Lacustrine Arcellinina (Testate Amoebae) as Bioindicators of Arsenic Contamination

Arcellininids (testate amoebae) were examined from 61 surface sediment samples collected from 59 lakes in the vicinity of former gold mines, notably Giant Mine, near Yellowknife, Northwest Territories, Canada to determine their utility as bioindicators of arsenic (As), which occurs both as a byproduct of gold extraction at mines in the area and ore-bearing outcrops. Cluster analysis (Q-R-mode) and detrended correspondence analysis (DCA) reveal five arcellininid assemblages, three of which are related to varying As concentrations in the sediment samples. Redundancy analysis (RDA) showed that 14 statistically significant environmental parameters explained 57 % of the variation in faunal distribution, while partial RDA indicated that As had the greatest influence on assemblage variance (10.7 %; p < 0.10). Stress-indicating species (primarily centropyxids) characterized the faunas of samples with high As concentrations (median = 121.7 ppm, max > 10000 ppm, min = 16.1 ppm, n = 32), while difflugiid dominated assemblages were prevalent in substrates with relatively low As concentrations (median = 30.2 ppm, max = 905.2 ppm, min = 6.3 ppm, n = 20). Most of the lakes with very high As levels are located downwind (N and W) of the former Giant Mine roaster stack where refractory ore was roasted and substantial quantities of As were released (as As2O3) to the atmosphere in the first decade of mining. This spatial pattern suggests that a significant proportion of the observed As, in at least these lakes, are industrially derived. The results of this study highlight the sensitivity of Arcellinina to As and confirm that the group has considerable potential for assessing the impact of As contamination on lakes.

I/Q imbalance in two-way AF relaying: Performance analysis and detection mode switch

This paper studies the impact of in-phase and quadrature-phase imbalance (IQI) in two-way amplify-and-forward (AF) relaying systems. In particular, the effective signal-to-interference-plus-noise ratio (SINR) is derived for each source node, considering four different linear detection schemes, namely, uncompensated (Uncomp) scheme, maximal-ratio-combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) based schemes. For each proposed scheme, the outage probability (OP) is investigated over independent, non-identically distributed Nakagami-m fading channels, and exact closed-form expressions are derived for the first three schemes. Based on the closed-form OP expressions, an adaptive detection mode switching scheme is designed for minimizing the OP of both sources. An important observation is that, regardless of the channel conditions and transmit powers, the ZF-based scheme should always be selected if the target SINR is larger than 3 (4.77dB), while the MRC-based scheme should be avoided if the target SINR is larger than 0.38 (-4.20dB).