Public participation in Michigan mining policy : the Kennecott Eagle Project case

Public participation is an important component of Michigan’s Part 632 Nonferrous Mining law and is identified by researchers as important to decision-making processes. The Kennecott Eagle Project, which is located near Marquette, Michigan, is the first mine permitted under Michigan’s new mining regulation, and this research examines how public participation is structured in regulations, how the permitting process occurred during the permitting of the Eagle Project, and how participants in the permitting process perceived their participation. To understand these issues, this research implemented a review of existing mining policy and public participation policy literature, examination of documents related to the Kennecott Eagle Project and completion of semi-structured, ethnographic interviews with participants in the decision-making process. Interviewees identified issues with the structure of participation, the technical nature of the permitting process, concerns about the Michigan Department of Environmental Quality’s (DEQ) handling of mine permitting, and trust among participants. This research found that the permitting of the Kennecott Eagle Mine progressed as structured by regulation and collected technical input on the mine permit application, but did not meet the expectations of some participants who opposed the project. Findings from this research indicated that current mining regulation in Michigan is resilient to public opposition, there is need for more transparency from the Michigan DEQ during the permitting process, and current participatory structures limit the opportunities for some stakeholder groups to influence decision-making.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

La Planificación de Áreas Mineras en Declive : Una respuesta multidimensional = Planning Declining Mining Areas. A multidimensional response

La actividad minera tiene un gran impacto sobre el territorio, probablemente más que ninguna otra de las actividades humanas, ya que transforma el espacio en todas sus dimensiones: ecológica, ambiental, social y económica. Cuando la reducción de la rentabilidad de la explotación conduce al cierre de ésta, la repercusión sobre su entorno puede llegar a ser brutal. Pero las explotaciones mineras son muy distintas entre ellas y los efectos que su abandono producen sobre el espacio en la que se enclavan pueden ser diversos, por lo que la decisión sobre el futuro de estas áreas no es simple y evidente. Aquí se propone desarrollar una propuesta de clasificación tipológica de las minas y sus regiones con el objetivo de determinar las estrategias de intervención más adecuadas para el futuro de estos espacios y sus habitantes. En concreto se busca diferenciar los conceptos de Mina, Parque Minero, Espacio Minero y Región Minera, todos ellos fruto de la interacción de la huella de la actividad minera con el medio físico, los enclaves urbanizados, y la estructura socioeconómica de la región en la que se enclavan. Mining activity is having a great impact on the territory, probably more than any other human activity, which transforms the space in all of its dimensions, ecological, environmental, social and economic. When reducing the profitability of the operation leads to the conclusion thereof, the impact on the environment can be brutal. But mining are very different between them and the effects they produce on their abandonment in space that interlock can be diverse, so the decision on the future of these areas is not simple and obvious. This proposal aims to develop a typological classification of mines and their regions in order to determine the most appropriate intervention strategies for the future of these spaces and their inhabitants. Specifically, it seeks to differentiate the concepts of Mine, Mining Park, Space Miner and Mining Region, all the result of the interaction of the mining footprint with the physical environment, the urbanized enclaves, and the socio-economic structure of the region which interlock. El presente libro reúne las ponencias presentadas por los investigadores de la red REUSE dentro del 1er Simposio de Reutilización del Espacio Minero; evento organizado por la Universidad Federal de Minas Gerais (UFMG) en Belo Horizonte, entre el 1 y el 3 de octubre de 2012, en el marco del 1er Seminario Internacional de Reconversión de Territorios. La red REUSE es una red realizada gracias a la financiación del programa CYTED

Nanoinformatics approaches for information extraction and text mining in nanomedical research texts

