The Gandarela Mountain Range and the “resistance space” against iron ore mining threat: a focus on the contrapositions

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Distribution of diatom communities in agricultural and mining watersheds of Southwest Spain

Els sistemes aquàtics continental representen un dels ecosistemes més amenaçats a nivell mundial, com a conseqüència de l'ús intensiu quel'home en fa. La conca del Guadiana no està lliure d'aquestes pressions antròpiques. Les grans infraestructures hidràuliques i l'escorrentia provinent de l'agricultura són només exemples dels greus problemes que pateix la conca. Aquests problemes es fan especialment palesos en la zona alta de la conca, on l'escassetat d'aigua no fa més que agreujar el problema.Tot això ha generat la necessitat urgent d'avaluar l'estat de conservació d'aquests ecosistemes aquàtics continentals, poder determinar la mesura i la magnitud de les pertorbacions que els estan afectant i així proposar mesures de gestió destinades a restaurar-ne la integritat ecològica. El principal objectiu que presenta aquest és determinar els patrons de distribució de les comunitats de algals (amb una menció especial en el grup de les diatomees) i de les seves causes en la conca del Guadiana i associades, amb la finalitat d'establir i proposar eines que permetin avaluar l'estat de conservació de les masses d'aigua d'aquestes conques.

Analytical methodologies based on X-Ray Fluorescence Spectrometry (XRF) and Inductively Couple Plasma Spectroscopy (ICP) for the assessment of metal dispersal around mining environments

La investigació que es presenta en aquesta tesi es centra en l'aplicació i millora de metodologies analítiques existents i el desenvolupament de nous procediments que poden ser utilitzats per a l'estudi dels efectes ambientals de la dispersió dels metalls entorn a les zones mineres abandonades. En primer lloc, es van aplicar diferents procediments d'extracció simple i seqüencial per a estudiar la mobilitat, perillositat i bio-disponibilitat dels metalls continguts en residus miners de característiques diferents. Per altra banda, per a estudiar les fonts potencials de Pb en la vegetació de les zones mineres d'estudi, una metodologia basada en la utilització de les relacions isotòpiques de Pb determinades mitjançant ICP-MS va ser avaluada. Finalment, tenint en compte l'elevat nombre de mostres analitzades per a avaluar l'impacte de les activitats mineres, es va considerar apropiat el desenvolupament de mètodes analítics d'elevada productivitat. En aquest sentit la implementació d'estratègies quantitatives així com l'aplicació de les millores instrumentals en els equips de XRF han estat avaluades per a aconseguir resultats analítics fiables en l'anàlisi de plantes. A més, alguns paràmetres de qualitat com la precisió, l'exactitud i els límits de detecció han estat curosament determinats en les diverses configuracions de espectròmetres de XRF utilitzats en el decurs d'aquest treball (EDXRF, WDXRF i EDPXRF) per a establir la capacitat de la tècnica de XRF com a tècnica alternativa a les clàssiques comunament aplicades en la determinació d'elements en mostres vegetals.

Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.

A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

High performance subgraph mining in molecular compounds

Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiver-initiated, load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening dataset, where the approach attains close-to linear speedup in a network of workstations.

Efficient mining of discriminative molecular fragments

Frequent pattern discovery in structured data is receiving an increasing attention in many application areas of sciences. However, the computational complexity and the large amount of data to be explored often make the sequential algorithms unsuitable. In this context high performance distributed computing becomes a very interesting and promising approach. In this paper we present a parallel formulation of the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The application is characterized by a highly irregular tree-structured computation. No estimation is available for task workloads, which show a power-law distribution in a wide range. The proposed approach allows dynamic resource aggregation and provides fault and latency tolerance. These features make the distributed application suitable for multi-domain heterogeneous environments, such as computational Grids. The distributed application has been evaluated on the well known National Cancer Institute’s HIV-screening dataset.

