In northeast Thailand, salinization caused by the discharge of salty groundwater is a serious problem. Locations where groundwater flows into surface water must be identified before measures against salinization can be taken. Radon-222 (222Rn) is a useful indicator for determining areas of groundwater discharge. We measured222Rn concentrations in surface waters in the region and found that groundwater flows into streams and lakes in low-elevation areas (below 180 m) . Our results agree with the results of published simulations of groundwater flow.
We collected atmospheric depositions along the altitudinal gradient on Mt. Emei, China. This study was intended to estimate the deposition rate of the major ionic components by below-cloud scavenging using their altitude distribution of Mt. Emei, which is located in a region of severe air pollution. The precipitation rate tends to increase because of cloud deposition (1500-2500 m) . The atmospheric depositions collected at St. 12, 13 and 17 seemed to evaporate from the altitude distribution pattern of δD and precipitation rate. The deposition flux of ionic components increased at lower altitudes, without dependence on precipitation rate. The main ionic components that influenced atmospheric deposition in this region were SO42-, NO3-, NH4+ and Ca2+. We estimated the increase rate in ionic components by below-cloud scavenging based on the altitude distribution of ion concentrations, except NH4+, which did not show good correlation with the first approximation. Respective rates of increase in SO42-, NO3-and Ca2+were 5.33, 1.36 and 9.51 μeq·L-1, when raindrops fell 100m.
We examined image co-registration techniques based on mutual information (MI) and normalized mutual information (NMI) to registrate two SPECT images with localized differences in brain activity. Simulations were performed by 100 trials with the random initial mismatch of ±20° and ±45 mm for a normal perfusion model (NRM) and a pathological perfusion model with a hemisphere defect (HSD) . In the HSD, activity in the defect region was reduced to be 75% (HSD75%), 50% (HSD50%), and 25% (HSD25%) of normal value. In the MI-based registration for the NRM and NRM dataset, no biases were observed (≤-0.06°, ≤0.06 mm) and the SDs were very small (≤0.07°, ≤0.04 mm) . In the registration for the NRM and HSD dataset, the biases were slightly larger (≤-0.18°, ≤0.34 mm for HSD75%, ≤-0.23°, ≤=0.45 mm for HSD50%, ≤-0.23°, ≤0.18 mm for HSD25%) in comparison with the results of registration for the NRM and NRM dataset. The accuracy of the NMI was almost identical to that of the MI. The entropy-based registration techniques are relatively unaffected by localized differences in brain activity.