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Climate change and related extreme events have become global challenges in ensuring sustainable development. This affects water availability and agricultural production, particularly in developing countries. This study explored the factors affecting farmers' adaptation mechanisms to climate change in different agro-ecological zones of the Bure Zuria district of northwestern Ethiopia. A household survey, focus group discussion, key informant interviews, and observations were used to acquire primary data on farmers' socioeconomic and demographic characteristics, adaptation strategies and potential barriers. About 190 randomly selected households from different agro-ecologies were included in this study. Moreover, reports and published sources were used to acquire secondary data. Data were analyzed using a multinomial logit regression model and descriptive statistics. The results indicated that soil and water conservation practices (26.7%) were the main adaptation responses in highland agro-ecology. In contrast, supplementary feeding for livestock (56%) was the main adaptation response to the adverse effects of climate extremes in lowland agro-ecology. Farmers identified land scarcity (25.84%) and shortage of water for irrigation (28.57%) as major barriers to adaptation in the highland and lowland agro-ecologies, respectively. In addition, agro-ecology, education level, age, active labor, number of livestock (TLU), off-farm income, frequency of extension contacts, credit access, and market access were decisive factors affecting farmers’ adaptation mechanisms to withstand extreme climatic events. In conclusion, soil and water conservation practices are more practiced in highland areas than in lowland areas. Because the steepness of farmlands and erodible soils increase farmers' vulnerability to flood hazards in highland areas than in lowland areas. It is suggested that investigations on the climate change-induced gender-differentiated impacts shall be conducted to design all-inclusive and effective responses.

Acid rock drainage (ARD) is a major environmental problem that poses significant environmental risks during and after mining activities. A new methodology for environmental risk assessment based on probability bounds and a geochemical speciation model (PHREEQC) is presented. The methodology provides conservative and non-conservative ways of estimating risk of heavy metals posed to selected endpoints probabilistically, while propagating data and parameter uncertainties throughout the risk assessment steps. The methodology is demonstrated at a minesite located in British Columbia, Canada. The result of the methodology for the case study minesite shows the fate-and-transport of heavy metals is well simulated in the mine environment. In addition, the results of risk characterization for the case study show that there is risk due to transport of heavy metals into the environment., (Copyright © 2015. Published by Elsevier B.V.)

Acid rock drainage (ARD) is a major pollution problem globally that has adversely impacted the environment. Identification and quantification of uncertainties are integral parts of ARD assessment and risk mitigation, however previous studies on predicting ARD drainage chemistry have not fully addressed issues of uncertainties. In this study, artificial neural networks (ANN) and support vector machine (SVM) are used for the prediction of ARD drainage chemistry and their predictive uncertainties are quantified using probability bounds analysis. Furthermore, the predictions of ANN and SVM are integrated using four aggregation methods to improve their individual predictions. The results of this study showed that ANN performed better than SVM in enveloping the observed concentrations. In addition, integrating the prediction of ANN and SVM using the aggregation methods improved the predictions of individual techniques., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Expression of the PD-1 receptor on T cells has been shown to provide an important inhibitory signal that down-modulates peripheral effector responses in normal tissues and tumors. Furthermore, PD-1 up-regulation on chronically activated T cells can maintain them in a partially reversible inactive state. The function of PD-1 in the very early stages of T-cell response to antigen in vivo has not been fully explored. In this study, we evaluate the role of PD-1 and its 2 B7 family ligands, B7-H1 (PD-L1) and B7-DC (PD-L2), in early fate decisions of CD8 T cells. We show that CD8 T cells specific for influenza hemagglutinin (HA) expressed as a self-antigen become functionally tolerized and express high levels of surface PD-1 by the time of their first cell division. Blockade of PD-1 or B7-H1, but not B7-DC, at the time of self-antigen encounter mitigates tolerance induction and results in CD8 T-cell differentiation into functional cytolytic T lymphocytes (CTLs). These findings demonstrate that, in addition to modulating effector functions in the periphery, B7-H1:PD-1 interactions regulate early T-cell-fate decisions.