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Olá 👋, sou o Edgar! Bem-vindo ao meu GitHub!

Meu nome é Edgar Oliveira e possuo graduação em Engenharia da Computação pela Faculdade Independente do Nordeste FAINOR (2021). Desenvolvo aplicações para hardware como os microcontroladores PIC, AVR(Arduino) e FPGA. Sou desenvolvedor de Softwares, pesquisador, entusiasta de tecnologia, Modelador 3D como também realizo a impressão das peças.

Sou desenvolvedor Full Stack na Meta Soluções em Vitória da Conquista / BA - Brasil, onde desenvolvemos softwares para empresas e atuamos no desenvolvimento da plataforma de soluções integradas de e-commerce para otimizar a performance de vendas além da otimização do tempo dos usuários.

Um pouco sobre mim:

  • 🎓 Graduado em Engenharia da Computação pela FAINOR .
  • 📱 Desenvolvedor Mobile Kotlin em Facilita.Tech .
  • 💻 Analista e desenvolvedor de software em Meta Soluções .
  • Atualmente desenvolvo aplicações WEB(Bootstrap, Js) e aplicações Mobile(Java, Kotlin). Publico sempre que possível projetos que desenvolvo em algumas línguagens como Python, JS, Goland, HTML, C++. Além de desenvolver projetos diários em VBA e PHP.
  • 📟 Desenvolvedor de Projetos com Arduino (Atmega328p), Raspberry Pi 3, e NodeMCU.
  • 🤓 Aprendendo sobre Goland, MongoDB, Firebase, Lora e SolidWorks.

Onde você pode me achar?



Experiência:

Facilita.Tech - Desenvolvedor Android Jr
Mar 2022 até o momento Utilizando a Metodologia Scrum:

  • Desenvolvimento com a linguagem Kotlin.
  • Desenvolvimento de interfaces gráficas
  • Comunicação com API Rest e banco de dados SQLite
  • Desenvolvimento utilizando GIT e GitHub.

SENAC - Professor no curso de Administrador de Banco de Dados
Nov 2020 até o momento Atuando no ensino da administração de banco de dados:

  • Banco de dados Relacionamental MySQL, MariaDB e SQLite.
  • Administração de recursos para manter um servidor BD.
  • Aplicações para consumir dados do banco
  • Monitoramento e manutenção de um banco.

Meta Soluções - Desenvolvedor de sistemas
Maio 2020 até o momento Atuação no desenvolvimento de aplicações, utilizando a metodologia ágil SCRUM:

  • Desenvolvimento de planilhas Excel utilizando VBA e banco Access.
  • Desenvolvimento de sistemas WEB com PHP, Javascript e Frameworks.
  • Criação e consumo de APIs para alimentar os sistemas
  • Plataforma E-Commerce.

Império Maker - Modelagem e Manufatura aditiva 3D
November 2019 até Fev 2022

Atuação na impressão 3D:

  • Modelagem de peças com SketchUp, Fusion360 e Blender.
  • Impressão 3D em FDM.
  • Fresagem em CNC.
  • Produção de E-commerce.

FAINOR - Ministro de Minicursos e Pesquisador IC
Junho 2019 até Nov 2021

Aluno em projeto de Iniciação Científica, atuo especificamente com Física e Computação através da experimentação e desenvolvimento de sistemas de software e hardware. Professor de minicurso FPGA e PIC, desde os conceitos teóricos, à prática e programação de placas de prototipagem, desenvolvendo assim projetos de hardware. Professor de Printed Circuit Board Curso de curta duração, tendo abordado a teoria de placas PCI e a elaboração de projetos.


Edgar Oliveira Cardoso's Projects

algoritmos-busca icon algoritmos-busca

Implementação do Algoritmo de Busca Binaria e Busca Sequencia em Python.

arduino-irremote icon arduino-irremote

Infrared remote library for Arduino: send and receive infrared signals with multiple protocols

arduino_projects icon arduino_projects

Repository containing the most varied tests and applications for the arduino uno (atmega328p).

assemblies-of-putative-sars-cov2-spike-encoding-mrna-sequences-for-vaccines-bnt-162b2-and-mrna-1273 icon assemblies-of-putative-sars-cov2-spike-encoding-mrna-sequences-for-vaccines-bnt-162b2-and-mrna-1273

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

awesome icon awesome

Uma lista dos materiais gratuitos diponibilizados pela Rocketseat, incluindo conteúdos do Blog, Youtube e Instagram.

beesic icon beesic

Balão estratosférico - Escola Secundária Inês de Castro, Vila Nova de Gaia, Portugal

bh1750fvi icon bh1750fvi

Arduino/ ESP8266 library for the ambient light sensor BH1750FVI

birl-language.github.io icon birl-language.github.io

BIRL (Bambam's "It's show time" Recursive Language), a linguagem descendente! Derrubar tudo essas árvores do Parque Ibirapuera! BIRL!

captk icon captk

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk/

cliente-servidor-echo-tcp-java icon cliente-servidor-echo-tcp-java

Implementação de Socket em comunicação TCP, onde é o servidor fica no aguardo para recebimento de mensagem pelo cliente. | Implementation of Socket in TCP communication, where the server is waiting to receive message by the client.

cliente-servidor-socket-data-java icon cliente-servidor-socket-data-java

Implementação de Socket em comunicação TCP, para solicitar a Data pelo Cliente e o Servidor Retornar. | Implementation of Socket in TCP communication, to request the Date by the Client and the Return Server.

cliente-servidor-udp-java icon cliente-servidor-udp-java

Implementação de DatagramSocket em comunicação UDP, onde é o servidor fica no aguardo para recebimento de mensagem pelo cliente. | Implementation of DatagramSocket in UDP communication, where the server is waiting to receive messages by the client.

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