A Real-time Energy-Saving Mechanism in Internet of Vehicles Systems

Emerging technologies, such as self-driving cars and 5G communications, are raising new mobility and transportation possibilities in smart and sustainable cities, bringing to a new echo-system often referred to as Internet of Vehicles (IoV). In order to efficiently operate, an IoV system should take into account more stringent requirements with respect to traditional IoT systems, e.g., ultra-broadband connections, high-speed mobility, high-energy efficiency and requires efficient real-time algorithms. This paper proposes an energy and communication driven model for IoV scenarios, where roadside units (RSUs) need to be frequently assigned and re-assigned to the operating vehicles. The problem has been formulated as an Uncapacitated Facility Location Problem (UFLP) for jointly solving the RSU-to-vehicle allocation problem while managing the RSUs switch-on and -off processes. Differently from traditional UFLP approaches, based on static solutions, we propose here a fast-heuristic approach, based on a dynamic multi-period time scale mapping: the proposed algorithm is able to efficiently manage in real-time the RSUs, selecting at each period those to be activated and those to be switched off. The resulting methodology is tested against a set of benchmark instances, which allows us to illustrate its potential. Results, in terms of overall cost –mapping both energy consumption and transmission delays–, number of active RSUs, and convergence speed, are compared with static approaches, showing the effectiveness of the proposed dynamic solution. It is noticeable a gain of up to 11% in terms of overall cost with respect to the static approaches, with a moderate additional delay for finding the solution, around 0.8 s, while the overall number of RSUs to be switched on is sensibly reduced up to a fraction of 15% of the overall number of deployed RSUs, in the most convenient scenario

A Real-Time Energy-Saving Mechanism in Internet of Vehicles Systems

[EN] Emerging technologies, such as self-driving cars and 5G communications, are raising new mobility and transportation possibilities in smart and sustainable cities, bringing to a new echo-system often referred to as Internet of Vehicles (IoV). In order to efficiently operate, an IoV system should take into account more stringent requirements with respect to traditional IoT systems, e.g., ultra-broadband connections, high-speed mobility, high-energy efficiency and requires efficient real-time algorithms. This paper proposes an energy and communication driven model for IoV scenarios, where roadside units (RSUs) need to be frequently assigned and re-assigned to the operating vehicles. The problem has been formulated as an Uncapacitated Facility Location Problem (UFLP) for jointly solving the RSU-to-vehicle allocation problem while managing the RSUs switch-on and -off processes. Differently from traditional UFLP approaches, based on static solutions, we propose here a fast-heuristic approach, based on a dynamic multi-period time scale mapping: the proposed algorithm is able to efficiently manage in real-time the RSUs, selecting at each period those to be activated and those to be switched off. The resulting methodology is tested against a set of benchmark instances, which allows us to illustrate its potential. Results, in terms of overall cost-mapping both energy consumption and transmission delays-, number of active RSUs, and convergence speed, are compared with static approaches, showing the effectiveness of the proposed dynamic solution. It is noticeable a gain of up to 11% in terms of overall cost with respect to the static approaches, with a moderate additional delay for finding the solution, around 0.8 s, while the overall number of RSUs to be switched on is sensibly reduced up to a fraction of 15% of the overall number of deployed RSUs, in the most convenient scenario.The work of Luca Cesarano and Andrea Croce has been done during an abroad study period at Universitat Oberta de Catalunya, Spain, supported by Erasmus+ Study Programme of the European Union.Cesarano, L.; Croce, A.; Martins, LDC.; Tarchi, D.; Juan-Pérez, ÁA. (2021). A Real-Time Energy-Saving Mechanism in Internet of Vehicles Systems. IEEE Access. 9:157842-157858. https://doi.org/10.1109/ACCESS.2021.3130125157842157858

Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation

[EN] The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033, RED2018-102642-T), the SEPIE Erasmus+Program (2019-I-ES01-KA103-062602), and the IoF2020-H2020 (731884) project.Do C. Martins, L.; Tordecilla, RD.; Castaneda, J.; Juan-Pérez, ÁA.; Faulin, J. (2021). Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation. Energies. 14(16):1-30. https://doi.org/10.3390/en14165131130141

