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The existing well-known short-term traffic forecasting algorithms require large traffic flow data sets, including information on current traffic scenarios to predict the future traffic conditions. This article proposes a random process traffic volume model that enables estimation and prediction of traffic volume at sites where such large and continuous data sets of traffic condition related information are unavailable. The proposed model is based on a combination of wavelet analysis (WA) and Bayesian hierarchical methodology (BHM). The average daily 'trend' of urban traffic flow observations can be reliably modeled using discrete WA. The remaining fluctuating parts of the traffic volume observations are modeled using BHM. This BHM modeling considers that the variance of the urban traffic flow observations from an intersection vary with the time-of-the-day. A case study has been performed at two busy junctions at the city-centre of Dublin to validate the effectiveness of the strategy. [ABSTRACT FROM AUTHOR]

This article proposes optimization frameworks for discrete road network design considering the land-use transport interaction over time. Unlike existing models, the optimization frameworks can determine the optimal designs automatically without trial-and-error once the objective(s) is/are clearly defined. Moreover, these frameworks allow the evaluation of the impacts of the optimal designs on the related parties including landowners, toll road operators, transit operators, and road users, and help network planners and profit-makers with decision making by eliminating many alternative designs. A numerical study is set up to examine road network design's effects on these related parties under three road construction schemes: exact cost recovery, build-operate-transfer, and cross-subsidization. The results show that the changes in landowner profits are not the same after implementing any scheme. These unequal changes raise the issue of the landowner equity. This implies that the government has to consider trade-offs between parties’ objectives carefully. [ABSTRACT FROM AUTHOR]

In acidifying lakes, pH decreases abruptly in response to acid precipitation events. We tested the hypothesis that, in comparison to a circumneutral lake, phytoplankton photosynthesis in an acidifying lake is less sensitive to a rapid decrease in pH (acid pH shock). Phytoplankton in Plastic Lake, which is undergoing acidification, was characterized by a predominance of Pyrophyta, and phytoplankton photosynthesis decreased to a lesser extent in response to an acid pH shock than the photosynthesis of populations from St. Nora Lake, a circumneutral lake located nearby, in which Pyrrophyta were not abundant. Rates of phytoplankton photosynthesis in acid pH shock experiments were significantly correlated with hydrogen ion but not with dissolved inorganic carbon (DIC) concentrations. Depression of photosynthesis following an acid pH shock occurred in axenic cultures of Chlorella Pyrenoidosa Chick but was not observed in axenic cultures of the acidophilic alga Chlorella saccharophila (Krug.) Nadson or in three species isolated from Plastic Lake. However, the three isolates were not acidophilic during growth. We conclude that phytoplankton in acidifying lakes consists predominantly of species which are tolerant to acid pH for short periods (hours) but cannot grow at these pHs. [ABSTRACT FROM AUTHOR]