Marcelo Augusto Costa Fernandes

• Dr.
• Professor (Associate) at Federal University of Rio Grande do Norte

Purpose: Twist1 is a transcription factor that regulates embryonic development, stemness, and differentiation, and can also stimulate initiation of tumorigenesis in peripheral solid cancers. However, its role in central nervous system tumors, including medulloblastoma (MB), the main type of malignant brain cancer that afflicts children, remains poo...

This article targets the implementation of a bilateral control algorithm for haptic devices on FPGA platforms, using fixed-point arithmetic (FxP-F) to overcome latency and processing efficiency challenges. The results show significant improvements in processing speed and latency reduction, with an efficient implementation that leverages the flexibi...

In modern cloud environments, efficient management of computational resources is a critical challenge due to the growing demand for scalable and high-performance applications. Horizontal scaling in Kubernetes (K8s) clusters is essential for dynamically adjusting resources to match workload demands. However, their reactive nature often limits tradit...

Changes in epigenetic processes such as histone acetylation are proposed as key events influencing cancer cell function and the initiation and progression of pediatric brain tumors. Valproic acid (VPA) is an antiepileptic drug that acts partially by inhibiting histone deacetylases (HDACs) and could be repurposed as an epigenetic anticancer therapy....

Autonomous navigation in mobile robots represents a significant challenge in unknown and dynamic environments, where the need to avoid obstacles and find safe trajectories in real-time requires efficient solutions. This work presents the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which combines potential fields with population-based...

This study investigates the use of machine learning (ML) models combined with explainable artificial intelligence (XAI) techniques to identify the most influential genes in the classification of five recurrent cancer types in women: breast cancer (BRCA), lung adenocarcinoma (LUAD), thyroid cancer (THCA), ovarian cancer (OV), and colon adenocarcinom...

Background/Objectives: Most of the rapid inhibitory neurotransmission in the brain is mediated through activation of the γ-aminobutyric acid (GABA) type A (GABAA) receptor, which is a ligand-gated ion channel. GABAA receptor activation via GABA binding allows for an intracellular influx of Cl− ions, thus inducing cellular hyperpolarization. Each GA...

This work presents the development of an embedded platform using Field Programmable Gate Arrays (FPGAs) for real-time simulation of dynamic systems in industrial plants. The platform, Real-Time Simulator for Dynamic Systems in FPGA (RTSDS-FPGA), is designed for industrial and academic applications. In industrial contexts, the RTSDS-FPGA facilitates...

Changes in epigenetic processes such as histone acetylation are proposed as key events influencing cancer cell function and the initiation and progression of pediatric brain tumors. Valproic acid (VPA) is an antiepileptic drug that acts partially by inhibiting histone deacetylases (HDACs) and could be repurposed as an epigenetic anticancer therapy....

This paper presents a fuzzy logic-based approach for replica scaling in a Kubernetes environment, focusing on integrating Edge Computing. The proposed FHS (Fuzzy-based Horizontal Scaling) system was compared to the standard Kubernetes scaling mechanism, HPA (Horizontal Pod Autoscaler). The comparison considered resource consumption, the number of r...

Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory, cardiac, and gastrointestinal disorders in children and newborns, mostly due to the complexity of therapeutic management in pediatrics and neonatology, owing to the lack of suitable dosage forms for these patients, often rendering them “therapeutic...

Since the beginning of the COVID-19 pandemic, the World Health Organization (WHO) has been tracking SARS-CoV-2 mutations. The SARS-CoV-2 consistently mutated throughout the pandemic, which resulted in many variants. A variant is a viral genome containing one or more genetic code mutations. Deep learning techniques have been successfully used in man...

Purpose In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since...

This work proposes an implementation of the SHA-256, the most common blockchain hash algorithm, on a field-programmable gate array (FPGA) to improve processing capacity and power saving in Internet of Things (IoT) devices to solve security and privacy issues. This implementation presents a different approach than other papers in the literature, usi...

Retinoic acid (RA) regulates stemness and differentiation in human embryonic stem cells (ESCs). Ewing sarcoma (ES) is a pediatric tumor that may arise from the abnormal development of ESCs. Here we show that RA impairs the viability of SK-ES-1 ES cells and affects the cell cycle. Cells treated with RA showed increased levels of p21 and its encoding...

