Mining in Alaska - environmental impact and pollution control

Environmental factors affecting mining are difficult to establish in Alaska due to the absence of large scale hard rock mining activities at the present time. Currently, experience is gathered from (and to a large degree based on) construction of above ground facilities such as roads, pipelines, and buildings. Past mining activities appear to have had little lasting effect on the natural environment, the exceptions being mine tailings and surface structures. This report, sponsored by the U. S. Bureau of Mines, present general engineering activities, considers the interaction of permafrost and underground mining, summarizes available literature and indicates possible environmental problems that might be encountered in Alaska based on Scandinavian experiences in large-scale northern mining operations. How the Scandinavians are solving their problems is also discussed.This paper was sponsored by the U. S. Bureau of Mines, Contract No. 0133059.Abstract -- Acknowledgements -- Table of contents -- List of illustrations -- List of tables -- Introduction -- Climatic parameters -- Alaska climatic regions -- Construction and mining activities in the Arctic -- General -- Cold weather construction practices -- Permafrost and underground mining operations -- Environmental considerations -- Mining and exploration parameters -- Conclusions -- Recommendations -- Bibliography -- Appendices -- Appendix A: Bibliography - Lost River area -- Appendix B: Mining and environmental considerations as practiced in Norway and Sweden -- Appendix C: Mining vs. the environment -- Figure 1. Alaska climatic regions -- Figure 2. Index map showing mining districts examined -- List of tables -- Table 1. Dates of break-up and freeze-up

Inverse Statistics in the Foreign Exchange Market

We investigate intra-day foreign exchange (FX) time series using the inverse statistic analysis developed in [1,2]. Specifically, we study the time-averaged distributions of waiting times needed to obtain a certain increase (decrease) $\rho$ in the price of an investment. The analysis is performed for the Deutsch mark (DM) against the $US for the full year of 1998, but similar results are obtained for the Japanese Yen against the$US. With high statistical significance, the presence of "resonance peaks" in the waiting time distributions is established. Such peaks are a consequence of the trading habits of the markets participants as they are not present in the corresponding tick (business) waiting time distributions. Furthermore, a new {\em stylized fact}, is observed for the waiting time distribution in the form of a power law Pdf. This result is achieved by rescaling of the physical waiting time by the corresponding tick time thereby partially removing scale dependent features of the market activity.Comment: 8 pages. Accepted Physica

Inverse Statistics for Stocks and Markets

In recent publications, the authors have considered inverse statistics of the Dow Jones Industrial Averaged (DJIA) [1-3]. Specifically, we argued that the natural candidate for such statistics is the investment horizons distribution. This is the distribution of waiting times needed to achieve a predefined level of return obtained from detrended historic asset prices. Such a distribution typically goes through a maximum at a time coined the {\em optimal investment horizon}, $\tau^*_\rho$, which defines the most likely waiting time for obtaining a given return $\rho$. By considering equal positive and negative levels of return, we reported in [2,3] on a quantitative gain/loss asymmetry most pronounced for short horizons. In the present paper, this gain/loss asymmetry is re-visited for 2/3 of the individual stocks presently in the DJIA. We show that this gain/loss asymmetry established for the DJIA surprisingly is {\em not} present in the time series of the individual stocks. The most reasonable explanation for this fact is that the gain/loss asymmetry observed in the DJIA as well as in the SP500 and Nasdaq are due to movements in the market as a whole, {\it i.e.}, cooperative cascade processes (or ``synchronization'') which disappear in the inverse statistics of the individual stocks.Comment: Revtex 13 pages, including 15 figure

Oscillatory regimes of the thermomagnetic instability in superconducting films

The stability of superconducting films with respect to oscillatory precursor modes for thermomag- netic avalanches is investigated theoretically. The results for the onset threshold show that previous treatments of non-oscillatory modes have predicted much higher thresholds. Thus, in film supercon- ductors, oscillatory modes are far more likely to cause thermomagnetic breakdown. This explains the experimental fact that flux avalanches in film superconductors can occur even at very small ramping rates of the applied magnetic field. Closed expressions for the threshold magnetic field and temperature, as well oscillation frequency, are derived for different regimes of the oscillatory thermomagnetic instability.Comment: 5 pages, 5 figure

Dendritic flux avalanches in rectangular superconducting films -- numerical simulations

Dendritic flux avalanches is a frequently encountered instability in the vortex matter of type II superconducting films at low temperatures. Previously, linear stability analysis has shown that such avalanches should be nucleated where the flux penetration is deepest. To check this prediction we do numerical simulations on a superconducting rectangle. We find that at low substrate temperature the first avalanches appear exactly in the middle of the long edges, in agreement with the predictions. At higher substrate temperature, where there are no clear predictions from the theory, we find that the location of the first avalanche is decided by fluctuations due to the randomly distributed disorder.Comment: 3 pages, 2 figure

Classification of Possible Finite-Time Singularities by Functional Renormalization

Starting from a representation of the early time evolution of a dynamical system in terms of the polynomial expression of some observable f (t) as a function of the time variable in some interval 0 < t < T, we investigate how to extrapolate/forecast in some optimal stability sense the future evolution of f(t) for time t>T. Using the functional renormalization of Yukalov and Gluzman, we offer a general classification of the possible regimes that can be defined based on the sole knowledge of the coefficients of a second-order polynomial representation of the dynamics. In particular, we investigate the conditions for the occurence of finite-time singularities from the structure of the time series, and quantify the critical time and the functional nature of the singularity when present. We also describe the regimes when a smooth extremum replaces the singularity and determine its position and amplitude. This extends previous works by (1) quantifying the stability of the functional renormalization method more accurately, (2) introducing new global constraints in terms of moments and (3) going beyond the ``mean-field'' approximation.Comment: Latex document of 18 pages + 7 ps figure

Optimal Investment Horizons for Stocks and Markets

The inverse statistics is the distribution of waiting times needed to achieve a predefined level of return obtained from (detrended) historic asset prices \cite{optihori,gainloss}. Such a distribution typically goes through a maximum at a time coined the {\em optimal investment horizon}, $\tau^*_\rho$, which defines the most likely waiting time for obtaining a given return $\rho$. By considering equal positive and negative levels of return, we reported in \cite{gainloss} on a quantitative gain/loss asymmetry most pronounced for short horizons. In the present paper, the inverse statistics for 2/3 of the individual stocks presently in the DJIA is investigated. We show that this gain/loss asymmetry established for the DJIA surprisingly is {\em not} present in the time series of the individual stocks nor their average. This observation points towards some kind of collective movement of the stocks of the index (synchronization).Comment: Subm. to Physica A as Conference Proceedings of Econophysics Colloquium, ANU Canberra, 13-17 Nov. 2005. 6 pages including figure