Numerical simulation of dam construction using low-CO<Subscript>2</Subscript>-emission concrete

Cement production gives rise to CO₂ emissions generated by the calcination of CaCO₃ and by the combustion of fossil fuels, being responsible for about 5% of the global CO₂ emissions. These emissions can be substantially reduced if cement replacement materials are used. In this paper two residual ashes that can be used as mineral additions are considered: sugar cane bagasse ash and rice husk ash. A case study of the construction of a dam with a blended material composed by cement and these two ashes is presented, indicating the potentiality of its use for civil engineering applications. The analyses were performed using experimental and numerical tools developed on the basis of a thermo-chemo-mechanical model. This model considers the coupling, within the theory of thermodynamics, of the several phenomena that intervene in the hydration process, namely, exothermicity, thermo-activation, chemo-plasticity, evolution of thermal and mechanical properties with the hydration reaction, which includes creep and relaxation.     

DC conductivity study of polyaniline and poly(acrylonitrile-butadiene-styrene) blends

In this study, conducting blends of poly(acrylonitrile-butadiene-styrene) and polyaniline doped with dodecylbenzene sulfonic acid were prepared by solution blending. In order to understand the electrical conduction mechanism of the samples, DC electrical conductivity measurements of the blends were carried out in the temperature range of 80–320 K. The experimental results fit well with Mott's model of three-dimensional variable range hopping conduction. The values of Mott's temperature, density of states at the Fermi energy, average hopping distance and barrier height for the composites were calculated and presented.     

PV–wind hybrid system performance: A new approach and a case study

Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV–Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV–Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV–Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV–Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work.     

Rational spatio-temporal strategies for controlling a Chagas disease vector in urban environments

The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments.     

The effect of low number of points in clustering validation via the negentropy increment

We recently introduced the negentropy increment, a validity index for crisp clustering that quantifies the average normality of the clustering partitions using the negentropy. This index can satisfactorily deal with clusters with heterogeneous orientations, scales and densities. One of the main advantages of the index is the simplicity of its calculation, which only requires the computation of the log-determinants of the covariance matrices and the prior probabilities of each cluster. The negentropy increment provides validation results which are in general better than those from other classic cluster validity indices. However, when the number of data points in a partition region is small, the quality in the estimation of the log-determinant of the covariance matrix can be very poor. This affects the proper quantification of the index and therefore the quality of the clustering, so additional requirements such as limitations on the minimum number of points in each region are needed. Although this kind of constraints can provide good results, they need to be adjusted depending on parameters such as the dimension of the data space. In this article we investigate how the estimation of the negentropy increment of a clustering partition is affected by the presence of regions with small number of points. We find that the error in this estimation depends on the number of points in each region, but not on the scale or orientation of their distribution, and show how to correct this error in order to obtain an unbiased estimator of the negentropy increment. We also quantify the amount of uncertainty in the estimation. As we show, both for 2D synthetic problems and multidimensional real benchmark problems, these results can be used to validate clustering partitions with a substantial improvement.     

Adapting maize production to climate change in sub-Saharan Africa

Given the accumulating evidence of climate change in sub-Saharan Africa, there is an urgent need to develop more climate resilient maize systems. Adaptation strategies to climate change in maize systems in sub-Saharan Africa are likely to include improved germplasm with tolerance to drought and heat stress and improved management practices. Adapting maize systems to future climates requires the ability to accurately predict future climate scenarios in order to determine agricultural responses to climate change and set priorities for adaptation strategies. Here we review the projected climate change scenarios for Africa’s maize growing regions using the outputs of 19 global climate models. By 2050, air temperatures are expected to increase throughout maize mega- environments within sub-Saharan Africa by an average of 2.1°C. Rainfall changes during the maize growing season varied with location. Given the time lag between the development of improved cultivars until the seed is in the hands of farmers and adoption of new management practices, there is an urgent need to prioritise research strategies on climate change resilient germplasm development to offset the predicted yield declines.     