A multidisciplinary approach for the management of hypodontia: case report

Hypodontia is the congenital absence of one or more teeth and may affect permanent teeth. Several options are indicated to treat hypodontia, including the maintenance of primary teeth or space redistribution for restorative treatment with partial adhesive bridges, tooth transplantation, and implants. However, a multidisciplinary approach is the most important requirement for the ideal treatment of hypodontia. This paper describes a multidisciplinary treatment plan for congenitally missing permanent mandibular second premolars involving orthodontics, implantology and prosthodontic specialties

Edge computing and iot analytics for agile optimization in intelligent transportation systems

[EN] With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens' mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing. These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.This work was partially supported by the Spanish Ministry of Science (PID2019111100RB-C21/AEI/10.13039/501100011033, RED2018-102642-T), and the Erasmus+ program (2019I-ES01-KA103-062602).Peyman, M.; Copado, PJ.; Tordecilla, RD.; Do C. Martins, L.; Xhafa, F.; Juan-Pérez, ÁA. (2021). Edge computing and iot analytics for agile optimization in intelligent transportation systems. Energies. 14(19):1-26. https://doi.org/10.3390/en14196309126141

Desempenho de bovinos em sistema de Integração Lavoura-Pecuária de longa duração.

Evento híbrido

Desenvolvimento de Software Educacional para Representação e Reconhecimento de Som Aplicado à Ausculta Cardiovascular

No ensino da medicina, especificamente, em laboratórios de estudos e práticas, existe uma preocupação de resguardar o máximo o paciente, buscando o mínimo de constrangimento, porém sem deixar que o aprendizado seja prejudicado. Com o objetivo de capacitar o discente para a prática em ausculta cardiovascular, sem que o contato com o paciente seja necessário, foi desenvolvido o sistema CARDIOS. Contendo informações de doenças cardiovasculares, o aluno conhece o som e o respectivo registro gráfico. A utilização de aparelhos específicos, como um estetoscópio eletrônico, promove a visualização e amplificação do som em tempo real. O uso de agentes inteligentes possibilita o reconhecimento do som cardíaco, classificando-o em normal ou patológico

Providing genetics for the dairy industry in the tropics - the Brazilian Dairy Gir Breeding Program.

Milk production is usually challenging under tropical environments. Heat stress and/or recurrent parasite infestations frequently cause cattle?s reduced fitness and productivity. As a way to overcome this challenge, the Gir indicine cattle breed has increasingly been used in crossbred schemes to constitute milk production herds in Brazil and other countries in tropical regions. The Brazilian Dairy Gir Breeding Program was established in 1985, based on a partnership between the Brazilian Agricultural Research Corporation and the Brazilian Association of Dairy Gir Breeders. It was the first breeding program outlined with a progeny test for the improvement of an indicine breed for milk production in the world. Several technical innovations were employed along the time. Now, producers can access genomic predictions for thousands of Gir males and females. Those predictions are used mainly by Brazilian breeders, but also increasingly in other tropical countries from South America, Central America and Asia

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Cell-Free Antigens from Paracoccidioides brasiliensis Drive IL-4 Production and Increase the Severity of Paracoccidioidomycosis

The thermally dimorphic fungus Paracoccidioides brasiliensis (Pb) is the causative agent of paracoccidioidomycosis (PCM), one of the most frequent systemic mycosis that affects the rural population in Latin America. PCM is characterized by a chronic inflammatory granulomatous reaction, which is consequence of a Th1-mediated adaptive immune response. In the present study we investigated the mechanisms involved in the immunoregulation triggered after a prior contact with cell-free antigens (CFA) during a murine model of PCM. The results showed that the inoculation of CFA prior to the infection resulted in disorganized granulomatous lesions and increased fungal replication in the lungs, liver and spleen, that paralleled with the higher levels of IL-4 when compared with the control group. The role of IL-4 in facilitating the fungal growth was demonstrated in IL-4-deficient- and neutralizing anti-IL-4 mAb-treated mice. The injection of CFA did not affect the fungal growth in these mice, which, in fact, exhibited a significant diminished amount of fungus in the tissues and smaller granulomas. Considering that in vivo anti-IL-4-application started one week after the CFA-inoculum, it implicates that IL-4-CFA-induced is responsible by the mediation of the observed unresponsiveness. Further, the characterization of CFA indicated that a proteic fraction is required for triggering the immunosuppressive mechanisms, while glycosylation or glycosphingolipids moieties are not. Taken together, our data suggest that the prior contact with soluble Pb antigens leads to severe PCM in an IL-4 dependent manner