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This study delves into the intricate dynamics of urban mobility, a pivotal aspect for policymakers, businesses, and communities alike. By deciphering patterns of movement within a city, stakeholders can craft targeted interventions to mitigate traffic congestion peaks, optimizing both resource allocation and individual travel routes. Focused on Barcelona, Spain, this paper draws on data sourced from the city council's open data service. Through a blend of exploratory analysis, visualization techniques, and modeling methodologies—including time series analysis and the eXtreme Gradient Boosting (XGBoost) algorithm—the research endeavors to forecast traffic conditions. Additionally, a study of variable importance is carried out, and Shapley Additive Explanations are applied to enhance the interpretability of model outputs. Findings underscore the limitations of traditional forecasting methods in capturing the nuanced spatial and temporal dependencies present in traffic flows, particularly over medium- to long-term horizons. However, the XGBoost model demonstrates robust performance, with the area under ROC curves consistently exceeding 80%, indicating its efficacy in handling non-linear traffic data variables. [ABSTRACT FROM AUTHOR]

While generating high harmonics in long media of helium gas, at certain laser intensities and chirp, the spectral shift and split of the harmonic lines were experimentally observed, sometimes exceeding one harmonic order. Beyond reporting these results, numerical simulations were performed to understand the phenomenon. A 3D propagation model was solved under the strong field approximation. According to the simulations, the distortion of the laser beam profile during propagation and the consequently accused change in the conditions of phase matching are responsible for the observations. The observed phenomena can be an excellent tool to produce tunable narrow band harmonic sources covering a broad range around 13.5 nm for spectroscopy and for seeding X-ray lasers, and to understand non-desired detuning of the seed wavelength. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel framework for enriching time series data in smart cities by supplementing it with information from external sources via semantic data enrichment. Our methodology effectively merges multiple data sources into a uniform time series, while addressing difficulties such as data quality, contextual information, and time lapses. We demonstrate the efficacy of our method through a case study in Barcelona, which permitted the use of advanced analysis methods such as windowed cross-correlation and peak picking. The resulting time series data can be used to determine traffic patterns and has potential uses in other smart city sectors, such as air quality, energy efficiency, and public safety. Interactive dashboards enable stakeholders to visualize and summarize key insights and patterns. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an 'Internet of vehicles' with the potential to significantly enhance citizens' mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities. [ABSTRACT FROM AUTHOR]

In smart cities, unmanned aerial vehicles and self-driving vehicles are gaining increased concern. These vehicles might utilize ultra-reliable telecommunication systems, Internet-based technologies, and navigation satellite services to locate their customers and other team vehicles to plan their routes. Furthermore, the team of vehicles should serve their customers by specified due date efficiently. Coordination between the vehicles might be needed to be accomplished in real-time in exceptional cases, such as after a traffic accident or extreme weather conditions. This paper presents the planning of vehicle routes as a team orienteering problem. In addition, an 'agile' optimization algorithm is presented to plan these routes for drones and other autonomous vehicles. This algorithm combines an extremely fast biased-randomized heuristic and a parallel computing approach. [ABSTRACT FROM AUTHOR]

We investigate the effect of chirped excitation and the excitation detuning on the coherent control of population transfer and vibrational states in a four-level system. Density matrix equations are studied for optimally enhanced processes by considering specific parameters typical of oxazine systems. Our simulations show a strong dependence on the interplay between chirp and excitation detuning and predict enhancement factors up to 3.2 for population transfer and up to 38.5 for vibrational coherences of electronic excited states. The study of the dynamics of the populations and vibrational coherences involved in the four-level system allows an interpretation of the different enhancement/suppression processes observed. [ABSTRACT FROM AUTHOR]

We present a numerical solution for complete population inversion in a four-level ladder system obtained by using a full π-pulse illumination scheme with resonant ultrashort phase-locked Gaussian laser pulses. We find that a set of pulse areas such as √3π, 2π, and √3π completely inverts the four-level system considering identical effective dipole coupling coefficients. The solution is consistent provided the involved electric fields are not too strong and it is amply accurate also in the case of diverse transition dipole moments. We study the effect of detuning and chirp of the laser pulses on the complete population inversion using the level structure of atomic sodium interacting with ps and fs pulses as an example. Our result opens the door for multiple applications such as efficient ultrashort pulse lasing in the UV or the engineering of quantum states for quantum computing. [ABSTRACT FROM AUTHOR]

A technique for broadband spectral amplitude control of light pulses produced in high-order harmonic generation (HHG) is presented. It has been shown elsewhere that broadband spectral phase control in HHG is achievable using a computerized feedback loop scheme by coherently adding a filtered region of the HHG emission to the intense IR driving pulse with optimal attenuation and time delay parameters. In the present study, further computational evidence of the capabilities of this control scheme is provided by considering the spectral amplitude in a broadband region of the HHG spectrum as the control target for the production of isolated attosecond pulses. Different spectral widths and central photon energies are examined, such as a spectral width of 30 eV centered at 36 eV, well in the plateau, and a width of 20 eV centered at 60 eV in the cutoff region. An iterative procedure of themethod is implemented and optimal isolated single cycle pulses at a central photon energy of 36 eV are obtained. This control scheme is a fundamental tool that can be implemented for amplitude and phase shaping of any suitable spectral region in HHG. [ABSTRACT FROM AUTHOR]

The COVID pandemic has touched many aspects of everyone's life. Education is one of the fields greatly affected by it, as students and teachers were forced to move online and quickly adapt to the online environment. Assessment is a crucial part of education, especially in STEM fields. A gap analysis was performed by expert groups in the frame of an Erasmus+ project looking at the practices of six European countries. Specialists teaching university-grade mathematics in seven European institutions were asked about their perception of gaps in the assessment of students both before (2019) and during (2021) the pandemic. This qualitative study looks at the difference in perception of such gaps after almost one year of online teaching. The analysis of their responses showed that some gaps were present before the pandemic, as well as others that are specific to it. Some gaps, such as the lack of IT infrastructure and the need to adapt materials to an online environment, have been exacerbated by the outbreak. [ABSTRACT FROM AUTHOR]