Studies on the interactions between bovine β-lactoglobulin and chitosan at the solid-liquid interface

Chitosan ultrathin films have been formed on polycrystalline Au substrates using the LbL technique with the purpose of studying its interaction with bovine β-lactoglobulin (β-LG) at the solid-liquid interface. The immobilization of chitosan was followed by Quartz Crystal Microbalance with energy dissipation (QCM-D), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS). The behavior of the chitosan films in the presence of β-LG solutions with different bulk concentrations ([β-LG]), ionic strength (I), and pH has been investigated using the same techniques plus Atomic Force Microscopy (AFM). The results showed that for pHs lower than protein's pI, weak intermolecular forces (H bonding, Van der Waals, hydrophobic, etc.) are established between β-LG and chitosan (especially close to the pI) leading to low coverage nonspecific adsorption. On the contrary when pH > pI, strong ionic bonding through attractive electrostatic interactions lead to high coverage adsorbed phases composed of large β-LG aggregates. The adsorption process was shown to consist of a relatively fast step (in which these interactions are predominant) which is followed, once the β-LG monolayer is exceeded, by the slow formation of thicker and increasingly viscoelastic films through β-LG self-aggregation. QCM-D and AFM experiments unveiled the role of [β-LG] and I on the formation of these aggregates. The adsorption isotherm built from impedance data in the medium-low [β-LG] range (0.001-0.3 mg mL⁻¹), showed good fitting to the Langmuir model confirming that the formation of one β-LG monolayer is achieved in this concentration range.     

A satellite navigation system to improve the management of intermodal drayage

The intermodal transport chain can become more efficient by means of a good organization of the drayage movements. Drayage in intermodal container terminals involves the pick up or delivery of containers at customer locations, and the main objective is normally the assignment of transportation tasks to the different vehicles, often with the presence of time windows. The literature shows some works on centralized drayage management, but most of them consider the problem only from a static and deterministic perspective, whereas the work we present here incorporates the knowledge of the real-time position of the vehicles, which permanently enables the planner to reassign tasks in case the problem conditions change. This exact knowledge of position of the vehicles is possible thanks to a geographic positioning system by satellite (GPS, Galileo, Glonass), and the results show that this additional data can be used to dynamically improve the solution.     

Sensory acceptability of slow fermented sausages based on fat content and ripening time

Low fat dry fermented sausages were manufactured using controlled ripening conditions and a slow fermented process. The effect of fat content and ripening time on the chemical, colour, texture parameters and sensory acceptability was studied. The fat reduction in slow fermented sausages produced an increase in the pH decline during the first stage of the process that was favoured by the higher water content of the low fat sausages. Fat reduction did not affect the external appearance and there was an absence of defects but lower fat content resulted in lower sausage lightness. The sausage texture in low fat sausages caused an increase in chewiness and at longer ripening times, an increase in hardness. The sensory acceptability of the fermented sausages analyzed by internal preference mapping depended on the different preference patterns of consumers. A group of consumers preferred sausages with high and medium fat content and high ripening time. The second group of consumers preferred sausages with low ripening time regardless of fat content except for the appearance, for which these consumers preferred sausages of high ripening time. Finally, the limit to produce high acceptability low fat fermented sausages was 16% fat content in the raw mixture that is half the usual content of dry fermented sausages.     

Reducing channel change delay in IPTV by predictive pre-joining of TV channels

One of the major concerns of IPTV network deployment is channel change delay (also known as zapping delay). This delay can add up to 2 s or more, and its main culprits are synchronisation and buffering of the media streams. Proving the importance of the problem is the already significant amount of literature addressing it. We start this paper with a survey of techniques proposed to reduce IPTV channel change delay.Then, by analysing an extensive dataset from an operational IPTV provider - comprising 255 thousand users, 150 TV channels, and covering a 6-month period - we have observed that most channel switching events are relatively predictable: users very frequently switch linearly, up or down to the next TV channel. This fact motivated us to use this dataset to analyse in detail a specific type of solutions to this problem, namely, predictive pre-joining of TV channels. In these schemes each set top box (STB) simultaneously joins additional multicast groups (TV channels) along with the one that is requested by the user. If the user switches to any of these channels the switching latency is virtually eliminated, not affecting therefore user's experience.We start by evaluating a simple scheme, where the neighbouring channels (i.e., channels adjacent to the requested one) are pre-joined by the STB during zapping periods. Notwithstanding the simplicity of this scheme, trace-driven simulations show that the zapping delay can be virtually eliminated for a significant percentage of channel switching requests. For example, when sending the previous and the next channel concurrently with the requested one, for only 1 min after a zapping event, switching delay is eliminated for close to half of all channel switching requests. Importantly, this result is achieved with a negligible increase of bandwidth utilisation in the access link. Other more complex schemes where user behaviour is tracked were also evaluated, but the improvement over the simple scheme was insignificant.