The Wheal Jane wetlands model for bioremediation of acid mine drainage

Acid mine drainage (AMD) is a widespread environmental problem associated with both working and abandoned mining operations. As part of an overall strategy to determine a long-term treatment option for AMD, a pilot passive treatment plant was constructed in 1994 at Wheal Jane Mine in Cornwall, UK. The plant consists of three separate systems, each containing aerobic reed beds, anaerobic cell and rock filters, and represents the largest European experimental facility of its kind. The systems only differ by the type of pretreatment utilised to increase the pH of the influent minewater (pH <4): lime dosed (LD), anoxic limestone drain (ALD) and lime free (LF), which receives no form of pretreatment. Historical data (1994-1997) indicate median Fe reduction between 55% and 92%, sulphate removal in the range of 3-38% and removal of target metals (cadmium, copper and zinc) below detection limits, depending on pretreatment and flow rates through the system. A new model to simulate the processes and dynamics of the wetlands systems is described, as well as the application of the model to experimental data collected at the pilot plant. The model is process based, and utilises reaction kinetic approaches based on experimental microbial techniques rather than an equilibrium approach to metal precipitation. The model is dynamic and utilises numerical integration routines to solve a set of differential equations that describe the behaviour of 20 variables over the 17 pilot plant cells on a daily basis. The model outputs at each cell boundary are evaluated and compared with the measured data, and the model is demonstrated to provide a good representation of the complex behaviour of the wetland system for a wide range of variables. (C) 2004 Elsevier B.V/ All rights reserved.

Bioremediation of acid mine drainage: an introduction to the Wheal Jane wetlands project

Acid mine drainage (AMD) is a widespread environmental problem associated with both working and abandoned mining operations. As part of an overall strategy to determine a long-term treatment option for AMD, a pilot passive treatment plant was constructed in 1994 at Wheat Jane Mine in Cornwall, UK. The plant consists of three separate systems; each containing aerobic reed beds, anaerobic cell and rock filters, and represents the largest European experimental facility of its kind. The systems only differ by the type of pre-treatment utilised to increase the pH of the influent minewater (pH<4): lime-dosed (LD), anoxic limestone drain (ALD) and lime free (LF), which receives no form of pre-treatment. The Wheal Jane pilot plant offered a unique facility and a major research project was established to evaluate the pilot plant and study in detail the biological mechanisms and the geochemical and physical processes that control passive treatment systems. The project has led to data, knowledge, models and design criteria for the future design, planning and sustainable management of passive treatment systems. A multidisciplinary team of scientists and managers from the U.K. universities, the Environment Agency and the Mining Industry has been put together to obtain the maximum advantage from the excellent facilities facility at Wheal Jane. (C) 2004 Elseaier B.V All rights reserved.

Skill Rating by Bayesian Inference

Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure.

‘Inherited commitments’: do changes in ownership affect corporate social responsibility (CSR) at African gold mines?

This paper critically examines the issue of ‘inherited corporate social responsibility’ in the gold mining industry, focusing specifically on the case of sub-Saharan Africa, a region plagued with excessive corruption, rampant poverty and weak governance. Whilst there appears to be little incentive to proactively engage with communities and implement cutting-edge environmental policies in the region, mine managers argue otherwise, highlighting a number of reasons for embracing corporate social responsibility (CSR). After briefly reviewing the philosophical underpinnings of CSR, the paper provides an in-depth analysis of these arguments, in the process, underscoring how tenuous the case for CSR in the extractive industries, and gold mining more specifically, is in the context of sub-Saharan Africa. Following a change in ownership, new management faces few pressures to embrace CSR in its entirety and therefore, more often than not, finds itself in a position to implement programs and policies of its choice. More research is needed that further popularizes the issue of ‘inherited CSR’ in the gold mining sector and extractive industries more generally.