In order to address the growing problem of air pollution, it is necessary to implement innovative regulations and practical solutions to reduce and control its impact. Numerous studies have recommended using multivariate statistical methods to identify the connections and characteristics of atmospheric pollutants, which can provide valuable informa...

The literature on ECG delineation algorithms has seen significant growth in recent decades. However, several challenges still need to be addressed. This work aims to propose a lightweight R-peak-detection algorithm that does not require pre-setting and performs classification on a sample-by-sample basis. The novelty of the proposed approach lies in...

Rapid neuronal inhibition in the brain is mediated by γ-aminobutyric acid (GABA) activation of GABAA receptors. The GABRA5 gene, which encodes the α5 subunit of the GABAA receptor, has been implicated in an aggressive subgroup of medulloblastoma (MB), a type of pediatric brain tumor. However, the possible role of GABAA receptor subunits in glioma r...

Background DNA sequences harbor vital information regarding various organisms and viruses. The ability to analyze extensive DNA sequences using methods amenable to conventional computer hardware has proven invaluable, especially in timely response to global pandemics such as COVID-19. Objectives This study introduces a new representation that enco...

Gliomas comprise most cases of central nervous system (CNS) tumors. Gliomas afflict both adults and children, and glioblastoma (GBM) in adults represents the clinically most important type of malignant brain cancer, with a very poor prognosis. The cell surface glycoprotein CD114, which is encoded by the CSF3R gene, acts as the receptor for the gran...

Objective: The aim of this study was to use a machine learning algorithm to identify biomarkers of resistance to neoadjuvant chemotherapy (NACT) in breast cancer (BC). Methodology: We evaluated microarray gene expression data of BC samples before NACT from public datasets of the Gene Expression Omnibus database. We performed differential expression...

Deep learning techniques, such as deep neural networks (DNNs), have proven highly effective in addressing various automatic modulation classification challenges. However, their computational demands pose a significant hurdle for real-time modulation detection. To tackle this issue, a novel training strategy is proposed in this study. This strategy...

Este artigo faz uso de três técnicas de aprendizagem de máquina (Machine Learnig – ML) para classificar os cinco tipos de câncer mais recorrentes em mulheres, a partir de dados de expressão gênica de RNA-Seq. Os desafios incluem: alta dimensionalidade do conjunto de dados e a falta de transparência dos modelos de ML. Para mitigar esses problemas, f...

Este artigo apresenta um estudo que utiliza técnicas de aprendizado de máquina não supervisionado, com foco na técnica t-SNE, para estratificar o risco de mortalidade em recém-nascidos prematuros. A metodologia adotada envolve a coleta de dados das bases governamentais do Sistemas de Informações sobre Nascidos Vivos (SINASC) e do Sistemas de Inform...

O câncer de mama é a neoplasia maligna mais comum em ambos os sexos, representando um quarto dos diagnósticos de câncer em mulheres. Para melhorar a identificação e o desenvolvimento de terapias mais eficazes, e fundamental encontrar potenciais biomarcadores de prognostico. Neste estudo, uma abordagem foi desenvolvida utilizando técnicas de aprendi...

Preterm birth (PTB) poses risks and difficulties for the survival of the newborn baby. Despite considerable progress in research, the causes of PTB still need to be fully understood. PTB risk is believed to be multi-faceted and may be linked to socioeconomic factors. This research aims to categorize the risk of PTB in Brazil based on socioeconomic...

Este trabalho apresenta uma abordagem baseada em lógica Fuzzy para o escalonamento de réplicas em um ambiente Kubernetes. O sistema proposto, denominado FHS (Fuzzy-based Horizontal Scaling), foi comparado ao mecanismo padrão de escalonamento do Kubernetes, o HPA (Horizontal Pod Autoscaler). A comparação levou em consideração o consumo de recursos,...

Este artigo apresenta uma abordagem inovadora para o escalonamento horizontal automático em cluster Kubernetes (K8s), utilizando Redes Neurais Artificiais. A proposta é chamada de ANN-HS e em comparação com o Escalonador Horizontal padrão do K8s (HPA), o ANN-HS demonstra eficiência superior em termos de consumo de recursos, alocação otimizada de ré...

The article presents a new trajectory planning approach for mobile ground robots, named Dynamic Planning Navigation Algorithm optimized with Particle Swarm Optimization (DPNA-PSO), which utilizes the Particle Swarm Optimization (PSO) algorithm to replace the Genetic Algorithm (GA) used in the Dynamic Planning Navigation Algorithm optimized with Gen...

