Abstract
Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for selecting dynamically the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request, while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to make decisions on tuning the number of samples to improve the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36 and 81 percent) with respect to a static approach, while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, the execution-time speedup is between 1.5x and 5.1x. This speedup is reflected at the infrastructure-level in terms of a reduction of 36 percent of the computing resources needed to support the whole navigation pipeline.

Abstract
Resistive switching behaviour has been demonstrated to be a common characteristic to many materials. In this regard, research teams to date have produced a plethora of different devices exhibiting diverse behaviour, but when system design is considered, finding a 'one-model-fits-all' solution can be quite difficult, or even impossible. However, it is in the interest of the community to achieve more general modelling tools for design that allows a quick model update as devices evolve. Laying the grounds with such a principle, this paper presents an artificial neural network learning approach to resistive switching modelling. The efficacy of the method is demonstrated firstly with two simulated devices and secondly with a 4 mu m(2) amorphous IGZO device. For the amorphous IGZO device, a normalized root-mean-squared error (NRMSE) of 5.66 x 10(-3) is achieved with a [2, 50,50 ,1] network structure, representing a good balance between model complexity and accuracy. A brief study on the number of hidden layers and neurons and its effect on network performance is also conducted with the best NRMSE reported at 4.63 x 10(-3). The low error rate achieved in both simulated and real-world devices is a good indicator that the presented approach is flexible and can suit multiple device types.

Abstract
Over the years, the food industry’s concern to provide safe food that does not cause harm or illness to consumers has increased. The growing demand for the detection of compounds that can contaminate food is increasingly important. Hydrogen peroxide is frequently used as a substance to control the growth of microorganisms in milk, thus increasing its shelf life. Here, a strategy is presented for the detection of hydrogen peroxide as a milk adulterant, using a single shot membrane sensor. The lowest concentration measured with this technique was 0.002% w/w of H2O2 in semi-fat milk.

Abstract
Immersive Interactive 360° videos, experienced through Head-Mounted Displays (HMD), constitute a particular case of VR applications for which it is relatively easy to record content nowadays, and that can be explored as a game format. We therefore explore the idea of using live action 360° videos as the basis for immersive adventure games. In particular, we explore possible interactions in immersive adventure games based on 360° videos, in terms of game elements and mechanics, and the player's interface with those. To support this, we developed a browser-based framework for creating such games, and conducted a user study with a game created specifically for that purpose. The results obtained indicate a high level of satisfaction with the chosen control schemes and game mechanics, and suggest that the framework can be used to create this kind of experience.

Abstract
This paper aims to identify and analyze project management maturity models in order to identify those best suited to be adopted in construction firms. To do so, models from papers available in academic repositories were analyzed. To be successful, the construction business deeply depends on projects outcomes; thus, the implementation of project management maturity models is important for this sector. A maturity model is a valuable technique to assess project management capabilities within a single part of an organization or to assess an organization as a whole. Its main purpose is to provide a means to create a more organized and predictable way for organizations to achieve their goals, increasing their chances of success regarding the outputs, outcomes, and benefits. In this paper, documentary research was performed to identify available project management maturity models and togather information about their performance. The information gathered was used to find elements to be compared with the identified models. Reviewing the literature, 39 project management maturity models were identified. The authors selected two PMMMs that were well fitted to assess the project management capabilities in construction firms: OPM3 and MMGP Prado.

Abstract
Mobility and urban planning are among the main problems that cities face in order to achieve sustainable development. The significant economic and social changes in emerging cities, as well as the urgency of environment protection, make sustainable urban mobility planning a very critical issue. Although sustainability is difficult to be measured directly, it can be assessed through a system of parameters that attempt to reflect its multiple aspects. The definition of adequate indicators constitutes an essential part of this process, even if the literature is already abundant in available metrics. This research proposes a set of indicators, grouped in different dimensions, as a tool for the assessment of sustainability in mobility systems, for the specific context of emerging cities. These dimensions and indicators are based on a comprehensive literature review on sustainable urban mobility indicators, subsequently subjected to validation with experts through surveys, semi-structured interviews and statistical analysis, in order to identify the indicators significance and their priority within the selected dimensions. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.