Sustainable mining, local communities and environmental regulation

Sustainable mining is an objective as well as a tool for balancing economic, social, and environmental considerations. Each of these three dimensions of mining – and sustainable development – has many components, some of which were chosen for closer study in the SUMILCERE project. While there is no single component that in itself provides a definitive argument for or against sustainable mining, the research reveals some that have proven valuable in the process of balancing the different dimensions of sustainability. In the SUMILCERE project, comparative studies enabled us to identify factors such as the following, which are essential when discussing the balancing in practice of the three dimensions of sustainable mining cited above: the framework and functionality of environmental regulation to protect the environment (environmental sustainability); the competitiveness of the mining industry in light of environmental regulation and its enforcement (economic sustainability); public participation and the opportunities local communities have to influence their surroundings, as well as communities’ acceptance of projects (social sustainability) before and during operations; and the protection of Sámi cultural rights in mining projects (social and cultural sustainability). Although each of the three dimensions of sustainability leaves room for discretion in the weight assigned to it, ecological sustainability, protected by smart environmental regulation and minimum standards, sets essential boundaries that leave no room for compromises. Economic and social sustainability are possible only within these limits. Details of the analyses in the Kolarctic area and accounts of the methods used can be found in the cited SUMILCERE articles.publishedVersio

Scenarios for the development of smart grids in the UK: synthesis report

‘Smart grid’ is a catch-all term for the smart options that could transform the ways society produces, delivers and consumes energy, and potentially the way we conceive of these services. Delivering energy more intelligently will be fundamental to decarbonising the UK electricity system at least possible cost, while maintaining security and reliability of supply. Smarter energy delivery is expected to allow the integration of more low carbon technologies and to be much more cost effective than traditional methods, as well as contributing to economic growth by opening up new business and innovation opportunities. Innovating new options for energy system management could lead to cost savings of up to £10bn, even if low carbon technologies do not emerge. This saving will be much higher if UK renewable energy targets are achieved. Building on extensive expert feedback and input, this report describes four smart grid scenarios which consider how the UK’s electricity system might develop to 2050. The scenarios outline how political decisions, as well as those made in regulation, finance, technology, consumer and social behaviour, market design or response, might affect the decisions of other actors and limit or allow the availability of future options. The project aims to explore the degree of uncertainty around the current direction of the electricity system and the complex interactions of a whole host of factors that may lead to any one of a wide range of outcomes. Our addition to this discussion will help decision makers to understand the implications of possible actions and better plan for the future, whilst recognising that it may take any one of a number of forms

Optimal Portfolio Management in Alaska: A Case Study on Risk Characteristics of Environmental Consulting Companies

A Project Submitted in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE in Project ManagementSharp declines in global oil prices have led to a marked contraction in Alaska’s natural resource dependent economy. This, coupled with record the State’s budgetary shortfalls and a decrease in incoming federal dollars, has created a climate where environmental consulting companies must accept riskier projects to balance portfolio growth and security. As a result, companies must adopt a risk-based portfolio management approach as both a high level strategy and a core management practice. It is important to specifically identify projects best suited for an organization’s tolerance for risk based off of the supply and demand of the industry in rapidly changing economic conditions. Therefore, the aims of this project report are to help environmental consulting companies identify risk characteristics and manage their portfolio, as well as develop a tool to guide decision-making and selecting projects best suited for a companies’ portfolio strategy. The results of this research may provide Alaska based environmental companies with a clear understanding of the types of projects that offer both development and financial security for an organization. This research paper will present the methodology, results, and an environmental consulting portfolio management tool.Title Page / Table of Contents / List of Exhibits / Abstract / Introduction / Background / Literature Review / Project Methodology / Research Methodology / Presentation and Analysis of Data from Survey / Data Validation From Survey / Conclusion / Recommendation / Project Conclusion / Recommendations for Further Research / References / Appendi

Fourth Amendment Accommodations: (UN)Compelling Public Needs, Balancing Acts, and the Fiction of Consent

The problems of public housing-including crime, drugs, and gun violence- have received an enormous amount of national attention. Much attention has also focused on warrantless searches and consent searches as solutions to these problems. This Note addresses the constitutionality of these proposals and asserts that if the Supreme Court\u27s current Fourth Amendment jurisprudence is taken to its logical extremes, warrantless searches in public housing can be found constitutional. The author argues, however, that such an interpretation fails to strike the proper balance between public need and privacy in the public housing context. The Note concludes by proposing alternative consent-based regimes that would pass constitutional muster

Is it time to rethink project success?

