Efectos jurídicos de prohibir minería en ecosistemas de páramos con títulos mineros preexistentes

A raíz del impacto ambiental que produce la actividad minera sobre la biodiversidad y los recursos naturales, el sistema jurídico colombiano sustrajo de esta actividad, zonas de especial importancia ecológica y ambiental, que podrían llegar a deteriorarse en su totalidad. Sin embargo, si bien es clara la importancia de proteger estas zonas de la actividad extractiva, lo cierto es que en la actualidad se presenta un alto porcentaje de estas zonas que se superponen con títulos mineros. Circunstancia que conlleva a que entren en tensión intereses constitucionales protegidos. Por un lado, el interés general de proteger el medio ambiente y los recursos naturales y por el otro, el interés público de desarrollar la actividad minera. De acuerdo a lo anterior, a través de este trabajo de investigación, se busca describir y analizar las consecuencias en el ámbito jurídico, que se generan, al prohibir la actividad minera en zonas sobre las cuales el Estado había autorizado la realización de actividades de exploración y /o explotación minera con anterioridad al cambio regulatorio. En consecuencia, se expondrán los escenarios en que se puede encontrar un contrato de concesión, con la prohibición legal de desarrollar actividades mineras en ecosistemas de páramos. Específicamente, se analizará la situación de los títulos mineros que cuenten con licencia ambiental, títulos mineros que se encuentren en etapa de exploración y los títulos que habiendo terminado la etapa de exploración su licencia ambiental se encuentre en trámite.

Prevalencia e incidencia de cáncer en habitantes de Sibaté, y georeferenciación de casos 2010-2014

Introducción: El Cáncer es prevenible en algunos casos, si se evita la exposición a sustancias cancerígenas en el medio ambiente. En Colombia, Cundinamarca es uno de los departamentos con mayores incrementos en la tasa de mortalidad y en el municipio de Sibaté, habitantes han manifestado preocupación por el incremento de la enfermedad. En el campo de la salud ambiental mundial, la georreferenciación aplicada al estudio de fenómenos en salud, ha tenido éxito con resultados válidos. El estudio propuso usar herramientas de información geográfica, para generar análisis de tiempo y espacio que hicieran visible el comportamiento del cáncer en Sibaté y sustentaran hipótesis de influencias ambientales sobre concentraciones de casos. Objetivo: Obtener incidencia y prevalencia de casos de cáncer en habitantes de Sibaté y georreferenciar los casos en un periodo de 5 años, con base en indagación de registros. Metodología: Estudio exploratorio descriptivo de corte transversal,sobre todos los diagnósticos de cáncer entre los años 2010 a 2014, encontrados en los archivos de la Secretaria de Salud municipal. Se incluyeron unicamente quienes tuvieron residencia permanente en el municipio y fueron diagnosticados con cáncer entre los años de 2010 a 2104. Sobre cada caso se obtuvo género, edad, estrato socioeconómico, nivel académico, ocupación y estado civil. Para el análisis de tiempo se usó la fecha de diagnóstico y para el análisis de espacio, la dirección de residencia, tipo de cáncer y coordenada geográfica. Se generaron coordenadas geográficas con un equipo GPS Garmin y se crearon mapas con los puntos de la ubicación de las viviendas de los pacientes. Se proceso la información, con Epi Info 7 Resultados: Se encontraron 107 casos de cáncer registrados en la Secretaria de Salud de Sibaté, 66 mujeres, 41 hombres. Sin división de género, el 30.93% de la población presento cáncer del sistema reproductor, el 18,56% digestivo y el 17,53% tegumentario. Se presentaron 2 grandes casos de agrupaciones espaciales en el territorio estudiado, una en el Barrio Pablo Neruda con 12 (21,05%) casos y en el casco Urbano de Sibaté con 38 (66,67%) casos. Conclusión: Se corroboro que el análisis geográfico con variables espacio temporales y de exposición, puede ser la herramienta para generar hipótesis sobre asociaciones de casos de cáncer con factores ambientales.

The impact of mining and smelting activities on property values : a study of Mount Isa city, Queensland, Australia

Much publicity has been given to the problem of high levels of environmental contaminants, most notably high blood lead concentration levels among children in the city of Mount Isa because of mining and smelting activities. The health impacts from mining-related pollutants are now well documented. This includes published research being discussed in an editorial of the Medical Journal of Australia (see Munksgaard et al. 2010). On the other hand, negative impacts on property prices, although mentioned, have not been examined to date. This study rectifies this research gap. This study uses a hedonic property price approach to examine the impact of mining- and smelting-related pollution on nearby property prices. The hypothesis is that those properties closer to the lead and copper smelters have lower property (house) prices than those farther away. The results of the study show that the marginal willingness to pay to be farther from the pollution source is AUS $13 947 per kilometre within the 4 km radius selected. The study has several policy implications, which are discussed briefly. We used ordinary least squares, geographically weighted regression, spatial error and spatial autoregressive or spatial lag models for this analysis.

Mining large-scale response networks reveals `topmost activities' in Mycobacterium tuberculosis infection

Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.

