Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integration

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.Comment: 10 pages, 11 figure

EpIG‐DB: A database of vascular epiphyte assemblages in the Neotropics

Vascular epiphytes are a diverse and conspicuous component of biodiversity in tropical and subtropical forests. Yet, the patterns and drivers of epiphyte assemblages are poorly studied in comparison with soil‐rooted plants. Current knowledge about diversity patterns of epiphytes mainly stems from local studies or floristic inventories, but this information has not yet been integrated to allow a better understanding of large‐scale distribution patterns. EpIG‐DB, the first database on epiphyte assemblages at the continental scale, resulted from an exhaustive compilation of published and unpublished inventory data from the Neotropics. The current version of EpIG‐DB consists of 463,196 individual epiphytes from 3,005 species, which were collected from a total of 18,148 relevés (host trees and ‘understory’ plots). EpIG‐DB reports the occurrence of ‘true’ epiphytes, hemiepiphytes and nomadic vines, including information on their cover, abundance, frequency and biomass. Most records (97%) correspond to sampled host trees, 76% of them aggregated in forest plots. The data is stored in a TURBOVEG database using the most up‐to‐date checklist of vascular epiphytes. A total of 18 additional fields were created for the standardization of associated data commonly used in epiphyte ecology (e.g. by considering different sampling methods). EpIG‐DB currently covers six major biomes across the whole latitudinal range of epiphytes in the Neotropics but welcomes data globally. This novel database provides, for the first time, unique biodiversity data on epiphytes for the Neotropics and unified guidelines for future collection of epiphyte data. EpIG‐DB will allow exploration of new ways to study the community ecology and biogeography of vascular epiphytes

Correlations between Risk Factors for Breast Cancer and Genetic Instability in Cancer Patients- A Clinical Perspective Study

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Molecular epidemiological studies have identified several risk factors linking to the genes and external factors in the pathogenesis of breast cancer. In this sense, genetic instability caused by DNA damage and DNA repair inefficiencies are important molecular events for the diagnosis and prognosis of therapies. Therefore, the objective of this study was to analyze correlation between sociocultural, occupational, and lifestyle risk factors with levels of genetic instability in non-neoplastic cells of breast cancer patients. Total 150 individuals were included in the study that included 50 breast cancer patients submitted to chemotherapy (QT), 50 breast cancer patients submitted to radiotherapy (RT), and 50 healthy women without any cancer. Cytogenetic biomarkers for apoptosis and DNA damage were evaluated in samples of buccal epithelial and peripheral blood cells through micronuclei and comet assay tests. Elder age patients (61–80 years) had higher levels of apoptosis (catriolysis by karyolysis) and DNA damage at the diagnosis (baseline damage) with increased cell damage during QT and especially during RT. We also reported the increased frequencies of cytogenetic biomarkers in patients who were exposed to ionizing radiation as well as for alcoholism and smoking. QT and RT induced high levels of fragmentation (karyorrhexis) and nuclear dissolution (karyolysis) and DNA damage. Correlations were observed between age and karyorrhexis at diagnosis; smoking and karyolysis during RT; and radiation and karyolysis during QT. These correlations indicate that risk factors may also influence the genetic instability in non-neoplastic cells caused to the patients during cancer therapies