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With the advent of mass customization and product proliferation, the appearance of hybrid Make-toStock(MTS)/Make-to-Order(MTO) policies arise as a strategy to cope with high product variety maintaining satisfactory lead times. In companies operating under this reality, Sales and Operations Planning (S&OP) practices must be adapted accordingly during the coordinated planning of procurement, production, logistics, and sales activities. This paper proposes a novel S&OP decision-making framework for a flow shop/batch company that produces standard products under an MTS strategy and customized products under an MTO strategy. First, a multi-objective mixed-integer programming model is formulated to characterize the problem. Then, a matrix containing the different strategies a firm in this context may adopt is proposed. This rationale provides a business-oriented approach towards the analysis of different plans and helps to frame the different Pareto-optimal solutions given the priority on MTS or MTO segments and the management positioning regarding cost minimization or service level orientation. The research is based on a real case faced by an electric cable manufacturer. The computational experiments demonstrate the applicability of the proposed methodology. Our approach brings a practical, supply chain-oriented, and mid-term perspective on the study of operations planning policies in MTS/MTO contexts.

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This chapter aims to introduce the European Project Semester concept and the network of providers together with historical and current data on participants and providers. EPS is a one-semester international exchange program designed for engineering, product designers, and business undergraduates. It embraces student-centered project-based learning and multicultural and transdisciplinary teamwork to help students develop the competencies and skills required for the 21st century. It was created in 1995 in Denmark to prepare future engineers for global challenges, and it combines scientific and technical education, ethical and sustainability-driven problem-solving, intercultural communication, and teamwork. EPS has since been adopted by 19 European higher education institutions, establishing a network of EPS providers across Europe. The network offers international students a wide range of European study locations and cultural insights and, above all, the opportunity to enjoy the EPS learning experience. The number of alumni shows the program's attractiveness, range, and vitality.

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Public transport services play an important role in the mobility of the population in urban centers, allowing a decrease in the number of private vehicles in circulation and contributing to a more sustainable mobility. However, the emergence of the COVID-19 pandemic had a serious impact on the mobility habits of the population, with a substantial reduction in the number of public transport passengers due to the fear of contagion, which raises questions about the future sustainability of cities. Thus, it is essential to restore the confidence of travelers to feel safe and comfortable using public transport services. Taking advantage of the widespread use of mobile technologies, this article intends to propose a route planning system for public transport that meets the needs of passengers in terms of safety and comfort. After a systematic review of the existing literature and a series of focus group sessions, a prototype of the system was developed, and subsequently evaluated by potential users through usability tests. The results obtained are a good indicator of the system's functionality and ease of use. This assessment allowed us to corroborate the potential that the proposed route planning system has in promoting the use of public transport services as a means of mobility.

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The estimation of the spectral absorption coefficient of biological tissues provides valuable information that can be used in diagnostic procedures. Such estimation can be made using direct calculations from invasive spectral measurements or though machine learning algorithms based on noninvasive or minimally invasive spectral measurements. Since in a noninvasive approach, the number of measurements is limited, an exploratory study to investigate the use of artificial generated data in machine learning techniques was performed to evaluate the spectral absorption coefficient of the brain cortex. Considering the spectral absorption coefficient that was calculated directly from invasive measurements as reference, the similar spectra that were estimated through different machine learning approaches were able to provide comparable information in terms of pigment, DNA and blood contents in the cortex. The best estimated results were obtained based only on the experimental measurements, but it was also observed that artificially generated spectra can be used in the estimations to increase accuracy, provided that a significant number of experimental spectra are available both to generate the complementary artificial spectra and to estimate the resulting absorption spectrum of the tissue. © 2022 Journal of Biomedical Photonics & Engineering. © J-BPE.

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