减因子(PDOP)平均改善了28.7%。研究结果可为下一代北斗的论证设计与研制建设提供参考借鉴。