Este artigo apresenta uma nova estratégia de treinamento para compressão de modelos de redes neurais convolucionais (Convolutional Neural Networks - CNN). A estratégia proposta utiliza um esquema de poda consciente dos pesos da CNN, diferenciando-se das abordagens convencionais. Neste trabalho, a poda consciente é aplicada de forma contínua durante...

Purpose: The primary objective of this study was to develop and evaluate a deep neural network model based on convolutional neural networks (CNNs) for accurately classifying SARS-CoV-2 viral sequences and other subtypes within the Coronaviridae family. With the rapid evolution of viral genomes and the increasing need for timely classification, we a...

Experimental tools are a key factor in both academic and industrial research communities to create design evaluations of new networking technologies that involve troubleshooting or changing the planning of deployed networks. Physical Software-Defined Radio (SDR) experimental platforms enable a design solution for the quick prototyping of wireless c...

Background In December 2019, the first case of COVID-19 was described in Wuhan, China, and by July 2022, there were already 540 million confirmed cases. Due to the rapid spread of the virus, the scientific community has made efforts to develop techniques for the viral classification of SARS-CoV-2. Results In this context, we developed a new propos...

Most driver monitoring systems (DMS) rely on cameras facing the driver while detecting their gaze or head position. Both future automated driving (AD) in-vehicle interactions and AD vehicle interior designs (e.g., seating arrangement) might drastically reduce the effectiveness of such camera-based DMS solutions, however. Thus, alternative solutions...

Objective: The objective of this study was to identify possible biomarkers of resistance to neoadjuvant chemotherapy (NACT) in breast cancer (BC). Methodology: We evaluated microarray gene expression data of BC samples before NACT from three public datasets of the Gene Expression Omnibus database. We performed differential expression analyses compa...

This work aimed to develop a real-time test platform for systems associated with the tactile internet area. The proposal comprises a master device, a communication channel and a slave device. The master device is a tactile glove (wearable technology) that works as a tactile interface based on vibratory feedback. The master device can interact with...

Since December 2019, the world has been intensely affected by the COVID-19 pandemic, caused by the SARS-CoV-2. In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is essential for strategic planning, containment, and treatments. Deep learning techniques have been su...

Tactile internet applications allow robotic devices to be remotely controlled over a communication medium with an unnoticeable time delay. In bilateral communication, the acceptable round trip latency is usually 1 ms up to 10 ms, depending on the application requirements. The communication network is estimated to generate 70% of the total latency,...

Atmospheric pollution is a critical issue in our society due to the continuous development of countries. Therefore, studies concerning atmospheric pollutants using multivariate statistical methods are widely available in the literature. Furthermore, machine learning has proved a good alternative, providing techniques capable of dealing with problem...

This work proposes a fully parallel hardware architecture of the Naive Bayes classifier to obtain high-speed processing and low energy consumption. The details of the proposed architecture are described throughout this work. Besides, a fixed-point implementation on a Stratix V Field Programmable Gate Array (FPGA) is presented and evaluated regardin...

COVID-19, the illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus belonging to the Coronaviridade family, a single-strand positive-sense RNA genome, has been spreading around the world and has been declared a pandemic by the World Health Organization. On 17 January 2022, there were more than 329 million cases, w...

Nano-hybrid systems are products of interactions between organic and inorganic materials designed and planned to develop drug delivery platforms that can be self-assembled. Poloxamine, commercially available as Tetronic®, is formed by blocks of copolymers consisting of poly (ethylene oxide) (PEO) and poly (propylene oxide) (PPO) units arranged in a...

In bioinformatics, alignment is an essential technique for finding similarities between biological sequences. Usually, the alignment is performed with the Smith-Waterman (SW) algorithm, a well-known sequence alignment technique of high-level precision based on dynamic programming. However, given the massive data volume in biological databases and t...

Tactile Internet (TI) is a new internet paradigm that enables sending touch interaction information and other stimuli, which will lead to new human-to-machine applications. However, TI applications require very low latency between devices, as the system’s latency can result from the communication channel, processing power of local devices, and the...

Preterm birth (PTB) is a phenomenon that brings risks and challenges for the survival of the newborn child. Despite many advances in research, not all the causes of PTB are already clear. It is understood that PTB risk is multi-factorial and can also be associated with socioeconomic factors. Thereby, this article seeks to use unsupervised learning...