Livelihood diversification and the expansion of artisanal mining in rural Tanzania: drivers and policy implications

This paper provides an extended analysis of livelihood diversification in rural Tanzania, with special emphasis on artisanal and small-scale mining (ASM). Over the past decade, this sector of industry, which is labour-intensive and comprises an array of rudimentary and semi-mechanized operations, has become an indispensable economic activity throughout Sub-Saharan Africa, providing employment to a host of redundant public sector workers, retrenched large-scale mine labourers and poor farmers. In many of the region’s rural areas, it is overtaking subsistence agriculture as the primary industry. Such a pattern appears to be unfolding within the Morogoro and Mbeya regions of southern Tanzania, where findings from recent research suggest that a growing number of smallholder farmers are turning to ASM for employment and financial support. It is imperative that national rural development programmes take this trend into account and provide support to these people.

Data-mining chess databases

This is a report on the data-mining of two chess databases, the objective being to compare their sub-7-man content with perfect play as documented in Nalimov endgame tables. Van der Heijden’s ENDGAME STUDY DATABASE IV is a definitive collection of 76,132 studies in which White should have an essentially unique route to the stipulated goal. Chessbase’s BIG DATABASE 2010 holds some 4.5 million games. Insight gained into both database content and data-mining has led to some delightful surprises and created a further agenda.

Restructuring and rescaling water governance in mining contexts: the co-production of waterscapes in Peru

The governance of water resources is prominent in both water policy agendas and academic scholarship. Political ecologists have made important advances in reconceptualising the relationship between water and society. Yet, while they have stressed both the scalar dimensions, and the politicised nature, of water governance, analyses of its scalar politics are relatively nascent. In this paper, we consider how the increased demand for water resources by the growing mining industry in Peru reconfigures and rescales water governance. In Peru, the mining industry’s thirst for water draws in, and reshapes, social relations, technologies, institutions and discourses that operate over varying spatial and temporal scales. We develop the concept of waterscape to examine these multiple ways in water is co-produced through mining, and become embedded in changing modes and structures of water governance, often beyond the watershed scale. We argue that an examination of waterscapes avoids the limitations of thinking about water in purely material terms, structuring analysis of water issues according to traditional spatial scales and institutional hierarchies, and taking these scales and structures for granted.

The data-mining of studies database 'HHdbIV'

This article clarifies what was done with the sub-7-man positions in data-mining Harold van der Heijden's 'HHdbIV' database of chess studies prior to its publication. It emphasises that only positions in the main lines of studies were examined and that the information about uniqueness of move was not incorporated in HHdbIV. There is some reflection on the separate technical and artistic dimensions of study evaluation.

‘Cursed’ communities? Corporate Social Responsibility (CSR), company towns and the mining industry in Namibia

This article examines Corporate Social Responsibility (CSR) and mining community development, sustainability and viability. These issues are considered focussing on current and former company-owned mining towns in Namibia. Historically company towns have been a feature of mining activity in Namibia. However, the fate of such towns upon mine closure has been and remains controversial. Declining former mining communities and even ghost mining towns can be found across the country. This article draws upon research undertaken in Namibia and considers these issues with reference to three case study communities. This article examines the complexities which surround decision-making about these communities, and the challenges faced in efforts to encourage their sustainability after mining. In this article, mine company engagements through CSR with the development, sustainability and viability of such communities are also critically discussed. The role, responsibilities, and actions of the state in relation to these communities are furthermore reflected upon. Finally, ways forward for these communities are considered.

Occupying the margins: Labour integration and social exclusion in artisanal mining in Tanzania

This article examines the marginal position of artisanal miners in sub-Saharan Africa, and considers how they are incorporated into mineral sector change in the context of institutional and legal integration. Taking the case of diamond and gold mining in Tanzania, the concept of social exclusion is used to explore the consequences of marginalization on people's access to mineral resources and ability to make a living from artisanal mining. Because existing inequalities and forms of discrimination are ignored by the Tanzanian state, the institutionalization of mineral titles conceals social and power relations that perpetuate highly unequal access to resources. The article highlights the complexity of these processes, and shows that while legal integration can benefit certain wealthier categories of people, who fit into the model of an 'entrepreneurial small-scale miner', for others adverse incorporation contributes to socio-economic dependence, exploitation and insecurity. For the issue of marginality to be addressed within integration processes, the existence of local forms of organization, institutions and relationships, which underpin inequalities and discrimination, need to be recognized.