Ordered mixed-layer structures in the Mighei carbonaceous chondrite matrix

High resolution transmission electron microscopy of the Mighei carbonaceous chondrite matrix has revealed the presence of a new mixed layer structure material. This mixed-layer material consists of an ordered arrangement of serpentine-type (S) and brucite-type (B) layers in the sequence ... SBBSBB. ... Electron diffraction and imaging techniques show that the basal periodicity is ~ 17 Å. Discrete crystals of SBB-type material are typically curved, of small size (<1 μm) and show structural variations similar to the serpentine group minerals. Mixed-layer material also occurs in association with planar serpentine. Characteristics of SBB-type material are not consistent with known terrestrial mixed-layer clay minerals. Evidence for formation by a condensation event or by subsequent alteration of preexisting material is not yet apparent. © 1982.

New phyllosilicate types in a carbonaceous chondrite matrix

CARBONACEOUS chondrites provide valuable information as they are the least altered examples of early Solar System material1. The matrix constitutes a major proportion of carbonaceous chondrites. Despite many past attempts, unambiguous identification of the minerals in the matrix has not been totally successful2. This is mainly due to the extremely fine-grained nature of the matrix phases. Recently, progress in the characterisation of these phases has been made by electron diffraction studies3,4. We present here the direct observation, by high resolution imaging, of phases in carbonaceous chondrite matrices. We used ion-thinned sections from the Murchison C2(M) meteorite for transmission electron microscopy. The Murchison matrix contains both ordered and disordered inter-growths of serpentine-like and brucite-like layers. Such mixed-layer structures are new types of layer silicates. © 1979 Nature Publishing Group.

Using patterns co-occurrence matrix for cleaning closed sequential patterns for text mining

With the overwhelming increase in the amount of texts on the web, it is almost impossible for people to keep abreast of up-to-date information. Text mining is a process by which interesting information is derived from text through the discovery of patterns and trends. Text mining algorithms are used to guarantee the quality of extracted knowledge. However, the extracted patterns using text or data mining algorithms or methods leads to noisy patterns and inconsistency. Thus, different challenges arise, such as the question of how to understand these patterns, whether the model that has been used is suitable, and if all the patterns that have been extracted are relevant. Furthermore, the research raises the question of how to give a correct weight to the extracted knowledge. To address these issues, this paper presents a text post-processing method, which uses a pattern co-occurrence matrix to find the relation between extracted patterns in order to reduce noisy patterns. The main objective of this paper is not only reducing the number of closed sequential patterns, but also improving the performance of pattern mining as well. The experimental results on Reuters Corpus Volume 1 data collection and TREC filtering topics show that the proposed method is promising.

A preconditioned Lanczos method for space-fractional reaction-diffusion equations on two-dimensional unstructured meshes

We consider a two-dimensional space-fractional reaction diffusion equation with a fractional Laplacian operator and homogeneous Neumann boundary conditions. The finite volume method is used with the matrix transfer technique of Ilić et al. (2006) to discretise in space, yielding a system of equations that requires the action of a matrix function to solve at each timestep. Rather than form this matrix function explicitly, we use Krylov subspace techniques to approximate the action of this matrix function. Specifically, we apply the Lanczos method, after a suitable transformation of the problem to recover symmetry. To improve the convergence of this method, we utilise a preconditioner that deflates the smallest eigenvalues from the spectrum. We demonstrate the efficiency of our approach for a fractional Fisher’s equation on the unit disk.

The digital transformation of 21st century news journalism

This paper deals with the transformations that have occurred in news journalism worldwide in the early 21st century. I argue that they havebeen the most significant changes to the profession for 100 years, and the challenges facing the news media industry in responding to them are substantial, as are those facing journalism education. This argument is developed in relation to the crisis of the newspaper business model, and why social media, blogging and citizen journalism have not filled the gap left by the withdrawal of resources from traditional journalism. It also draws upon Wikileaks as a case study in debates about computational and data-driven journalism, and whether large-scale "leaks" of electronic documents may be the future of investigative journalism.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

One-stop government portals : transformation or navigation?

E-government is seen as a promising approach for governments to improve their service towards citizens and become more cost-efficient in service delivery. This is often combined with one-stop government, which is a citizen-oriented approach stressing integrated provision of services from multiple departments via a single access point, the one-stop government portal. While the portal concept is gaining prominence in practice, there is little know about its status in academic literature. This hinders academics in building an accumulated body of knowledge around the concept and makes it hard for practitioners to access relevant academic insights on the topic. The objective of this study is to identify and understand the key themes of the one-stop government portal concept in academic, e-government research. A holistic analysis is provided by addressing different viewpoints: social-political, legal, organizational, user, security, service, data & information, and technical. As overall finding we conclude that there are two different approaches: a more pragmatic approach focuses on quick wins in particular related to usability and navigation and a more ambitious, transformational approach having far reaching social-political, legal, organizational implications.

Damage assessment in reinforced concrete flexural members using modal strain energy based method