Drug discovery (DD) is a time-consuming and expensive process. Thus, the industry employs strategies such as drug repositioning and drug repurposing, which allows the application of already approved drugs to treat a different disease, as occurred in the first months of 2020, during the COVID-19 pandemic. The prediction of drug–target interactions i...

Since December 2019, the world has been intensely affected by the COVID-19 pandemic, caused by the SARS-CoV-2 virus, first identified in Wuhan, China. In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is essential for strategic planning, containment, and treatment...

In bioinformatics, alignment is an essential technique for finding similarities between biological sequences. Usually, the alignment is performed with the Smith-Waterman (SW) algorithm, a well-known sequence alignment technique of high-level precision based on dynamic programming. However, given the massive data volume in biological databases and t...

The amount of data in real-time, such as time series and streaming data, available today continues to grow. Being able to analyze this data the moment it arrives can bring an immense added value. However, it also requires a lot of computational effort and new acceleration techniques. As a possible solution to this problem, this paper proposes a har...

This work proposes a high-throughput implementation of the Otsu automatic image thresholding algorithm on Field Programmable Gate Array (FPGA), aiming to process high-resolution images in real-time. The Otsu method is a widely used global thresholding algorithm to define an optimal threshold between two classes. However, this technique has a high c...

Deep Learning techniques have been successfully applied to solve many Artificial Intelligence (AI) applications problems. However, owing to topologies with many hidden layers, Deep Neural Networks (DNNs) have high computational complexity, which makes their deployment difficult in contexts highly constrained by requirements such as performance, rea...

Self-Organizing Maps (SOMs) are extensively used for data clustering and dimensionality reduction. However, if applications are to fully benefit from SOM based techniques, high-speed processing is demanding, given that data tends to be both highly dimensional and yet “big”. Hence, a fully parallel architecture for the SOM is introduced to optimize...

This work proposes an implementation in Field Programmable GateArray (FPGA) of the Otsu’s method applied to real-time trackingof worms called Caenorhabditis elegans. Real-time tracking is necessaryto measure changes in the worm’s behavior in response totreatment with Ribonucleic Acid (RNA) interference. Otsu’s methodis a global thresholding algorit...

Em dezembro de 2019 o primeiro caso de COVID-19 foi descrito em Wuhan, na China, e em abril de 2021, já haviam 136 milhões de casos confirmados. Devido a rápida propagação do vírus, esforços vêm sendo realizados pela comunidade científica para o desenvolvimento de técnicas de classificação viral do SARS-CoV-2. Neste trabalho foi desenvolvido, utili...

Este artigo propõe uma técnica, baseada em aprendizado de máquina, que faz uso de uma rede neural convolucional (Convolutional Neural Network – CNN) profunda de uma dimensão (1D), destinada à classificação de genomas virais, capaz de identificar corretamente o vírus SARS-CoV-2, causador da doença COVID-19. Como entrada, foi utilizado amostras genôm...

Este trabalho tem como objetivo aplicar uma nova abordagem para a análise de dados de poluentes atmosféricos através de uma técnica aprendizagem de máquina. A técnica é baseada em uma rede neural artificial não supervisionada do tipo mapas auto-organizáveis. A análise foi realizada na cidade de Salvador – Bahia em uma única estação de monitoramento...

O nascimento prematuro (Preterm birth – PTB) é um fenômeno que traz diversos riscos e desafios à sobrevivência dos recém-nascidos. Apesar de muitos avanços, ainda não foram esclarecidas todas as causas desse fenômeno. Entende-se que o risco ao PTB é multi-fatorial e também pode estar associado a fatores socioeconômicos. Assim, este artigo tem como...

Este trabalho propõe uma implementação em hardware do classificador Naive Bayes, tendo como objetivo o desenvolvimento de uma arquitetura totalmente paralela, que visa obter alta performance em termos de velocidade de processamento e consumo energético. O hardware proposto foi desenvolvido em Field Programmable Gate Array (FPGA) utilizando ponto fi...

Nano-hybrid formulations combine organic and inorganic materials in self-assembled platforms for drug delivery. Laponite is a synthetic clay, biocompatible, and a guest of compounds. Poloxamines are amphiphilic four-armed compounds and have pH-sensitive and thermosensitive properties. The association of Laponite and Poloxamine can be used to improv...

