In this paper we construct a new set of basis functions for the numerical solution of nonhomogeneous heat conduction problems with Dirichlet boundary conditions and null initial data. These functions can be seen as Newtonian potentials of plane waves for the heat equation and satisfy a null initial condition. Density results for adapted waves will be established and several numerical simulations will be presented in order to discuss the accuracy and feasibility of the proposed method. An application of the method for heat problems with non null initial temperature will also be discussed.

Recent developments in automation and Artificial Intelligence (AI) are leading to a wave of innovation in organizational design and changes in the workplace. Techno-optimists even named it the ‘second machine age’, arguing that it now involves the substitution of the human brain. Other authors see this as just a continuation of previous ICT developments. Potentially, automation and AI can have significant technical, economic, and social implications in firms. The paper will answer the question: what are the implications on industrial productivity and employment in the automotive sector with the recent automation trends, including AI, in Portugal? Our approach used mixed methods to conduct statistical analyses of relevant databases and interviews with experts on R&D projects related to automation and AI implementation. Results suggest that automation can have widespread adoption in the short term in the automotive sector, but AI technologies will take more time to be adopted. Findings show that adoption of automation and AI increases productivity in firms and is dephased in time with employment implications. Investments in automation are not substituting operators but rather changing work organization. Thus, negative effects about technology and unemployment were not substantiated by our results

https://ideas.repec.org/p/mde/wpaper/0165.html

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The Algar do Vale da Pena is a cave that was discovered during limestone mining works around 1980, at the Natural Park of Serras de Aire e Candeeiros, Portugal. The entrance to the cave, through the collapsed roof, is a 30 meter near-vertical well, inaccessible without means of vertical progression and specialized equipment. Soon after the discovery of the cave, bone material belonging to bears and hundreds of bear claw marks were located inside it. Nevertheless, the technical descent and the extraordinary difficulties of retrieving the calcite flowstones that encased the bones prevented scientists from undertaking excavations for nearly 40 years. Since 2016 a series of expeditions by a team of paleontologists from NOVA University and Museum of Lourinhã recovered more than 20 disarticulated remains from five bone accumulations, separated more than five meters apart, which given the level of erosion and breakage, are para-autochthonous in origin. These are interpreted as belonging to different individuals. Morphological characters, like a relatively elongated third phalanx, the clear separation of paracone-metacone of the first upper molar and the ventral position of the mandibular condyle; as well as numerous morphometric characters, allow to ascribe the remains to Ursus arctos. Nevertheless, the main finding from the cave is a complete skull with an articulated mandible; which denotes absence of transport, encased within a 180 kg calcite flowstone, including other skeletal remains as well, which could not be extracted from the cave until 2021. This block was removed with the help of members of several speleological groups. It promises a wealth of information about fossil brown bears, being the most complete bear fossil ever recovered in Portugal. It is currently being dated trough magnetostratigraphy and prepared. We consider this intervention as an extraordinary example of citizen science applied to paleontology

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New technologies, sustainability policies, protectionism and consumers preferences are pushing for the reorganisation of the automotive cluster. The emergence of artificial intelligence (AI) has the potential to create disruptive effects in the employment systems across the world. The future deployment of broad-spectrum algorithms capable of being used in wide areas of application (e.g., industrial robotics, software and data communication) can lead to considerable changes in current work patterns, swiftly render many unemployed across the globe and profoundly destabilise labour relations. In this paper, we identify the probable penetration of AI in the automotive sector and to study its effects on work organisation, employment, and industrial relations systems, in Portugal. These changes are put in place to enhance the product quality, control costs, and improve productivity. We study these implications on productivity and industrial relations collecting new data and obtain results based on secondary statistical analyses and case studies in the automotive industry. Finally, changes in the productivity and labour market will be discussed considering the employment and skills changes in the automotive sector when investment on automation becomes a clear trend in the automotive sector.

Technology is recognized by its potential to promote mathematical learning. However, achieving this potential
requires the teachers to have the knowledge to integrate it properly into their practices. Several authors have intended to characterize the teachers’ knowledge and developed several models, but this approach has often been criticized by its static approach, not attending neither valuing the teachers’ practice. In this study we adopt the KTMT – Knowledge for Teaching Mathematics with Technology model, assuming the teachers’ practice as the main scenario of analysis. We focus on the options guiding the teachers’ decisions when confronted with a situation of lack of mathematical concordance while teaching functions. The situations of lack of mathematical concordance (i.e., situations where the mathematics addressed by the students is different from the one intended by the teacher) are assumed as rich and encapsulating the potential to reveal significant aspects of the teachers’ KTMT. The main goal of the study is to understand what domains of the teachers’ KTMT are highlighted in these circumstances. A qualitative methodology is adopted and one episode of one 10th grade teacher’s practice is analyzed, based on the KTMT model. The conclusions reached show the relevance of different knowledge domains, but emphasize the Mathematics and Technology Knowledge (MTK). They also raise questions about the impact of the specific technology being used on the teachers’ KTMT.

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