Review and analysis of networking challenges in cloud computing

Cloud Computing offers virtualized computing, storage, and networking resources, over the Internet, to organizations and individual users in a completely dynamic way. These cloud resources are cheaper, easier to manage, and more elastic than sets of local, physical, ones. This encourages customers to outsource their applications and services to the cloud. The migration of both data and applications outside the administrative domain of customers into a shared environment imposes transversal, functional problems across distinct platforms and technologies. This article provides a contemporary discussion of the most relevant functional problems associated with the current evolution of Cloud Computing, mainly from the network perspective. The paper also gives a concise description of Cloud Computing concepts and technologies. It starts with a brief history about cloud computing, tracing its roots. Then, architectural models of cloud services are described, and the most relevant products for Cloud Computing are briefly discussed along with a comprehensive literature review. The paper highlights and analyzes the most pertinent and practical network issues of relevance to the provision of high-assurance cloud services through the Internet, including security. Finally, trends and future research directions are also presented

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Modeling cooperative behavior for resilience in cyber-physical systems using SDN and NFV

Cyber-Physical Systems (CPSs) are increasingly important in everyday applications including the latest mobile devices, power grids and intelligent buildings. CPS functionality has intrinsic characteristics including considerable heterogeneity, variable dynamics, and complexity of operation. These systems also typically have insufficient resources to satisfy their full demand for specialized services such as data edge storage, data fusion, and reasoning. These novel CPS characteristics require new management strategies to support the resilient global operation of CPSs. To reach this goal, we propose a Software Defined Networking based solution scaled out by Network Function Virtualization modules implemented as distributed management agents. Considering the obvious need for orchestrating the distributed agents towards the satisfaction of a common set of global CPS functional goals, we analyze distinct incentive strategies to enact a cooperative behavior among the agents. The repeated operation of each agent’s local algorithm allows that agent to learn how to adjust its behavior following both its own experience and observed behavior in neighboring agents. Therefore, global CPS management can evolve iteratively to ensure a state of predictable and resilient operation

A data-driven intelligent decision support system that combines predictive and prescriptive analytics for the design of new textile fabrics

In this paper, we propose an Intelligent Decision Support System (IDSS) for the design of new textile fabrics. The IDSS uses predictive analytics to estimate fabric properties (e.g., elasticity) and composition values (% cotton) and then prescriptive techniques to optimize the fabric design inputs that feed the predictive models (e.g., types of yarns used). Using thousands of data records from a Portuguese textile company, we compared two distinct Machine Learning (ML) predictive approaches: Single-Target Regression (STR), via an Automated ML (AutoML) tool, and Multi-target Regression, via a deep learning Artificial Neural Network. For the prescriptive analytics, we compared two Evolutionary Multi-objective Optimization (EMO) methods (NSGA-II and R-NSGA-II) when optimizing 100 new fabrics, aiming to simultaneously minimize the physical property predictive error and the distance of the optimized values when compared with the learned input space. The two EMO methods were applied to design of 100 new fabrics. Overall, the STR approach provided the best results for both prediction tasks, with Normalized Mean Absolute Error values that range from 4% (weft elasticity) to 11% (pilling) in terms of the fabric properties and a textile composition classification accuracy of 87% when adopting a small tolerance of 0.01 for predicting the percentages of six types of fibers (e.g., cotton). As for the prescriptive results, they favored the R-NSGA-II EMO method, which tends to select Pareto curves that are associated with an average 11% predictive error and 16% distance.This work was carried out within the project "TexBoost: less Commodities more Specialities" reference POCI-01-0247-FEDER-024523, co-funded by Fundo Europeu de Desenvolvimento Regional (FEDER), through Portugal 2020 (P2020)

Biogeochemistry of the Amazonian Floodplains: Insights from Six End-Member Mixing Models

International audienceThe influence of Amazonian floodplains on the hydrological, sedimentary, and biogeochemical river budget was investigated along the Vargem Grande–Óbidos reach, by applying six mixing models based on variable regional and/or variable hydrological sources. By comparing the output of many different models designed for different purposes, the nature and the magnitude of processes linking water and biogeochemical budgets of the Amazonian floodplains were clarified. This study reveals that most of the chemical baseline of the Amazon River basin is acquired before the studied 2000-km Amazonian reach. However, the tight connection between the hydrograph stage of the river and the chemical signals provides insightful information on the dynamics of its floodplains. The chemical expression of biotic and abiotic processes occurring in the Amazonian floodplains can be particularly perceived during falling waters. It appears delayed in time compared to the maximum extension of submerged area, because the alternating water circulation polarity (filling versus emptying) between the main channel and the adjacent floodplains determines delayed emptying of floodplains during falling waters. It results also in a longer time of residence in the hydrograph network, which strengthens the rate of transformation of transiting materials and solutes. Biotic and biologically mediated processes tend to accentuate changes in river water chemistry initiated upstream, in each subbasin, along river corridors, indicating that processes operating downstream prolong those from upstream (e.g., floodplains of the large tributaries). Conversely, the flood wave propagation tends to lessen the seasonal variability as a result of the water storage in the floodplains, which admixes waters of distinct origins (in time and space). The morphology of floodplains, determining the deposition and the diagenesis of the sediments as well as the variable extension of submerged areas or the chronology of floodplains storage/emptying, appears to be the main factor controlling the floodplains biogeodynamics. By coupling classical end-member mixing models (providing insight on hydrological source) with a variable regional contribution scheme, relevant information on the biogeochemical budget of the Amazonian floodplains can be achieved

Methylation status of ANAPC1, CDKN2A and TP53 promoter genes in individuals with gastric cancer

Gastric cancer is the forth most frequent malignancy and the second most common cause of cancer death worldwide. DNA methylation is the most studied epigenetic alteration, occurring through a methyl radical addition to the cytosine base adjacent to guanine. Many tumor genes are inactivated by DNA methylation in gastric cancer. We evaluated the DNA methylation status of ANAPC1, CDKN2A and TP53 by methylation-specific PCR in 20 diffuse- and 26 intestinal-type gastric cancer samples and 20 normal gastric mucosa in individuals from Northern Brazil. All gastric cancer samples were advanced stage adenocarcinomas. Gastric samples were surgically obtained at the João de Barros Barreto University Hospital, State of Pará, and were stored at -80°C before DNA extraction. Patients had never been submitted to chemotherapy or radiotherapy, nor did they have any other diagnosed cancer. None of the gastric cancer samples presented methylated DNA sequences for ANAPC1 and TP53. CDKN2A methylation was not detected in any normal gastric mucosa; however, the CDKN2A promoter was methylated in 30.4% of gastric cancer samples, with 35% methylation in diffuse-type and 26.9% in intestinal-type cancers. CDKN2A methylation was associated with the carcinogenesis process for ~30% diffuse-type and intestinal-type compared to non-neoplastic samples. Thus, ANAPC1 and TP53 methylation was probably not implicated in gastric carcinogenesis in our samples. CDKN2A can be implicated in the carcinogenesis process of only a subset of gastric neoplasias.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FINEP/CT-INFRAFAEPAUniversidade Federal do Piauí Colegiado de BiomedicinaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de MorfologiaUniversidade Federal do Pará Instituto de Ciências Biológicas Laboratório de Citogenética HumanaHospital João de Barros Barreto Serviço de CirurgiaInstituto de Investigaciones BiomedicasUniversidade de São Paulo Faculdade de Medicina de Ribeirão Preto Departamento de GenéticaUNIFESP, EPM, Depto. de MorfologiaFINEP/CT-INFRA: 0927-03SciEL

Genetic Diversity Strategy For The Management And Use Of Rubber Genetic Resources: More Than 1,000 Wild And Cultivated Accessions In A 100-genotype Core Collection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)The rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg.] is the only plant species worldwide that is cultivated for the commercial production of natural rubber. This study describes the genetic diversity of the Hevea spp. complex that is available in the main ex situ collections of South America, including Amazonian populations that have never been previously described. Genetic data were analyzed to determine the genetic structure of the wild populations, quantify the allelic diversity and suggest the composition of a core collection to capture the maximum genetic diversity within a minimal sample size. A total of 1,117 accessions were genotyped with 13 microsatellite markers. We identified a total of 408 alleles, 319 of which were shared between groups and 89 that were private in different groups of accessions. In a population structure and principal component analysis, the level of clustering reflected a primary division into the following two subgroups: cluster 1, which consisted of varieties from the advanced breeding germplasm that originated from the Wickham and Mato Grosso accessions; and cluster 2, which consisted of the wild germplasm from the Acre, Amazonas, Para and Rondonia populations and Hevea spp. The analyses revealed a high frequency of gene flow between the groups, with the genetic differentiation coefficient (GST) estimated to be 0.018. Additionally, no distinct separation among the H. brasiliensis accessions and the other species from Amazonas was observed. A core collection of 99 accessions was identified that captured the maximum genetic diversity. Rubber tree breeders can effectively utilize this core collection for cultivar improvement. Furthermore, such a core collection could provide resources for forming an association panel to evaluate traits with agronomic and commercial importance. Our study generated a molecular database that should facilitate the management of the Hevea germplasm and its use for subsequent genetic and genomic breeding.107Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)FAPESP [2007/50392-1, 2012/50491-8, 2011/50188-0, 2009/52975-0, 2012/05473-1]CNPq [478701/2012-8, 402954/2012-2

Subacute Cognitive Impairment in Individuals With Mild and Moderate COVID-19: A Case Series

Background: Previous reported neurologic sequelae associated with SARS-CoV-2 infection have mainly been confined to hospital-based patients in which viral detection was restricted to nasal/throat swabs or to IgM/IgG peripheral blood serology. Here we describe seven cases from Brazil of outpatients with previous mild or moderate COVID-19 who developed subacute cognitive disturbances. Methods: From June 1 to August 15, 2020, seven individuals 18 to 60 years old, with confirmed mild/moderate COVID-19 and findings consistent with encephalopathy who were observed >7 days after respiratory symptom initiation, were screened for cognitive dysfunction. Paired sera and CSF were tested for SARS-CoV-2 (IgA, IgG ELISA, and RT-PCR). Serum and intrathecal antibody dynamics were evaluated with oligoclonal bands and IgG index. Cognitive dysfunction was assessed by the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the Clock Drawing Test (CDT). Results: All but one of our patients were female, and the mean age was 42.6 years. Neurologic symptoms were first reported a median of 16 days (IQR 15–33) after initial COVID-19 symptoms. All patients had headache and altered behavior. Cognitive dysfunction was observed mainly in phonemic verbal fluency (MoCA) with a median of six words/min (IQR 5.25–10.75) and altered visuospatial construction with a median of four points (IQR 4–9) (CDT). CSF pleocytosis was not detected, and only one patient was positive for SARS-Co Conclusions: A subacute cognitive syndrome suggestive of SARS-CoV-2-initiated damage to cortico-subcortical associative pathways that could not be attributed solely to inflammation and hypoxia was present in seven individuals with mild/moderate COVID-19

Relato sobre o desenvolvimento de modelos para obtenção automática do conteúdo de sites sobre saúde

Este relato técnico descreve o desenvolvimento de modelos, técnicas e protótipos para localização, padronização e extração automática do conteúdo apresentado em sites/páginas web com assuntos relacionados à área da saúde, visando à estimativa da qualidade destes sites/páginas extraídos. As técnicas e propostas descritas neste documento foram desenvolvidas ao longo do primeiro semestre de 2009 pelos alunos da disciplina CMPl12 - Sistemas de Informação Distribuídos do Programa de Pós-Graduação do Instituto de Informática da Universidade Federal do Rio Grande do Sul, ministrada pelo Professor Dr. José Palazzo Moreira de Oliveira. Cada uma das tarefas descritas aplicou técnicas e tecnologias diferentes para o seu desenvolvimento, apresentando resultados de diferentes naturezas, como tabelas, protótipos e modelos. Entretanto, todas foram desenvolvidas em busca do mesmo objetivo: a extração automática do conteúdo de sites/páginas que tratam sobre o tema "Doença de Alzheimer". Ao final to trabalho, obteve-se um conjunto de resultados, os quais serão utilizados para possibilitar a realização de estimativas a respeito da qualidade dos sites/páginas extraídos, de acordo com métricas de qualidade definidas.This report describes the development of models, techniques and prototypes to location, standardization and automatic extraction of content presented in web sites/pages with subject related to health, objecting estimate its quality. The techniques and proposals described here was performed during the first half of 2009 by students of the lecture CMP112 – Distributed Information Systems of Institute of Informatics of Federal University of Rio Grande do Sul, conducted by Professor Dr. José Palazzo Moreira de Oliveira. Each one of the tasks described in this report used different techniques and technologies for their development, presenting results of different natures, such as tables, prototypes and models. However, all tasks were developed looking for the same objective: the automatic extraction of content from web sites/pages related with the subject “Alzheimer’s Disease”. At the end of the work, we obtained a set of results, which will be used to enable the development of estimative concerning the quality of extracted web sites/pages, according with defined quality metrics