Recently, many researchers have used graph theory to study the aberrant brain structures in Alzheimer's disease (AD) and have made great progress. However, the characteristics of the cortical network in Mild Cognitive Impairment (MCI) are still largely unexplored. In this study, the gray matter volumes obtained from magnetic resonance imaging (MRI) for all brain regions except the cerebellum were parcellated into 90 areas using the automated anatomical labeling (AAL) template to construct cortical networks for 98 normal controls (NCs), 113 MCIs and 91 ADs. The measurements of the network properties were calculated for each of the three groups respectively. We found that all three cortical networks exhibited small-world properties and those strong interhemispheric correlations existed between bilaterally homologous regions. Among the three cortical networks, we found the greatest clustering coefficient and the longest absolute path length in AD, which might indicate that the organization of the cortical network was the least optimal in AD. The small-world measures of the MCI network exhibited intermediate values. This finding is logical given that MCI is considered to be the transitional stage between normal aging and AD. Out of all the between-group differences in the clustering coefficient and absolute path length, only the differences between the AD and normal control groups were statistically significant. Compared with the normal controls, the MCI and AD groups retained their hub regions in the frontal lobe but showed a loss of hub regions in the temporal lobe. In addition, altered interregional correlations were detected in the parahippocampus gyrus, medial temporal lobe, cingulum, fusiform, medial frontal lobe, and orbital frontal gyrus in groups with MCI and AD. Similar to previous studies of functional connectivity, we also revealed increased interregional correlations within the local brain lobes and disrupted long distance interregional correlations in groups with MCI and AD.

Impacts of land use and climate change on runoff were investigated by studying the runoff in the Yarlung Zangbo River basin, China. Trends in precipitation, mean air temperature, and runoff were analysed by non‐parametric Mann‐Kendall tests. Land‐use changes were examined with land‐use transition matrix and geographic information system tools. Land‐use and climate changes showed several characteristics, including increased reforestation, decreased grassland, retreat of glaciers and increased desertification. Human activity caused great impact, especially within densely populated regions and cities. Reforestation and degradation of grasslands were more frequent than deforestation and cultivation of grasslands. Annual mean air temperature, precipitation and runoff showed increasing trends between 1974 and 2000. The impacts of land use and climate change on runoff had different effects depending on region and season. In the season of freezing, climate change clearly affected runoff within regions that experienced precipitation. Altered evapotranspiration accounted for about 80 per cent of runoff changes, whereas land‐use changes appear to have had greatest impact on runoff changes within regions that have inconsistent relationships between runoff and climate change. It was demonstrated that afforestation leads to increased runoff in dry seasons. It was estimated that glacier snow melt has caused annual runoff to increase at least 6·0 mm/10yr, 2·1 mm/10yr and 1·7 mm/10yr in Regions 1, 3 and 4, respectively, whereas evapotranspiration caused annual runoff to decrease at least 7·4 mm/10yr in Region 2. Copyright © 2012 John Wiley & Sons, Ltd.

[1] A multi-criteria score-based method is developed to assess General Circulation Model (GCM) performance at the regional scale. Application of the method assessing 25 GCM simulations of monthly mean sea level pressure (MSLP) and air temperature, and monthly and annual rainfall over the southeastern Australia region for 1960/1961-1999/2000 indicate that GCMs usually simulate monthly temperature better than monthly rainfall and mean sea level pressure. For example, the mean observed annual temperature for the study region is 16.7 C while the median and mean values of 25 GCMs are 16.8 and 16.9 C, respectively, and 24 GCMs (except BCC:CM1) can reproduce the annual cycle of temperature accurately, with a minimum correlation coefficient of 0.99. In contrast, the mean observed annual rainfall for the study region is 502 mm, whereas the GCM values vary from 195 to 807 mm, and 12 out of 25 GCMs produce a negative correlation coefficient of monthly rainfall annual cycle. However, GCMs overestimate trend magnitude for temperature, but underestimate for rainfall. The observed annual temperature trend is +0.007 C/yr, while both the median and mean GCM values are +0.013 C/yr, which is almost double the observed magnitude. The observed annual rainfall trend is +0.62mm/yr, while the median and mean values of 25 GCMs are 0.21and 0.36mm/yr, respectively. This demonstrates the advantages of using multi-criteria to assess GCMs performance. The method developed in this study can easily be extended to different study regions and results can be used for better informed regional climate change impact analysis.

Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

This study focuses on the chemical composition, and the factors controlling it, of the high mountain-rivers in the source region of the Yangtze River on the Tibetan Plateau. By comprehensive and systematic analysis, the chemical signatures, spatial variations of water quality, as well as the factors controlling them are studied. The value of the average total dissolved solids (TDS) is 778 mg/l, ranging from 117 to 5496 mg/l. In order of decreasing concentration, the main cations are Na try of the river water is controlled by lithogenic weathering processes. The Na-normalized ratio end-member diagram indicates that the weathering of silicates and carbonates is relatively significant, on the whole. There exists pronounced regional heterogeneity in the water chemistry and the factors affecting it. The northern rivers, including Chumaer He, Beilu He, and Ranchiqu, are mainly affected by evaporation and crystallization processes, while the southern rivers (Tuotuo He, Gaerqu, and Buqu) show effects from the weathering of carbonates and silicates.

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