PMCRI: a parallel modular classification rule induction framework

In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction of Decision Trees (TDIDT) algorithm is a very widely used technology to predict the classification of newly recorded data. However alternative technologies have been derived that often produce better rules but do not scale well on large datasets. Such an alternative to TDIDT is the PrismTCS algorithm. PrismTCS performs particularly well on noisy data but does not scale well on large datasets. In this paper we introduce Prism and investigate its scaling behaviour. We describe how we improved the scalability of the serial version of Prism and investigate its limitations. We then describe our work to overcome these limitations by developing a framework to parallelise algorithms of the Prism family and similar algorithms. We also present the scale up results of a first prototype implementation.

How Twitter is studied in the medical professions: a classification of Twitter papers indexed in PubMed

Background: Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. // Objective: This paper aims to identify published work relating to Twitter indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Limiting the study to papers indexed by PubMed ensures the work provides a reproducible benchmark. // Methods: Papers, indexed by PubMed, on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain and aspect. // Results: As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focussed on Twitter (the others referring to it tangentially). The early Twitter focussed papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. // Conclusions: This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used five dimensions to categorise published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research relating to Twitter in the area of medicine and beyond, can position and ground their work.

Typography papers, 9

This latest issue of the series of Typography papers opens with a beautifully illustrated article by the type designer Gerard Unger on ‘Romanesque’ letters. A further installment of Eric Kindel’s pathbreaking history of stencil letters is published in contributions by him, Fred Smeijers, and James Mosley. Maurice Göldner writes the first history of an early twentieth-century German typefounder, Brüder Butter. William Berkson and Peter Enneson recover the notion of ‘readability’ through a history of the collaboration between Matthew Luckiesh and the Linotype Company. Paul Luna discusses the role of pictures in dictionaries. Titus Nemeth describes a new form of Arabic type for metal composition. The whole gathering shows the remarkable variety and vitality of typography now.

Relationships Among Murine CD11chigh Dendritic Cell Subsets as Revealed by Baseline Gene Expression Patterns

The functional relationships and properties of different subtypes of dendritic cells (DC) remain largely undefined. To better characterize these cells, we used global gene analysis to determine gene expression patterns among murine CD11c(high) DC subsets. CD4(+), CD8alpha(+), and CD8alpha(-) CD4(-) (double negative (DN)) DC were purified from spleens of normal C57/BL6 mice and analyzed using Affymetrix microarrays. The CD4(+) and CD8alpha(+) DC subsets showed distinct basal expression profiles differing by >200 individual genes. These included known DC subset markers as well as previously unrecognized, differentially expressed CD Ags such as CD1d, CD5, CD22, and CD72. Flow cytometric analysis confirmed differential expression in nine of nine cases, thereby validating the microarray analysis. Interestingly, the microarray expression profiles for DN cells strongly resembled those of CD4(+) DC, differing from them by <25 genes. This suggests that CD4(+) and DN DC are closely related phylogenetically, whereas CD8alpha(+) DC represent a more distant lineage, supporting the historical distinction between CD8alpha(+) and CD8alpha(-) DC. However, staining patterns revealed that in contrast to CD4(+) DC, the DN subset is heterogeneous and comprises at least two subpopulations. Gene Ontology and literature mining analyses of genes expressed differentially among DC subsets indicated strong associations with immune response parameters as well as cell differentiation and signaling. Such associations offer clues to possible unique functions of the CD11c(high) DC subsets that to date have been difficult to define as rigid distinctions.

Efficiency issues of evolutionary k-means

One of the top ten most influential data mining algorithms, k-means, is known for being simple and scalable. However, it is sensitive to initialization of prototypes and requires that the number of clusters be specified in advance. This paper shows that evolutionary techniques conceived to guide the application of k-means can be more computationally efficient than systematic (i.e., repetitive) approaches that try to get around the above-mentioned drawbacks by repeatedly running the algorithm from different configurations for the number of clusters and initial positions of prototypes. To do so, a modified version of a (k-means based) fast evolutionary algorithm for clustering is employed. Theoretical complexity analyses for the systematic and evolutionary algorithms under interest are provided. Computational experiments and statistical analyses of the results are presented for artificial and text mining data sets. (C) 2010 Elsevier B.V. All rights reserved.

