Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.

Reconfigurable intelligent surfaces (RIS) offer the potential to customize the radio propagation environment for wireless networks, and will be a key element for 6G communications. However, due to the unique constraints in these systems, the optimization problems associated to RIS configuration are challenging to solve. This paper illustrates a new approach to the RIS configuration problem, based on the use of artificial intelligence (AI) and deep learning (DL) algorithms. Concretely, a custom convolutional neural network (CNN) intended for edge computing is presented, and implementations on different representative edge devices are compared, including the use of commercial AI-oriented devices and a field-programmable gate array (FPGA) platform. This FPGA option provides the best performance, with ×20 performance increase over the closest FP32, GPU-accelerated option, and almost ×3 performance advantage when compared with the INT8-quantized, TPU-accelerated implementation. More noticeably, this is achieved even when high-level synthesis (HLS) tools are used and no custom accelerators are developed. At the same time, the inherent reconfigurability of FPGAs opens a new field for their use as enabler hardware in RIS applications.

Whole-exome sequencing of oral epithelial dysplasia samples reveals an association with new genes.

The genetic basis of oral epithelial (OED) is unknown, and there is no reliable method for evaluating the risk of malignant transformation. Somatic mutations are responsible for the transformation of dysplastic mucosa to invasive cancer. In addition, these genomic variations could represent objective markers of the potential for malignant transformation. We performed whole-exome sequencing of 10 OED samples from Brazilian and Chilean patients. Using public genetic repositories, we identified 41 deleterious variants that could produce high-impact changes in the amino acid structures of 38 genes. In addition, the variants were filtered according to normal skin and Native American genome profiles. Finally, 13 genes harboring 15 variants were found to be exclusively related to OED. High-grade epithelial dysplasia samples showed a tendency to accumulate highly deleterious variants. We observed that 62% of 13 OED genes identified in our study were also found in head and neck squamous cell carcinoma. Among the shared genes, eight were not identified in oral squamous cell carcinoma. To our knowledge, we have described for the first time 13 genes that are found in OED in a Latin American population, of which five genes have already been observed in oral squamous cell carcinoma. Through this study, we identified genes that may be related to basal biological functions in OED.

Whole-exome sequencing of oral epithelial dysplasia samples reveals an association with new genes

Abstract The genetic basis of oral epithelial (OED) is unknown, and there is no reliable method for evaluating the risk of malignant transformation. Somatic mutations are responsible for the transformation of dysplastic mucosa to invasive cancer. In addition, these genomic variations could represent objective markers of the potential for malignant transformation. We performed whole-exome sequencing of 10 OED samples from Brazilian and Chilean patients. Using public genetic repositories, we identified 41 deleterious variants that could produce high-impact changes in the amino acid structures of 38 genes. In addition, the variants were filtered according to normal skin and Native American genome profiles. Finally, 13 genes harboring 15 variants were found to be exclusively related to OED. High-grade epithelial dysplasia samples showed a tendency to accumulate highly deleterious variants. We observed that 62% of 13 OED genes identified in our study were also found in head and neck squamous cell carcinoma. Among the shared genes, eight were not identified in oral squamous cell carcinoma. To our knowledge, we have described for the first time 13 genes that are found in OED in a Latin American population, of which five genes have already been observed in oral squamous cell carcinoma. Through this study, we identified genes that may be related to basal biological functions in OED.

Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations' COCI: a multidisciplinary comparison of coverage via citations.

New sources of citation data have recently become available, such as Microsoft Academic, Dimensions, and the OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI). Although these have been compared to the Web of Science Core Collection (WoS), Scopus, or Google Scholar, there is no systematic evidence of their differences across subject categories. In response, this paper investigates 3,073,351 citations found by these six data sources to 2,515 English-language highly-cited documents published in 2006 from 252 subject categories, expanding and updating the largest previous study. Google Scholar found 88% of all citations, many of which were not found by the other sources, and nearly all citations found by the remaining sources (89-94%). A similar pattern held within most subject categories. Microsoft Academic is the second largest overall (60% of all citations), including 82% of Scopus citations and 86% of WoS citations. In most categories, Microsoft Academic found more citations than Scopus and WoS (182 and 223 subject categories, respectively), but had coverage gaps in some areas, such as Physics and some Humanities categories. After Scopus, Dimensions is fourth largest (54% of all citations), including 84% of Scopus citations and 88% of WoS citations. It found more citations than Scopus in 36 categories, more than WoS in 185, and displays some coverage gaps, especially in the Humanities. Following WoS, COCI is the smallest, with 28% of all citations. Google Scholar is still the most comprehensive source. In many subject categories Microsoft Academic and Dimensions are good alternatives to Scopus and WoS in terms of coverage.