La nanotecnología es un área de investigación de reciente creación que trata con la manipulación y el control de la materia con dimensiones comprendidas entre 1 y 100 nanómetros. A escala nanométrica, los materiales exhiben fenómenos físicos, químicos y biológicos singulares, muy distintos a los que manifiestan a escala convencional. En medicina, los compuestos miniaturizados a nanoescala y los materiales nanoestructurados ofrecen una mayor eficacia con respecto a las formulaciones químicas tradicionales, así como una mejora en la focalización del medicamento hacia la diana terapéutica, revelando así nuevas propiedades diagnósticas y terapéuticas. A su vez, la complejidad de la información a nivel nano es mucho mayor que en los niveles biológicos convencionales (desde el nivel de población hasta el nivel de célula) y, por tanto, cualquier flujo de trabajo en nanomedicina requiere, de forma inherente, estrategias de gestión de información avanzadas. Desafortunadamente, la informática biomédica todavía no ha proporcionado el marco de trabajo que permita lidiar con estos retos de la información a nivel nano, ni ha adaptado sus métodos y herramientas a este nuevo campo de investigación. En este contexto, la nueva área de la nanoinformática pretende detectar y establecer los vínculos existentes entre la medicina, la nanotecnología y la informática, fomentando así la aplicación de métodos computacionales para resolver las cuestiones y problemas que surgen con la información en la amplia intersección entre la biomedicina y la nanotecnología. Las observaciones expuestas previamente determinan el contexto de esta tesis doctoral, la cual se centra en analizar el dominio de la nanomedicina en profundidad, así como en el desarrollo de estrategias y herramientas para establecer correspondencias entre las distintas disciplinas, fuentes de datos, recursos computacionales y técnicas orientadas a la extracción de información y la minería de textos, con el objetivo final de hacer uso de los datos nanomédicos disponibles. El autor analiza, a través de casos reales, alguna de las tareas de investigación en nanomedicina que requieren o que pueden beneficiarse del uso de métodos y herramientas nanoinformáticas, ilustrando de esta forma los inconvenientes y limitaciones actuales de los enfoques de informática biomédica a la hora de tratar con datos pertenecientes al dominio nanomédico. Se discuten tres escenarios diferentes como ejemplos de actividades que los investigadores realizan mientras llevan a cabo su investigación, comparando los contextos biomédico y nanomédico: i) búsqueda en la Web de fuentes de datos y recursos computacionales que den soporte a su investigación; ii) búsqueda en la literatura científica de resultados experimentales y publicaciones relacionadas con su investigación; iii) búsqueda en registros de ensayos clínicos de resultados clínicos relacionados con su investigación. El desarrollo de estas actividades requiere el uso de herramientas y servicios informáticos, como exploradores Web, bases de datos de referencias bibliográficas indexando la literatura biomédica y registros online de ensayos clínicos, respectivamente. Para cada escenario, este documento proporciona un análisis detallado de los posibles obstáculos que pueden dificultar el desarrollo y el resultado de las diferentes tareas de investigación en cada uno de los dos campos citados (biomedicina y nanomedicina), poniendo especial énfasis en los retos existentes en la investigación nanomédica, campo en el que se han detectado las mayores dificultades. El autor ilustra cómo la aplicación de metodologías provenientes de la informática biomédica a estos escenarios resulta efectiva en el dominio biomédico, mientras que dichas metodologías presentan serias limitaciones cuando son aplicadas al contexto nanomédico. Para abordar dichas limitaciones, el autor propone un enfoque nanoinformático, original, diseñado específicamente para tratar con las características especiales que la información presenta a nivel nano. El enfoque consiste en un análisis en profundidad de la literatura científica y de los registros de ensayos clínicos disponibles para extraer información relevante sobre experimentos y resultados en nanomedicina —patrones textuales, vocabulario en común, descriptores de experimentos, parámetros de caracterización, etc.