The use of the scanning electron microscope in the determination of the mineral composition of Ballachulish slate

Slate is a fine-grained, low-grade metamorphic rock derived from argillaceous sediments or occasionally volcanic ash. Although most slates contain mainly quartz, chlorite and white mica, they vary considerably in their durability, some lasting centuries while others fail after a few years of service. A detailed characterisation of their mineralogy is required for the assessment of performance, and to establish the provenance of a used slate. A combination of methods was used to examine Ballachulish slates; XRD analysis to determine the principal minerals present, XRF analysis to determine the total chemical composition, and scanning electron microscopy to determine the chemical composition of individual minerals. It was found that the white mica in Ballachulish slate is phengite and the chlorite is ripidolite. Feldspar is present as albite and carbonate as ferroan dolomite. Several accessory minerals were also identified, including chloritoid, monzonite and zircon. There was considerable variation in the ratio of the principal minerals, making it impossible to identify used slates by this criterion. Instead, chemical composition of the individual minerals, and possibly key accessory minerals, should be used to determine the provenance of slates.     

日照苏家村遗址出土钱山漾文化陶鬶的产地研究

日照苏家村遗址位于鲁东南沿海地区,是大汶口文化晚期至龙山文化早中期一处重要的环濠聚落。该遗址新出土的钱山漾文化细长颈袋足鬶(M45:5)作为目前已知南方系陶鬶布最北的一件,揭示出公元前2300年前后中国南北方的区域文化交流。本文通过对苏家村出土钱山漾文化红陶鬶、其他龙山文化红陶鬶及部分苏家村黑陶的主、微量元素分析,结合主成分分析揭示了苏家村本地生产钱山漾文化红陶鬶的可能性,表明龙山文化早中期的制陶业的发展可能伴随着南方系制陶工匠的迁徙。     

基于数据世系的微博信息管理与检索算法研究

在微博平台中用户的消息以流的形式按照时间顺序到达系统,对微博数据流的有效管理可以及时地响应用户的查询操作。基于数据库的数据世系思想,提出了一种基于数据世系的微博信息管理方法。首先,根据事件的产生、发展以及变化,将同一社会事件包含的消息定义为数据世系;其次,将微博消息流划分为不同的数据世系,并根据新消息动态地维护数据世系集合;最后,应用数据世系中的文本消息响应用户的查询。实验表明,基于数据世系的微博信息管理方法使用的内存少,运行效率高,可用于微博消息流的实时处理及查询响应工作。     

Digital provenance: Enabling secure data forensics in cloud computing

Secure provenance that records the ownership and process history of data objects is vital to the success of data forensics in cloud computing. In this paper, we propose a new secure provenance scheme based on group signature and attribute-based signature techniques. The proposed provenance scheme provides confidentiality on sensitive documents stored in a cloud, unforgeability of the provenance record, anonymous authentication to cloud servers, fine-grained access control on documents, and provenance tracking on disputed documents. Furthermore, it is assumed that the cloud server has huge computation capacity, while users are regarded as devices with low computation capability. Aiming at this, we show how to utilize the cloud server to outsource and decrease the user’s computational overhead during the process of provenance. With provable security techniques, we formally demonstrate the security of the proposed scheme under standard assumptions.     

Linking open data and the crowd for real-time passenger information

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.     

Visualization workflows for level-12 HUC scales: Towards an expert system for watershed analysis in a distributed computing environment

