Módulo de aprendizaje para diseñar placas de circuito impreso para dispositivos basados en el IoT

[ES] El taller sobre Tecnologías Disruptivas de la Información y la Comunicación para la Innovación y la Transformación Digital, organizado en el ámbito del proyecto DISRUPTIVE (disruptive.usal.es) y celebrado el 12 de septiembre de 2022 en Valladolid, tiene como objetivo debatir sobre los problemas, retos y beneficios del uso de tecnologías digitales disruptivas, a saber, Internet de las Cosas, Big data, computación en la nube, sistemas multiagente, aprendizaje automático, realidad virtual y aumentada y robótica colaborativa, para apoyar la transformación digital en curso en la sociedad. El programa del taller incluyó 6 papers técnicos aceptados, 2 charlas de invitados y una sesión de networking. Este volumen contiene 6 de las ponencias presentadas en el taller sobre Tecnologías Disruptivas de la Información y la Comunicación para la Innovación y la Transformación Digital. Este taller fue organizado por ICE (Instituto para la Competitividad Empresarial de Castilla y León), UVa (Universidad de Valladolid) y apoyado principalmente por el Fondo Europeo de Desarrollo Regional (FEDER) a través del Programa Interreg España-Portugal V-A (POCTEP) bajo la subvención 0677_DISRUPTIVE_2_E (Dinamización de los Digital Innovation Hubs dentro de la región PocTep para el impulso de las TIC disruptivas y de última generación a través de la cooperación en la región transfronteriza).[EN] The workshop on Disruptive Information and Communication Technologies for Innovation and Digital transformation, organized under the scope of the DISRUPTIVE project (disruptive.usal.es) and held on September 12, 2022 in Valladolid, aims to discuss problems, challenges and benefits of using disruptive digital technologies, namely Internet of Things, Big data, cloud computing, multi-agent systems, machine learning, virtual and augmented reality, and collaborative robotics, to support the on-going digital transformation in society. The main topics included: Intelligent Manufacturing Systems; Industry 4.0 and digital transformation; Internet of Things; Cyber-security; Collaborative and intelligent robotics; Multi-Agent Systems; Industrial Cyber-Physical Systems; Virtualization and digital twins; Predictive maintenance; Virtual and augmented reality, Big Data and advanced data analytics; Edge and cloud Computing; Digital Transformation. The workshop program included 6 accepted technical papers, 2 invited talks and a networking session. This volume contains 6 of the papers presented at the Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation. This workshop was organized by ICE (Institute for Business Competitiveness of Castilla y León), UVa (University of Valladolid) and mainly supported by the European Regional Development Fund (ERDF) through the Interreg Spain-Portugal V-A Program (POCTEP) under grant 0677_DISRUPTIVE_2_E (Intensifying the activity of Digital Innovation Hubs within the PocTep region to boost the development of disruptive and last generation ICTs through cross-border cooperation)

Raman Spectroscopy for Characterization of Hydrotalcite-like Materials Used in Catalytic Reactions

This chapter covers a brief review of the definition, structural characteristics and main applications of hydrotalcite, an interesting multifunctional material which finds applicability in different areas. Particularly, some catalytic reactions using hydrotalcite or mixed oxides derived from these materials are addressed (Ethanol Steam Reforming, Photochemical conversions, Hydrodesulfurization). The use of Raman Spectroscopy associated with other techniques, such as powder X-ray diffraction (XRD), Extended X-ray Absorption Fine-Structure (EXAFS), Temperature Programmed Reduction of hydrogen (H2-TPR), Fourier-Transform Infrared (FTIR) and Density Functional Theory (DFT) simulations, to characterize this type of material is addressed through examples described in the current literature. In this sense, multidisciplinary efforts must be made in order to increase the understanding of the properties of these materials and the catalytic behavior in the most varied reactions

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Early stages of vanadium deposition on Si(111)-7 x 7

4 p. : il.We investigate the low-coverage regime of vanadium deposition on the Si(111)-7 x 7 surface using a combination of scanning tunnelling microscopy (STM) and density-functional theory (DFT) adsorption energy calculations. We theoretically identify the most stable structures in this system: (i) substitutional vanadium atoms at silicon adatom positions; (ii) interstitial vanadium atoms between silicon adatoms and rest atoms; and (iii) interstitial vanadium – silicon adatom vacancy complexes. STM images reveal two simple vanadium-related features near the Si adatom positions: bright spots at both polarities (BB) and dark spots for empty and bright spots for filled states (DB). We relate the BB spots to the interstitial structures and the DB spots to substitutional structures

Neurological outcomes in children with and without amalgam-related mercury exposure: seven years of longitudinal observations in a randomized trial

Background. Although large-scale, randomized trials involving children have been completed and their results demonstrate an absence of neurobehavioral effects from clinical exposure to mercury amalgam, neurological findings from such studies have not been reported. Methods. The authors conducted a randomized, prospective trial examining the safety of dental amalgam in which 507 children aged 8 through 12 years were assigned to treatment with either amalgam or resin-based composite. During seven years of follow-up, the authors performed annual clinical neurological examinations, including an evaluation of neurological hard signs (NHSs), presence of tremor and neurological soft signs (NSSs). Results. The authors found no significant differences between treatment groups in any of the neurological measures. Groups did not differ with respect to the presence or absence of NHSs or tremor, nor the presence or absence or severity of NSSs at any point. As expected, NSS severity scores diminished with increasing age. Conclusions. Even at the levels of amalgam exposure in this study (a mean of 7.7-10.7 amalgam surfaces per subject across the seven years of follow-up), the authors conclude that exposure to mercury from dental amalgam does not adversely affect neurological status. Clinical Implications. The current evidence is that potential neurobehavioral or neurological effects from dental amalgam mercury exposure in children are inconsequential.info:eu-repo/semantics/publishedVersio

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved