高效液相色谱-离子阱质谱法测定海洋微藻藻粉中的8种脂溶性毒素

建立了利用高效液相色谱-电喷雾离子阱质谱(HPLC-ESI-IT-MS)测定海洋微藻藻粉中8种典型脂溶性毒素的分析方法。藻粉样品经超声细胞破碎后,采用超声波辅助提取法对藻毒素进行提取,用HPLC-ESI-IT-MS多反应离子监测(MRM)模式对各种毒素(包括大田软海绵酸(OA)、鳍藻毒素1(DTX-1)、扇贝毒素2(PTX-2)、虾夷扇贝毒素(YTX)、原多甲藻酸1(AZA1)原多甲藻酸2(AZA2)、罗环内酯毒素(SPX),米氏裸甲藻毒素(GYM))进行测定。8种脂溶性藻毒素均在线性范围内线性关系良好(R2均在0.991以上),检出限均介于0.085～1.315 pg之间,加标回收率在88.5%～111.4%之间,方法重复性相对标准偏差(RSD)在4.82%～10.17%范围。应用该方法对利玛原甲藻干藻粉中的毒素进行了测定,分析结果良好,说明本方法是海洋微藻藻粉中脂溶性藻毒素测定的有效方法。     

MatDEM-fast matrix computing of the discrete element method

Discrete element method can effectively simulate the discontinuity, inhomogeneity and large deformation and failure of rock and soil. Based on the innovative matrix computing of the discrete element method, the high-performance discrete element software MatDEM may handle millions of elements in one computer, and enables the discrete element simulation at the engineering scale. It supports heat calculation, multi-field and fluid-solid coupling numerical simulations. Furthermore, the software integrates pre-processing, solver, post-processing, and powerful secondary development, allowing recompiling new discrete element software. The basic principles of the DEM, the implement and development of the MatDEM software, and its applications are introduced in this paper. The software and sample source code are available online (http://matdem.com).     

一种基于天基的瞬变电磁高分辨探测小尺度太空碎片的方法

目前,太空碎片的天基探测方法一般是激光雷达法.由于激光雷达的辐射频率一般为可见光或红外波段,在分辨厘米量级的太空碎片时具有一定的优势.但激光雷达在探测时也面临一些客观问题：即（1）难以捕捉快速移动的太空碎片;（2）对目标体穿透能力低;（3）外层空间的强干扰环境对激光雷达的不良影响等.这些问题在一定程度上限制了激光雷达在太空碎片探测方面的应用.本文针对太空碎片体积小、预警距离远和强干扰环境等特点,提出使用高性能瞬变电磁辐射源对远距离、小尺度的太空碎片进行探测.通过三维矢量有限元方法,分析了利用高性能瞬变电磁辐射源的优点,对比不同瞬变电磁辐射源的幅频特性,从发射机理上证明高性能瞬变电磁辐射源在辐射能力与频率带宽方面都优于传统瞬变电磁辐射源.并通过调整脉冲宽度,得到最适合探测本文太空碎片模型的辐射脉冲.最后通过电场分布图和多测道图对太空碎片的明显电场分异结果,证实了高性能瞬变电磁辐射源在探测远距离、小尺度太空碎片方面的有效性.     

gLucifer: next generation visualization framework for high-performance computational geodynamics

High-performance computing provides unprecedented capabilities to produce higher resolution 4-D models in a fraction of time. Thus, the need exists for a new generation of visualization systems able to maintain parity with the enormous volume of data generated. In attempting to write this much data to disk, each computational step introduces a significant performance bottleneck, yet most existing visualization software packages inherently rely on reading data in from a dump file. Available packages make this assumption of postprocessing at quite a fundamental level and are not very well suited for plotting very large numbers of specialized particles. This necessitates the creation of a new visualization system that meets the needs of large-scale geodynamic modeling. We have developed such a system, gLucifer, using a software framework approach that allows efficient reuse of our efforts in other areas of research. gLucifer is capable of producing movies of a 4-D data set “on the fly” (simultaneously with running the parallel scientific application) without creating a performance bottleneck. By eliminating most of the human efforts involved in visualizing results through postprocessing, gLucifer reconnects the scientist to the numerical experiment as it unfolds. Data sets that were previously very difficult to even manage may be efficiently explored and interrogated without writing to disk, and because this approach is based entirely on memory distributed across as many processors as are being utilized by the scientific application, the visualization solution is scalable into terabytes of data being rendered in real time.     