—, seguido del desarrollo de mecanismos para estructurar y analizar dicha información automáticamente. Este análisis concluye con la generación de un modelo de datos de referencia (gold standard) —un conjunto de datos de entrenamiento y de test anotados manualmente—, el cual ha sido aplicado a la clasificación de registros de ensayos clínicos, permitiendo distinguir automáticamente los estudios centrados en nanodrogas y nanodispositivos de aquellos enfocados a testear productos farmacéuticos tradicionales. El presente trabajo pretende proporcionar los métodos necesarios para organizar, depurar, filtrar y validar parte de los datos nanomédicos existentes en la actualidad a una escala adecuada para la toma de decisiones. Análisis similares para otras tareas de investigación en nanomedicina ayudarían a detectar qué recursos nanoinformáticos se requieren para cumplir los objetivos actuales en el área, así como a generar conjunto de datos de referencia, estructurados y densos en información, a partir de literatura y otros fuentes no estructuradas para poder aplicar nuevos algoritmos e inferir nueva información de valor para la investigación en nanomedicina. ABSTRACT Nanotechnology is a research area of recent development that deals with the manipulation and control of matter with dimensions ranging from 1 to 100 nanometers. At the nanoscale, materials exhibit singular physical, chemical and biological phenomena, very different from those manifested at the conventional scale. In medicine, nanosized compounds and nanostructured materials offer improved drug targeting and efficacy with respect to traditional formulations, and reveal novel diagnostic and therapeutic properties. Nevertheless, the complexity of information at the nano level is much higher than the complexity at the conventional biological levels (from populations to the cell). Thus, any nanomedical research workflow inherently demands advanced information management. Unfortunately, Biomedical Informatics (BMI) has not yet provided the necessary framework to deal with such information challenges, nor adapted its methods and tools to the new research field. In this context, the novel area of nanoinformatics aims to build new bridges between medicine, nanotechnology and informatics, allowing the application of computational methods to solve informational issues at the wide intersection between biomedicine and nanotechnology. The above observations determine the context of this doctoral dissertation, which is focused on analyzing the nanomedical domain in-depth, and developing nanoinformatics strategies and tools to map across disciplines, data sources, computational resources, and information extraction and text mining techniques, for leveraging available nanomedical data. The author analyzes, through real-life case studies, some research tasks in nanomedicine that would require or could benefit from the use of nanoinformatics methods and tools, illustrating present drawbacks and limitations of BMI approaches to deal with data belonging to the nanomedical domain. Three different scenarios, comparing both the biomedical and nanomedical contexts, are discussed as examples of activities that researchers would perform while conducting their research: i) searching over the Web for data sources and computational resources supporting their research; ii) searching the literature for experimental results and publications related to their research, and iii) searching clinical trial registries for clinical results related to their research. The development of these activities will depend on the use of informatics tools and services, such as web browsers, databases of citations and abstracts indexing the biomedical literature, and web-based clinical trial registries, respectively. For each scenario, this document provides a detailed analysis of the potential information barriers that could hamper the successful development of the different research tasks in both fields (biomedicine and nanomedicine), emphasizing the existing challenges for nanomedical research —where the major barriers have been found. The author illustrates how the application of BMI methodologies to these scenarios can be proven successful in the biomedical domain, whilst these methodologies present severe limitations when applied to the nanomedical context. To address such limitations, the author proposes an original nanoinformatics approach specifically designed to deal with the special characteristics of information at the nano level. This approach consists of an in-depth analysis of the scientific literature and available clinical trial registries to extract relevant information about experiments and results in nanomedicine —textual patterns, common vocabulary, experiment descriptors, characterization parameters, etc.—, followed by the development of mechanisms to automatically structure and analyze this information. This analysis resulted in the generation of a gold standard —a manually annotated training or reference set—, which was applied to the automatic classification of clinical trial summaries, distinguishing studies focused on nanodrugs and nanodevices from those aimed at testing traditional pharmaceuticals. The present work aims to provide the necessary methods for organizing, curating and validating existing nanomedical data on a scale suitable for decision-making. Similar analysis for different nanomedical research tasks would help to detect which nanoinformatics resources are required to meet current goals in the field, as well as to generate densely populated and machine-interpretable reference datasets from the literature and other unstructured sources for further testing novel algorithms and inferring new valuable information for nanomedicine.

