The concept of sustainability requires that waste-modified materials also demonstrate adequate sustainability. This paper examines the effect of modifying cement concrete with waste lime dust on the course of concrete carbonation. The waste dust comes from the dedusting of aggregate for use in HMA – Hot Mixture Asphalt. The aim of the study was to examine whether the partial replacement of sand with waste powder would have a negative effect on the potential durability of a reinforced concrete element made of this concrete. To determine the extent of carbonation, an experimental plan was prepared including the execution of concretes with varying levels of substitution and a variable water/cement ratio. In order to identify long term influence the test was performed as indicated in EN 12390-12, but with the test time extended to 560 days. The results obtained were statistically analysed and the predicted maximum extent of carbonation depending on the level of substitution and the water/cement ratio was determined. The analysis indicates that it is possible to substitute sand with waste limestone dust without having a negative impact on the extent of carbonation, and thus on the durability of the reinforced concrete structure.

Net phytoplankton cell numbers in 50 m water column of Admiralty Bay ranged between 0.2 x 10 5 x m-2 on 24 August 1990 and 2.3 x 10 7 x m-2 on 15 November 1990. Cluster analysis has confirmed the presence of two groups of samples: spring and summer ones (October to April), rich in cells and in species, and, on the other hand, winter samples (June to August) impoverished in algae. Spring and summer fluctuations of diatoms were mainly due to Corethron criophilum, Rhizosolenia alata and its varieties, R. hebetata f. semispina, Thalassiosira spp., Chaetoceros spp., and Nitzschia spp. (Fragilariopsis and Pseudonitzschia groups). The abundance and succession of species in Admiralty Bay reflect seasonal differences in diatom growth; they also reflect mixed populations of the Weddell and Bellingshausen seas entering Admiralty Bay via Bransfield Strait. Striking poverty of algae in some summer samples can most likely be attributed to zooplankton grazing.

This paper proposes a soft sensing method of least squares support vector machine (LS-SVM) using temperature time series for gas flow measurements. A heater unit has been installed on the external wall of a pipeline to generate heat pulses. Dynamic temperature signals have been collected upstream of the heater unit. The temperature time series are the main secondary variables of soft sensing technique for estimating the flow rate. A LS-SVM model is proposed to construct a non-linear relation between the flow rate and temperature time series. To select its inputs, parameters of the measurement system are divided into three categories: blind, invalid and secondary variables. Then the kernel function parameters are optimized to improve estimation accuracy. The experiments have been conducted both in the single-pulse and multiple-pulse heating modes. The results show that estimations are acceptable.