This work presents a strategy to implement a distributed form of genetic algorithm (GA) on low power, low cost, and small-sized memory aiming for increased performance and reduction of energy consumption when compared to standalone GAs. This strategy focuses on making a distributed version of GA feasible to run as a low cost and a low power consump...

Nowadays, Deep Learning DL becoming more and more interesting in many areas, such as genomics, security, data analysis, image, and video processing. However, DL requires more and more powerful and parallel computing. The calculation performed by super-machines equipped with powerful processors, such as the latest GPUs. Despite their power, these co...

The adoption of intelligent systems with Artificial Neural Networks (ANNs) embedded in hardware for real-time applications currently faces a growing demand in fields such as the Internet of Things (IoT) and Machine to Machine (M2M). However, the application of ANNs in this type of system poses a significant challenge due to the high computational p...

This work proposes a strategy to create an embedded genetic algorithms (GAs) for low‐power, low‐cost, and low‐size‐memory devices. This strategy aims to provide the means of GAs to run as a low‐cost and low‐power consumption embedded system, where microcontrollers (μCs) are commonly used. The implementation details are presented, emphasizing the li...

Self-Organizing Maps (SOMs) are widely used as a data mining technique for applications that require data dimensionality reduction and clustering. Given the complexity of the SOM learning phase and the massive dimensionality of many data sets as well as their sample size in Big Data applications, high-speed processing is critical when implementing...

The adoption of intelligent systems with Artificial Neural Networks (ANNs) embedded in hardware for real-time applications currently faces a growing demand in fields like the Internet of Things (IoT) and Machine to Machine (M2M). However, the application of ANNs in this type of system poses a significant challenge due to the high computational powe...

As of May 25, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 348,000 deaths and more than 5,550,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approaches such as data stream techniques and algorithms. H...

This work proposes dedicated hardware to real-time cancer detection using Field-Programmable Gate Arrays (FPGA). The presented hardware combines a Multilayer Perceptron (MLP) Artificial Neural Networks (ANN) with Digital Image Processing (DIP) techniques. The DIP techniques are used to extract the features from the analyzed skin, and the MLP classi...

As of May 25, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 348,000 deaths and more than 5,550,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approaches such as data stream techniques and algorithms. H...

This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and floating-point). Two hardware designs are proposed;...

The dataset provides a chaos game representation (CGR) of SARS-CoV-2 virus nucleotide sequences. The dataset is composed of 100 virus instances of SARS-CoV-2. In addition, the dataset also provides a CGR representation of 11540 viruses from the Virus-Host DB dataset and the other three Riboviria viruses from NCBI.

As of April 16, 2020, the novel coronavirus disease (called COVID-19) spread to more than 185 countries/regions with more than 142,000 deaths and more than 2,000,000 confirmed cases. In the bioinformatics area, one of the crucial points is the analysis of the virus nucleotide sequences using approaches such as data stream, digital signal processing...

This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and other floating-point). Two hardware designs are pro...

Tactile internet applications allow robotic devices to be remotely controlled over a communication medium with an unnoticeable time delay. In a bilateral communication, the acceptable round trip latency is usually in the order of 1ms up to 10ms depending on the application requirements. It is estimated that 70% of the total latency is generated by...

The amount of data in real-time, such as time series and streaming data, available today continues to grow. Being able to analyze this data the moment it arrives can bring an immense added value. However, it also requires a lot of computational effort and new acceleration techniques. As a possible solution to this problem, this paper proposes a har...

The K-means algorithm is widely used to find correlations between data in different application domains. However, given the massive amount of data stored, known as Big Data, the need for high-speed processing to analyze data has become even more critical, especially for real-time applications. A solution that has been adopted to increase the proces...

This study evaluated the incorporation of tetracaine into liposomes by RSM (Response Surface Methodology) and ANN (Artificial Neural Networks) based models. RCCD (rotational central composite design) and ANN were performed to optimize the sonication conditions of particles containing 100 % lipid. Laser light scattering was used to perform measure h...

This project aims to develop a tactile glove device and a virtual environment inserted in the context of tactile internet. The tactile glove allows a human operator to interact remotely with objects from a 3D environment through tactile feedback or tactile sensation. In other words, the human operator is able to feel the contour and texture from vi...