Visualization workflows are important services for expert users to analyze watersheds when using our HydroTerre end-to-end workflows. Analysis is an interactive and iterative process and we demonstrate that the expert user can focus on model results, not data preparation, by using a web application to rapidly create, tune, and calibrate hydrological models anywhere in the continental USA (CONUS). The HydroTerre system captures user interaction for provenance and reproducibility to share modeling strategies with modelers. Our end-to-end workflow consists of four workflows. The first is data workflows using Essential Terrestrial Variables (ETV) data sets that we demonstrated to construct watershed models anywhere in the CONUS (Leonard and Duffy, 2013). The second is data-model workflows that transform the data workflow results to model inputs. The model inputs are consumed in the third workflow, model workflows (Leonard and Duffy, 2014a) that handle distribution of data and model within High Performance Computing (HPC) environments. This article focuses on our fourth workflow, visualization workflows, which consume the first three workflows to form an end-to-end system to create and share hydrological model results efficiently for analysis and peer review. We show how visualization workflows are incorporated into the HydroTerre infrastructure design and demonstrate the efficiency and robustness for an expert modeler to produce, analyze, and share new hydrological models using CONUS national datasets.     

Domain-specific summarization of Life-Science e-experiments from provenance traces

Translational research in Life-Science nowadays leverages e-Science platforms to analyze and produce huge amounts of data. With the unprecedented growth of Life-Science data repositories, identifying relevant data for analysis becomes increasingly difficult. The instrumentation of e-Science platforms with provenance tracking techniques provides useful information from a data analysis process design or debugging perspective. However raw provenance traces are too massive and too generic to facilitate the scientific interpretation of data. In this paper, we propose an integrated approach in which Life-Science knowledge is (i) captured through domain ontologies and linked to Life-Science data analysis tools, and (ii) propagated through rules to produced data, in order to constitute human-tractable experiment summaries. Our approach has been implemented in the Virtual Imaging Platform (VIP) and experimental results show the feasibility of producing few domain-specific statements which opens new data sharing and repurposing opportunities in line with Linked Data initiatives.     

Provenance studies of archaeological ceramics from Mar-Takla(Ain-Minin,Syria)using radioisotope X-ray fluorescence method

The radioisotope X-ray fluorescence method was applied to studies of the provenance of the ceramics fragments originated from the Mar-Takla site in Syria.The samples were irradiated 1000s by a ^109Cd radioisotope source and 13 elements (Ca,Ti,Mn,Fe,Zn,Ga,As,Rb,Sr,Y,Zr,Nb,and Pb)were determined in 35 samples.The data were subjected to two multivariate statistical methods,cluster and principal components analysis(PCA).It was shown from the combination of the statistical techniques and the determination of elemental composition of the samples that 94% of the ceramic samples analyzed can be considered to be manufactured using two sources of raw materials.     

Evaluation of elemental profile coupled to chemometrics to assess the geographical origin of Argentinean wines

Traceability of wines requires knowledge of their characteristics, which are associated with the geographical origin of grape, soil, water, climate as well as the winery techniques. The aim of this work was to classify wines and soil from three production areas of Argentina according to multielement data. The influence of the provenance soil on the wine element composition was also investigated.Eleven elements were determined in 31 wine samples and 137 soil samples from regions under study. Stepwise discriminant analysis allows us to correctly classify 100% of the wines analysed from the three regions using only seven parameters (K, Fe, Ca, Cr, Mg, Zn and Mn) and 92% correct classification for soils using seven variables (Ca, Cr, K, Fe, Cu, Zn and, Mg). Canonical analysis between soils and wines datasets affords a correlation coefficient of 0.85 (P-value < 0.001). Thus, almost 85% of variability observed amongst wines could be attributed to the soil in which the vines were cultivated.The analysis of elemental concentrations in the wines and soils, in combination with chemometrics, provides a powerful tool to verify the geographical origin of wines.     

铁边城地区长4+5油组重矿物特征及物源分析

铁边城地区延长组长4+5油组常见的重矿物有锆石、电气石、石榴石和白钛矿,依据重矿物的形貌特征及稳定性的平面变化趋势,可将它们自北东到西南划分为3个组合分带:石榴石+锆石+电气石、锆石+石榴石+电气石、锆石+电气石。重矿物组合特征及碎屑岩组分特征在平面上的变化趋势,表明北东方向为铁边城地区的主要物源区。石英的阴极发光特征表明研究区的母岩主要为中—低级变质岩系,说明北东方向的吕梁山和大青山区为该区的主要供屑区。