The changing structure of the U.S. coal industry, 1976-1986.

Item 429-T-11

Mining-associated Seismicity in Kolar Gold Mines: Some Case Studies using Multi-fractals

The occurrence of rockbursts was quite common during active mining periods in the Champion reef mines of Kolar gold fields, India. Among the major rockbursts, the ‘area-rockbursts’ were unique both in regard to their spatio-temporal distribution and the extent of damage caused to the mine workings. A detailed study of the spatial clustering of 3 major area-rockbursts (ARB) was carried out using a multi-fractal technique involving generalized correlation integral functions. The spatial distribution analysis of all 3 area-rockbursts showed that they are heterogeneous. The degree of heterogeneity (D2 – D∞) in the cases of ARB-I, II and III were found to be 0.52, 0.37 and 0.41 respectively. These differences in fractal structure indicate that the ARBs of the present study were fully controlled by different heterogeneous stress fields associated with different mining and geological conditions. The present study clearly showed the advantages of the application of multi-fractals to seismic data and to characterise, analyse and examine the area-rockbursts and their causative factors in the Kolar gold mines.

Safety and health in mines: the rise of bureaucracy in the coal mining industry and its results as evidenced by the public enquiry into an accident at Houghton Main Colliery

This thesis is concerned with certain aspects of the Public Inquiry into the accident at Houghton Main Colliery in June 1975. It examines whether prior to the accident there existed at the Colliery a situation in which too much reliance was being placed upon state regulation and too Iittle upon personal responsibility. I study the phenomenon of state regulation. This is done (a) by analysis of selected writings on state regulation/intervention/interference/bureaucracy (the words are used synonymously) over the last two hundred years, specifically those of Marx on the 1866 Committee on Mines, and (b) by studying Chadwick and Tremenheere, leading and contrasting "bureaucrats" of the mid-nineteenth century. The bureaucratisation of the mining industry over the period 1835-1954 is described, and it is demonstrated that the industry obtained and now possesses those characteristics outlined by Max Weber in his model of bureaucracy. I analyse criticisms of the model and find them to be relevant, in that they facilitate understanding both of the circumstances of the accident and of the Inquiry . Further understanding of the circumstances and causes of the accident was gained by attendance at the lnquiry and by interviewing many of those involved in the Inquiry. I analyse many aspects of the Inquiry - its objectives. structure, procedure and conflicting interests - and find that, although the Inquiry had many of the symbols of bureaucracy, it suffered not from " too much" outside interference. but rather from the coal mining industry's shared belief in its ability to solve its own problems. I found nothing to suggest that, prior to the accident, colliery personnel relied. or were encouraged to rely, "too much" upon state regulation.

Infer user interests via link structure regularization

Learning user interests from online social networks helps to better understand user behaviors and provides useful guidance to design user-centric applications. Apart from analyzing users' online content, it is also important to consider users' social connections in the social Web. Graph regularization methods have been widely used in various text mining tasks, which can leverage the graph structure information extracted from data. Previously, graph regularization methods operate under the cluster assumption that nearby nodes are more similar and nodes on the same structure (typically referred to as a cluster or a manifold) are likely to be similar. We argue that learning user interests from complex, sparse, and dynamic social networks should be based on the link structure assumption under which node similarities are evaluated based on the local link structures instead of explicit links between two nodes. We propose a regularization framework based on the relation bipartite graph, which can be constructed from any type of relations. Using Twitter as our case study, we evaluate our proposed framework from social networks built from retweet relations. Both quantitative and qualitative experiments show that our proposed method outperforms a few competitive baselines in learning user interests over a set of predefined topics. It also gives superior results compared to the baselines on retweet prediction and topical authority identification. © 2014 ACM.