The notion of success and failure in software projects are confusing. Failure is often considered in the context of the iron triangle as the inability to meet time, cost and performance constraints. Yet, while there is a consensus around the prevalence of project failure, new projects seem destined to repeat past mistakes. This paper tries to advance the discussion by offering a new perspective for reasoning about the meaning of success and the different types of software project failures. The paper advocates rising beyond the fixation with internal parameters of efficiency. It begins by discussing the limited insights from existing project failure surveys, before offering a four level model addressing the essence of successful delivery and operation in software projects and considering the different measures required in order to utilise richer measurements of success

Fourth Amendment Accommodations: (UN)Compelling Public Needs, Balancing Acts, and the Fiction of Consent

The problems of public housing-including crime, drugs, and gun violence- have received an enormous amount of national attention. Much attention has also focused on warrantless searches and consent searches as solutions to these problems. This Note addresses the constitutionality of these proposals and asserts that if the Supreme Court\u27s current Fourth Amendment jurisprudence is taken to its logical extremes, warrantless searches in public housing can be found constitutional. The author argues, however, that such an interpretation fails to strike the proper balance between public need and privacy in the public housing context. The Note concludes by proposing alternative consent-based regimes that would pass constitutional muster

Evaluating the Effect of Public Subsidies on firm R&D activity: an Application to Italy Using the Community Innovation Survey

WP 09/2008; The aim of the paper is twofold: to verify a full policy failure of public support on private R&D effort, when in presence of a potential plurality of public incentives; to compare the most recent econometric methods used for the analysis of the input additionality. Compared to previous studies our work wants to trace out an advance in two directions: adding more robustness by comparing results from various econometric techniques and providing an analysis of the R&D policy effect behind the average results. A by-product of the paper is a taxonomy of the econometric methods used in the literature, according to the structure of the models, the type of dataset and the available policy information. We exploit the third wave of the Community Innovation Survey for Italy (1998-2000) with a sample size of 1,221 supported and 1,319 non-supported firms. Given the used type of data, the article presents two main limits: first, we do not know the level of the subsidy, so that we can control only for the presence of a total crowding-out; second, we can check only the short-run effect of the supporting policy, while an increase in the private R&D effort could be more likely in the medium term. Our results suggest that: 1. the main factors influencing the probability to participate to the incentive policy are R&D experience, human skills, liquidity constraints, but also foreign capital ownership; 2. on average, the total substitution of private funding by the public one is excluded for Italy as a whole, although some cases of total crowding-out are found: low knowledge intensive services, very small firms (10-19 employees) and the auto-vehicle industry. We get, on average, 885 additional thousand Euros of R&D expenditure per firm with a ratio equal to 4.62: it means that if a generic control unit does 1 thousand Euros of R&D expenditure a matched treated does 4.62 thousand Euros. The additionality for the R&D intensity is about 0.014 with a ratio of about 2.67

Towards Automated Performance Bug Identification in Python

Context: Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems. In this work we focused on early detection of performance bugs; our software under study was a real time system used in the advertisement/marketing domain. Goal: Find a simple and easy to implement solution, predicting performance bugs. Method: We built several models using four machine learning methods, commonly used for defect prediction: C4.5 Decision Trees, Na\"{\i}ve Bayes, Bayesian Networks, and Logistic Regression. Results: Our empirical results show that a C4.5 model, using lines of code changed, file's age and size as explanatory variables, can be used to predict performance bugs (recall=0.73, accuracy=0.85, and precision=0.96). We show that reducing the number of changes delivered on a commit, can decrease the chance of performance bug injection. Conclusions: We believe that our approach can help practitioners to eliminate performance bugs early in the development cycle. Our results are also of interest to theoreticians, establishing a link between functional bugs and (non-functional) performance bugs, and explicitly showing that attributes used for prediction of functional bugs can be used for prediction of performance bugs