Gruvrätten vid Stora Kopparberget 1641-1682 : en undersökning över rannsakade brott och utdömda straff

The purpose of this essay is to examine and explain how the Swedish mining court of Stora Kopparberget (the Great Copper Mountain) implemented its judicial legislation between 1641-1682. Questions are asked about which counts of indictments the court tried, which sentences they handed out, in what quantities and how these results looks in comparison with other contemporary courts. The index cards of the court judicial protocols are the primary source of information. The methods are those of quantity- and comparative analysis.The results show that theft of copper ore was the most common crime ransacked by the court. Other common crimes were (in order): sin of omission, transgression of work directions, fights, slander and disdain, trade of stolen ore, failing appearance in court etc.Fines were by far the most common sentence followed by shorter imprisonments, gauntlets, loss of right to mine possession, twig beating, loss of work, penal servitude, banishment, “wooden horse riding” and finally military transcription. Even though previous re-search, in the field of Swedish specialized courts, is almost non existent evidence confirms great similarities between the Stora Kopparberget mining court and Sala mining court. This essay will, hopefully, enrich our knowledge of specialized courts, of 17th century mining industry and society and let us reach a broader understanding of the working conditions of the mountain.

Praktiska effekter av begreppsförvirring för en databas konceptuella design : En fallstudie om databas- och begreppsmodellering

Company X develops a laboratory information system (LIS) called System Y. The informationsystem has a two-tier database architecture consisting of a production database and a historicaldatabase. A database constitutes the backbone of a IS, which makes the design of the databasevery important. A poorly designed database can cause major problems within an organization.The two databases in System Y are poorly modeled, particularly the historical database. Thecause of the poor modeling was unclear concepts. The unclear concepts have remained in thedatabase and in the company organization and caused a general confusion of concepts. The splitdatabase architecture itself has evolved into a bottleneck and is the cause of many problemsduring the development of System Y.Company X investigates the possibility of integrating the historical database with the productiondatabase. The goal of our thesis is to conduct a consequence analysis of such integration andwhat the effects would be on System Y, and to create a new design for the integrated database.We will also examine and describe the practical effects of confusion of concepts for a databaseconceptual design.To achieve the goal of the thesis, five different method steps have been performed: a preliminarystudy of the organization, a change analysis, a consequence analysis and an investigation of theconceptual design of the database. These method steps have helped identify changes necessaryfor the organization, a new design proposal for an integrated database, the impact of theproposed design and a number of effects of confusion for the database.

ANFIS BASED MODELS FOR ACCESSING QUALITY OF WIKIPEDIA ARTICLES

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.

A implantação da metodologia TPM num equipamento piloto na Adria Alimentos do Brasil Ltda.

A melhoria nos sistemas de manutenção é cada dia mais importante para o aprimoramento das atividades de uma empresa, tanto na área de produção como em outros setores. Pode-se afirmar, então, que uma boa sistemática de manutenção colabora para que a empresa cumpra suas funções em relação à confiabilidade, flexibilidade, rapidez, qualidade, mantendo custos competitivos. O presente trabalho analisa, de acordo com um prisma teórico e prático, um esforço de implantação da Manutenção Produtiva Total (TPM-“Total Productive Maintenance”). Ele tem como principal objetivo descrever e discutir a implantação da TPM em uma empresa fabricante de massas e biscoitos. Em um primeiro momento, a implantação aconteceu em uma linha piloto. O ponto de partida foi a apresentação da TPM com seus passos para implantação e pilares que sustentam esta ferramenta. Na seqüência, descreve-se como aconteceu a implantação desta sistemática na linha piloto da empresa, discutindo as dificuldades, vantagens e desvantagens percebidas. As conclusões do trabalho apontam para resultados percebidos na linha piloto, onde a implantação ocorreu, possibilitando a percepção de melhorias para a empresa e para seus colaboradores. Foram observadas melhorias tanto no que concerne à manutenção dos equipamentos quanto ao envolvimento das pessoas em todo o processo.