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Tailing storage facilities are very complex structures whose failure generally leads to catastrophic consequences in terms of casualties, serious environmental impacts on local biodiversity, and disruptions in the mineral supply. For this reason, structures at risk must be reinforced or decommissioned. One possible option is its reinforcement with compacted filtered tailings stabilized with binders. Alkali-activated binders provide a more sustainable solution than ordinary Portland cement but require an optimization of the tailing–binder mixture, which, in some cases, can lead to a substantial experimental effort. Statistical models have been used to reduce the number of those experiments, but a rational design methodology is still lacking. This methodology to define the right mixture for a required strength should consider both the mixture components and in situ conditions. In this paper, response surface methods were used to plan and interpret unconfined compression strength test results on an iron tailing stabilized with alkali-activated binders. It was concluded that the fly ash content was the most important parameter, followed by the liquid content and sodium hydroxide concentration. From the obtained results, several statistical models were defined and compared according to the definition of a strength prediction model based on a mixture index parameter. It was interesting to observe that models with the porosity cement index still provide reasonable adjustment even when different tailings' water contents are considered. [ABSTRACT FROM AUTHOR]

The use of SCC in Europe began in the 1990s and was mainly promoted by the precast industry. Precast companies generally prefer high early-strength concrete mixtures to accelerate their production rate, reducing the demoulding time. From a materials science point of view, self-compacting and high early-strength concrete mixes may be challenging because they present contradicting mixture design requirements. For example, a low water/binder ratio (w/b) is key to achieving high early strength. However, it may impact the self-compacting ability, which is very sensitive to Vw/Vp. As such, the mixture design can be complex. The design of the experimental approach is a powerful tool for designing, predicting, and optimising advanced cement-based materials when several constituent materials are employed and multi-performance requirements are targeted. The current work aimed at fitting models to mathematically describe the flow ability, viscosity, and mechanical strength properties of high-performance self-compacting cement-based mortars based on a central composite design. The statistical fitted models revealed that Vs/Vm exhibited the strongest (negative) effect on the slump-flow diameter and T-funnel time. Vw/Vp showed the most significant effect on mechanical strength. Models were then used for mortar optimisation. The proposed optimal mixture represents the best compromise between self-compacting ability—a flow diameter of 250 mm and funnel time equal to 10 s—and compressive strength higher than 50 MPa at 24 h without any special curing treatment. [ABSTRACT FROM AUTHOR]

This work presents a microscopic stochastic simulation model that emulates the traffic movements at signalized intersections with semiactuated signal operation. This model uses the Awesim simulation language to implement and facilitate the evaluation of numerous operating scenarios associated with vehicle-actuated control strategies at isolated signalized intersections. A validation procedure was carried out, field data were collected, and delays and green times observed in the field were compared with those estimated by the simulation program. The adequacy of this model to represent real-world systems is shown. The structure of the model and the steps that were followed for its implementation are described. The relationship between simulated delays and the delays obtained from applying the Highway Capacity Manual model is analyzed. The impact of the maximum green time and the unit extension of green time assigned by the actuated system to each phase is also assessed. The model outputs include measures of effectiveness such as total vehicular delay, average green time, and average cycle length. DOI: l0.1061/(ASCE)TE.1943-5436.0000124 CE Database subject headings: Simulation; Traffic signals; Traffic delay; Stochastic models; Intersections. Author keywords: Simulation; Traffic signals; Traffic delay; Stochastic models; Intersections.

A signalized intersection regulated by pre-timed control in an urban traffic network is considered. A method for computing the mean delay of vehicles based on the theory of queues with server vacations is adapted from the existing literature and an algorithm for numerical implementation is proposed. Arrivals are assumed to occur according to a batch Markovian arrival process (BMAP). The proposed algorithm is an alternative to the previous methods that includes a numerical improvement in the computation of the queue invariant probabilities. In the case of isolated intersections we compare the new algorithm with other traffic models, including simulation model, Webster model and the Highway Capacity Manual model. The mean delay of vehicles given by the new algorithm is a short distance away from the mean delay obtained in the simulations. The approximation for large flows given by the proposed algorithm is as good as the Highway Capacity Manual model and with no need to tune unknown parameters. Our results are of interest for traffic engineers, since other approaches have been subject to criticism when flows near capacity are involved. [ABSTRACT FROM AUTHOR]

Introduction: The knowledge of transmission, prevention and symptoms of malaria is essential for travellers' safety. In real life, what do Portuguese travellers know about malaria before a Travel Medicine consultation? How can we, through this consultation, improve their knowledge?, Material and Methods: Before an appointment with a specialist in Travel Medicine, 80 adult travellers filled a questionnaire that included demographic aspects, characteristics of the trip and knowledge about malaria. Data were analysed using descriptive statistics and multifactorial variance analysis., Results: The travellers' ages fell in the range 20 - 80 years, 51% were male and 74% of the travellers had a university degree level of education. For 74% of the travellers, this was the first Travel Medicine consultation. Half of the travellers planed trips lasting no more than 14 days, mainly for tourism. The average percentage of correct answers about malaria given by a traveller was 63%. Travellers who had previously attended a Travel Medicine appointment exhibit a statistically significant difference in knowledge comparing to those who attend Travel Medicine appointment for the first time, and this was more evident in the sample composed of travellers without higher education. The clinical manifestations and prevention had the lowest number of correct answers among the travellers., Discussion: These travellers appear to have good knowledge about malaria but some misconceptions prevail., Conclusion: The Travel Medicine consultation seems important to raise awareness in the population about malaria, particularly for travellers without higher education. The prevention and the recognition of malaria symptoms must be prioritized during Travel Medicine consultations and the information given adapted to the traveller's characteristics.