Damage assessment (damage detection, localization and quantification) in structures and appropriate retrofitting will enable the safe and efficient function of the structures. In this context, many Vibration Based Damage Identification Techniques (VBDIT) have emerged with potential for accurate damage assessment. VBDITs have achieved significant research interest in recent years, mainly due to their non-destructive nature and ability to assess inaccessible and invisible damage locations. Damage Index (DI) methods are also vibration based, but they are not based on the structural model. DI methods are fast and inexpensive compared to the model-based methods and have the ability to automate the damage detection process. DI method analyses the change in vibration response of the structure between two states so that the damage can be identified. Extensive research has been carried out to apply the DI method to assess damage in steel structures. Comparatively, there has been very little research interest in the use of DI methods to assess damage in Reinforced Concrete (RC) structures due to the complexity of simulating the predominant damage type, the flexural crack. Flexural cracks in RC beams distribute non- linearly and propagate along all directions. Secondary cracks extend more rapidly along the longitudinal and transverse directions of a RC structure than propagation of existing cracks in the depth direction due to stress distribution caused by the tensile reinforcement. Simplified damage simulation techniques (such as reductions in the modulus or section depth or use of rotational spring elements) that have been extensively used with research on steel structures, cannot be applied to simulate flexural cracks in RC elements. This highlights a big gap in knowledge and as a consequence VBDITs have not been successfully applied to damage assessment in RC structures. This research will address the above gap in knowledge and will develop and apply a modal strain energy based DI method to assess damage in RC flexural members. Firstly, this research evaluated different damage simulation techniques and recommended an appropriate technique to simulate the post cracking behaviour of RC structures. The ABAQUS finite element package was used throughout the study with properly validated material models. The damaged plasticity model was recommended as the method which can correctly simulate the post cracking behaviour of RC structures and was used in the rest of this study. Four different forms of Modal Strain Energy based Damage Indices (MSEDIs) were proposed to improve the damage assessment capability by minimising the numbers and intensities of false alarms. The developed MSEDIs were then used to automate the damage detection process by incorporating programmable algorithms. The developed algorithms have the ability to identify common issues associated with the vibration properties such as mode shifting and phase change. To minimise the effect of noise on the DI calculation process, this research proposed a sequential order of curve fitting technique. Finally, a statistical based damage assessment scheme was proposed to enhance the reliability of the damage assessment results. The proposed techniques were applied to locate damage in RC beams and slabs on girder bridge model to demonstrate their accuracy and efficiency. The outcomes of this research will make a significant contribution to the technical knowledge of VBDIT and will enhance the accuracy of damage assessment in RC structures. The application of the research findings to RC flexural members will enable their safe and efficient performance.

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

Identifying the triggers for management services in business transformation management

Business transformations are complex organisational change endeavours that result in a business performing current work differently, or performing different work. Information Technology (IT) is a key enabler of such initiatives, but comes with its challenges, as revamping the IT infrastructure in large-scale organisations implies high complexity, high risk, and often high failure rates. We view business transformations as a collection of management services that are demanded and enacted at a program level, defined as abstract resources that provide the managerial capabilities necessary for business transformations. In this research-in-progress, we explore what triggers the need for management services in response to the challenges in business transformation management. We analyse data from two exploratory case studies using the critical incident technique as our qualitative analysis method. Early findings indicate that management service triggers reside on either the strategic level, which may be internally or externally driven, or at the program management level, which may be situational, influential or reactional. We detail implications for our on-going research.

Quality Assessment Matrix : A Collaborative Evaluation Using Multiple Lines of Evidence

Welcome to the Quality assessment matrix. This matrix is designed for highly qualified discipline experts to evaluate their course, major or unit in a systematic manner. The primary purpose of the Quality assessment matrix is to provide a tool that a group of academic staff at universities can collaboratively review the assessment within a course, major or unit annually. The annual review will result in you being read for an external curricula review at any point in time. This tool is designed for use in a workshop format with one, two or more academic staff, and will lead to an action plan for implementation.

Ruptures in the heterosexual matrix through teenage flows and multiplicities

This article analyzes a series of stories and artworks that were produced in a collective biography workshop. It explores Judith Butler’s concept of the heterosexual matrix combined with a Deleuzian theoretical framework. The article begins with an overview of Butler’s concept of the heterosexual matrix and her theorizations on how it might be disrupted. It then suggests how a Deleuzian framework offers other tools for analyzing these ruptures at the micro level of girls’ everyday interactions.

Thermal treatment of natural goethite : thermal transformation and physical properties

XRD (X-ray diffraction), XRF (X-ray fluorescence), TG (thermogravimetry), FT-IES (Fourier transform infrared emission spectroscopy), FESEM (field emission scanning electron microscope), TEM (transmission electron microscope) and nitrogen–adsorption–desorption analysis were used to characterize the composition and thermal evolution of the structure of natural goethite. The in situ FT-IES demonstrated the start temperature (250 °C) of the transformation of natural goethite to hematite and the thermodynamic stability of protohematite between 250 and 600 °C. The heated products showed a topotactic relationship to the original mineral based on SEM analysis. Finally, the nitrogen–adsorption–desorption isotherm provided the variation of surface area and pore size distribution as a function of temperature. The surface area displayed a remarkable increase up to 350 °C, and then decreased above this temperature. The significant increase in surface area was attributed to the formation of regularly arranged slit-shaped micropores running parallel to elongated direction of hematite microcrystal. The main pore size varied from 0.99 nm to 3.5 nm when heating temperature increases from 300 to 400 °C. The hematite derived from heating goethite possesses high surface area and favors the possible application of hematite as an adsorbent as well as catalyst carrier.

Matrix metalloproteinase biosensor based on a porous silicon reflector

Matrix metalloproteinases (MMPs) are proteolytic enzymes important to wound healing. In non-healing wounds, it has been suggested that MMP levels become dysfunctional, hence it is of great interest to develop sensors to detect MMP biomarkers. This study presents the development of a label-free optical MMP biosensor based on a functionalised porous silicon (pSi) thin film. The biosensor is fabricated by immobilising a peptidomimetic MMP inhibitor in the porous layer using hydrosilylation followed by amide coupling. The binding of MMP to the immobilised inhibitor translates into a change of effective optical thickness (EOT) over the time. We investigate the effect of surface functionalisation on the stability of pSi surface and evaluate the sensing performance. We successfully demonstrate MMP detection in buffer solution and human wound fluid at physiologically relevant concentrations. This biosensor may find application as a point-of-care device that is prognostic of the healing trajectory of chronic wounds.