Feature Extraction for Classification in the Data Mining Process

Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of “the curse of dimensionality”. Three different eigenvector-based feature extraction approaches are discussed and three different kinds of applications with respect to classification tasks are considered. The summary of obtained results concerning the accuracy of classification schemes is presented with the conclusion about the search for the most appropriate feature extraction method. The problem how to discover knowledge needed to integrate the feature extraction and classification processes is stated. A decision support system to aid in the integration of the feature extraction and classification processes is proposed. The goals and requirements set for the decision support system and its basic structure are defined. The means of knowledge acquisition needed to build up the proposed system are considered.

Analysis and Data Mining of Lead-Zinc Ore Data

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set of the DMX queries allows for browsing and managing the clusters, as well as predicting ore assay records. A testing and validation of the Pb-Zn cluster data mining model was developed in order to show its reasonable accuracy before beingused in a production environment. The Pb-Zn cluster data mining model can be used for changes of the mine grinding and floatation processing parameters in almost real-time, which is important for the efficiency of the Pb-Zn ore beneficiation process. ACM Computing Classification System (1998): H.2.8, H.3.3.

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

Mining in Peru: Indigenous and Peasant Communities vs. The State and Mining Capital

The Peruvian economy depends for its growth on the export of natural resources and investment in the mining and hydrocarbon sectors. Peruvian governments and mining corporations have confronted anti-mining protests in different ways. While the current government has introduced policies of social inclusion to soften the negative effects of the operations of mining capital and policies of dialogue to engage social actors with the essence of governmental policies, mining companies use corporate social responsibility programs as a cover for the devastating effects of their operations on the environment and the livelihoods and habitats of the indigenous and peasant communities. Curiously, in the current context of the declining commodity prices and export volumes the Peruvian government strengthens its extractivist model of development. This article argues that whatever government that follows the rules of capital cannot but favor the corporations. It points out the main adversaries of the indigenous and peasant communities and the problems to transform the locally and/or regionally struggle into a nationwide battle for another development model.

Contextual text mining

With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

The Influence of Healed Intrablock Rockmass Structure on the Behaviour of Deep Excavations in Complex Rockmasses

Conventional rockmass characterization and analysis methods for geotechnical assessment in mining, civil tunnelling, and other excavations consider only the intact rock properties and the discrete fractures that are present and form blocks within rockmasses. Field logging and classification protocols are based on historically useful but highly simplified design techniques, including direct empirical design and empirical strength assessment for simplified ground reaction and support analysis. As modern underground excavations go deeper and enter into more high stress environments with complex excavation geometries and associated stress paths, healed structures within initially intact rock blocks such as sedimentary nodule boundaries and hydrothermal veins, veinlets and stockwork (termed intrablock structure) are having an increasing influence on rockmass behaviour and should be included in modern geotechnical design. Due to the reliance on geotechnical classification methods which predate computer aided analysis, these complexities are ignored in conventional design. Given the comparatively complex, sophisticated and powerful numerical simulation and analysis techniques now practically available to the geotechnical engineer, this research is driven by the need for enhanced characterization of intrablock structure for application to numerical methods. Intrablock structure governs stress-driven behaviour at depth, gravity driven disintegration for large shallow spans, and controls ultimate fragmentation. This research addresses the characterization of intrablock structure and the understanding of its behaviour at laboratory testing and excavation scales, and presents new methodologies and tools to incorporate intrablock structure into geotechnical design practice. A new field characterization tool, the Composite Geological Strength Index, is used for outcrop or excavation face evaluation and provides direct input to continuum numerical models with implicit rockmass structure. A brittle overbreak estimation tool for complex rockmasses is developed using field observations. New methods to evaluate geometrical and mechanical properties of intrablock structure are developed. Finally, laboratory direct shear testing protocols for interblock structure are critically evaluated and extended to intrablock structure for the purpose of determining input parameters for numerical models with explicit structure.