Strengthening artisanal mining research and policy through baseline census activities

Over the past 10-15 years, several governments have implemented an array of technology, support-related, sustainable livelihoods (SL) and poverty-reduction projects for artisanal and small-scale mining (ASM). In the majority of cases, however, these interventions have failed to facilitate improvements in the industry's productivity and raise the living standards of the sector's subsistence operators. This article argues that a poor understanding of the demographics of target populations has precipitated these outcomes. In order to strengthen policy and assistance in the sector, governments must determine, with greater precision, the number of people operating in ASM regions, their origins and ethnic backgrounds, ages, and educational levels. This can be achieved by carrying out basic and localized census work before promoting ambitious sector-specific projects aimed at improving working conditions in the industry.

Sr-Nd isotopic analyses of sand-sized sediment from the San Francisco Bay coastal system

A diverse suite of geochemical tracers, including 87Sr/86Sr and 143Nd/144Nd isotope ratios, the rare earth elements (REEs), and select trace elements were used to determine sand-sized sediment provenance and transport pathways within the San Francisco Bay coastal system. This study complements a large interdisciplinary effort (Barnard et al., 2012) that seeks to better understand recent geomorphic change in a highly urbanized and dynamic estuarine-coastal setting. Sand-sized sediment provenance in this geologically complex system is important to estuarine resource managers and was assessed by examining the geographic distribution of this suite of geochemical tracers from the primary sources (fluvial and rock) throughout the bay, adjacent coast, and beaches. Due to their intrinsic geochemical nature, 143Nd/144Nd isotopic ratios provide the most resolved picture of where sediment in this system is likely sourced and how it moves through this estuarine system into the Pacific Ocean. For example, Nd isotopes confirm that the predominant source of sand-sized sediment to Suisun Bay, San Pablo Bay, and Central Bay is the Sierra Nevada Batholith via the Sacramento River, with lesser contributions from the Napa and San Joaquin Rivers. Isotopic ratios also reveal hot-spots of local sediment accumulation, such as the basalt and chert deposits around the Golden Gate Bridge and the high magnetite deposits of Ocean Beach. Sand-sized sediment that exits San Francisco Bay accumulates on the ebb-tidal delta and is in part conveyed southward by long-shore currents. Broadly, the geochemical tracers reveal a complex story of multiple sediment sources, dynamic intra-bay sediment mixing and reworking, and eventual dilution and transport by energetic marine processes. Combined geochemical results provide information on sediment movement into and through San Francisco Bay and further our understanding of how sustained anthropogenic activities which limit sediment inputs to the system (e.g., dike and dam construction) as well as those which directly remove sediments from within the Bay, such as aggregate mining and dredging, can have long-lasting effects.

The Exploration and Development of Alternative Management Strategies for Mining and Recreational Activities Atop Mount Antero and Mount White; Chaffee County, Colorado

The Mount Antero/White area is a popular prospecting area. Recent expansions in the recreation economy is drawing more visitors to the area. Consequently, visitors may be placing unsustainable pressures on the landscape. In order to help rectify this, the legal, ecological, geologic, aesthetic, recreational, historic, social, and economic character of the Antero/White area has been identified. Four feasible management alternatives have also been recognized. They are a) take no new management actions, b) prohibit motorized activities in the area, c) develop a mineralogical park, and d) a combination of options b and c. Option C has been defended, as it best balances the desires of area users with the underlying ecological and geological character of the area.

San Francisco Coastal System grain size and geochemical data for sand provenance study

Over 150 million cubic meter of sand-sized sediment has disappeared from the central region of the San Francisco Bay Coastal System during the last half century. This enormous loss may reflect numerous anthropogenic influences, such as watershed damming, bay-fill development, aggregate mining, and dredging. The reduction in Bay sediment also appears to be linked to a reduction in sediment supply and recent widespread erosion of adjacent beaches, wetlands, and submarine environments. A unique, multi-faceted provenance study was performed to definitively establish the primary sources, sinks, and transport pathways of beach sized-sand in the region, thereby identifying the activities and processes that directly limit supply to the outer coast. This integrative program is based on comprehensive surficial sediment sampling of the San Francisco Bay Coastal System, including the seabed, Bay floor, area beaches, adjacent rock units, and major drainages. Analyses of sample morphometrics and biological composition (e.g., Foraminifera) were then integrated with a suite of tracers including 87Sr/86Sr and 143Nd/144Nd isotopes, rare earth elements, semi-quantitative X-ray diffraction mineralogy, and heavy minerals, and with process-based numerical modeling, in situ current measurements, and bedform asymmetry to robustly determine the provenance of beach-sized sand in the region.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

From bust to boom : towards a strategic cognition perspective on Australian mining firms’ adaption

While the role of executives’ cognition in organisations’ responses to change is a central topic in strategic cognition research, changes in firms’ environment are typically not measured directly but described either as an event (for example, new industry legislation) or represented by a time period (e.g. when a new technology impacted an industry). The Australian mining sector has witnessed a historically significant change in demand for its products and we begin by developing measures of changes in supply and demand for key commodities during the period 1992-2008. We identify sub-groups of firms based on their activities and commodity sector and examine the relation of these variables to executives’ cognition and to firms’ CapEx. We find industry, firm and cognitive variables are related to both strategic cognition and firms’ CapEx.

Finding and matching communities in social networks using data mining

The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.