High-performance computing strategies for seismic-imaging software on the cluster and cloud-computing environments

Modern subsurface imaging techniques allow obtaining high-quality images but with high computational costs. Nonetheless, depending on the amount of data, their execution is limited by memory in the current generation's hardware. However, with the advancement of new hardware and cloud-based solutions, these problems are mitigated but still with the risk of work loss and instability. To mitigate the execution problems in memory-limited and fail-prone environments, we propose two high-performance computing techniques. The first is based on independent checkpointing alongside a fault-tolerant framework to store an execution state and recover from that state in case of failures. Besides, for memory-limited graphics processing units, we present a technique to reduce the amount of memory requirement that we call the hybrid strategy. The experiments showed that the independent checkpointing alongside the fault-tolerant framework is able to mitigate the performance penalty of node failures, with the independent checkpointing technique being more relevant when multiple nodes are terminated. Furthermore, the hybrid strategy technique has shown the possibility of execution of larger models that could make the graphics processing unit run out of memory otherwise. Finally, our implementation is scalable, allowing a significant improvement in performance when adding new nodes. In conclusion, our techniques can be used to deliver fast, high-fidelity subsurface imaging in unstable and memory-limited environments, such as the cloud.     

高效地图缓存分包封装技术研究与实现

论述了一种高性能的地图缓存的分包封装技术。通过高效的算法,将大数据量的缓存瓦片封装为多个独立缓存瓦片包。并通过多线程等并行技术,有效地提升了缓存的生成效率,加快缓存的读取速度,降低缓存分发、部署难度。该技术较好地解决了大数据量下缓存数据存储复杂性的问题。     

黄酮类化合物分析方法概述

主要综述了黄酮类化合物的分析方法。重点介绍了分光光度法、平面色谱法、高效液相色谱法、超临界流体色谱法、高效毛细管电泳法、极谱法、色谱—质谱联用技术。     

地震预测重点实验室高性能计算平台计费服务系统的设计与实现

本文简要回顾了高性能计算在地震研究中的应用,介绍了中国地震局地震预测重点实验室高性能计算平台及其应用情况,并指出作业计费的必要性。其次,详细介绍了1种高性能计算平台计费服务系统的设计与实现。该系统基于TORQUE和LSF集群作业管理系统日志信息的分析处理,具备作业查询、作业统计、作业计费、作业预约、信息管理、留言管理等功能,有益于解决高性能计算平台计算收费和运维支出平衡的问题,提高了平台的透明度和利用率,促进信息共享和技术交流,并具有较好的扩展性和应用前景。最后,对高性能计算过渡到高性能云计算进行了展望。     

基于高性能瞬变电磁辐射源的城市地下空间多分辨成像方法研究

城市地下空间的高精度、多分辨探测是城市地下合理开发的前提.由于城市探测环境的特殊性,需要探测方法具备抗干扰能力强、分辨能力好、分异多尺度地下目标等特性,现有的物探方法难以兼顾城市地下空间的探测需要.本文利用三维矢量有限元方法为正演手段,在瞬变电磁高性能辐射源进行微分脉冲扫描的基础上,对探测数据进行多时窗的扫时波场变换,将微分脉冲扫描后的多分辨响应信息,进行多分辨信息提取.同时通过地震探测中的多次覆盖处理,提高探测场对地下目标的分辨能力,最后对多次叠加后的虚拟波场进行拟地震偏移成像,最终实现城市地下空间的高精度探测.     

Application of HPC and big data in post-pandemic times

We lay out the ramifications of the 2020 pandemic for all people in geosciences, especially the young, and argue for significant changes on training and career development. We focus primarily on its devastating impact in USA and compare with that in other countries especially China. We review the potential effect for the next four years or so on the aspirations of an academic career versus more realistic career goals. We urge people in mid-career about the need to reassess previous goals. We stress the need for students or researchers to acquire technical skills in high-performance computing (HPC), data analytics, artificial intelligence, and/or visualization along with a broad set of technical skills in applied computer science and mathematics. We give advice about hot prospects in several areas that have great potential for advancement in the coming decade, such as visualization, deep learning, quantum computing and information, and cloud computing, all of which lie within the aegis of HPC. Our forecast is that the pandemic will significantly reshape the job landscape and career paths for both young and established researchers and we discuss bluntly the dire situation facing junior people in geosciences in the aftermath of the pandemic around the world until 2024.