Metrics in academic profiles: a new addictive game for researchers? / Métricas en perfiles académicos: ¿un nuevo juego adictivo para los investigadores?

This study aims to promote reflection and bring attention to the potential adverse effects of academic social networks on science. These academic social networks, where authors can display their publications, have become new scientific communication channels, accelerating the dissemination of research results, facilitating data sharing, and strongly promoting scientific collaboration, all at no cost to the user.One of the features that make them extremely attractive to researchers is the possibility to browse through a wide variety of bibliometric indicators. Going beyond publication and citation counts, they also measure usage, participation in the platform, social connectivity, and scientific, academic and professional impact. Using these indicators they effectively create a digital image of researchers and their reputations.However, although academic social platforms are useful applications that can help improve scientific communication, they also hide a less positive side: they are highly addictive tools that might be abused. By gamifying scientific impact using techniques originally developed for videogames, these platforms may get users hooked on them, like addicted academics, transforming what should only be a means into an end in itself.

OBJETIVO: Pretende este trabajo provocar la reflexión y alertar de los posibles peligros para la ciencia que encierran las nuevas redes sociales académicas que tanto éxito están teniendo en nuestros días. Las redes sociales académicas donde los autores pueden mostrar sus publicaciones se han convertido en nuevos canales de comunicación científica, pues agilizan la diseminación de los resultados de investigación, facilitan la compartición de datos y fomentan la colaboración científica de forma extensa sin coste alguno. Una de las novedades principales de estas plataformas, que es lo que las hace enormemente atractivas para los investigadores, consiste en la disponibilidad de una amplia batería de indicadores bibliométricos que van más allá del conteo de publicaciones y citas pues permiten medir el uso, la participación, la conectividad social y el impacto científico, académico y profesional. Sobre estos indicadores se está construyendo la propia imagen y reputación digital de los científicos. Pues bien, todos estos beneficios de las redes sociales académicas en la mejora de la comunicación científica esconden un lado no tan positivo para la ciencia. Se trata de herramientas muy peligrosas, que pueden convertirse en auténticas adicciones. Mediante la gamificación del impacto científico a través de persuasivas técnicas procedentes de los videojuegos, estas plataformas pueden hacer que los usuarios queden enganchados, como académicos adictos, convirtiendo lo que es un medio en un fin en sí mismo.

Métricas en perfiles académicos: ¿un nuevo juego adictivo para los investigadores? / Metrics in academic profiles: a new addictive game for researchers?

Pretende este trabajo provocar la reflexión y alertar de los posibles peligros para la ciencia que encierran las nuevas redes sociales académicas que tanto éxito están teniendo en nuestros días. Las redes sociales académicas donde los autores pueden mostrar sus publicaciones se han convertido en nuevos canales de comunicación científica, pues agilizan la diseminación de los resultados de investigación, facilitan la compartición de datos y fomentan la colaboración científica de forma extensa sin coste alguno. Una de las novedades principales de estas plataformas, que es lo que las hace enormemente atractivas para los investigadores, consiste en la disponibilidad de una amplia batería de indicadores bibliométricos que van más allá del conteo de publicaciones y citas pues permiten medir el uso, la participación, la conectividad social y el impacto científico, académico y profesional. Sobre estos indicadores se está construyendo la propia imagen y reputación digital de los científicos. Pues bien, todos estos beneficios de las redes sociales académicas en la mejora de la comunicación científica esconden un lado no tan positivo para la ciencia. Se trata de herramientas muy peligrosas, que pueden convertirse en auténticas adicciones. Mediante la gamificación del impacto científico a través de persuasivas técnicas procedentes de los videojuegos, estas plataformas pueden hacer que los usuarios queden enganchados, como académicos adictos, convirtiendo lo que es un medio en un fin en sí mismo (AU)

This study aims to promote reflection and bring attention to the potential adverse effects of academic social networks on science. These academic social networks, where authors can display their publications, have become new scientific communication channels, accelerating the dissemination of research results, facilitating data sharing, and strongly promoting scientific collaboration, all at no cost to the user. One of the features that make them extremely attractive to researchers is the possibility to browse through a wide variety of bibliometric indicators. Going beyond publication and citation counts, they also measure usage, participation in the platform, social connectivity, and scientific, academic and professional impact. Using these indicators they effectively create a digital image of researchers and their reputations. However, although academic social platforms are useful applications that can help improve scientific communication, they also hide a less positive side: they are highly addictive tools that might be abused. By gamifying scientific impact using techniques originally developed for videogames, these platforms may get users hooked on them, like addicted academics, transforming what should only be a means into an end in itself (AU)