JOURNAL OF BIOENGINEERING, TECHNOLOGIES AND HEALTH

A Comprehensive Survey on LDPC Code Design for CV-QKD

Mauro Queiroz Nooblath Neto — 2026-07-08

Continuous-Variable Quantum Key Distribution (CV-QKD) represents a promising technology for secure communication, but its practical implementation heavily relies on highly efficient information reconciliation (IR) to extract a secret key from correlated quantum data shared over noisy channels. Low-density parity-check codes (LDPC) have emerged as the state-of-the-art solution for this task due to their capacity-approaching performance. However, designing LDPC codes that perform reliably in the very low signal-to-noise ratio (SNR) regime of CV-QKD, while preserving practical implementation complexity, remains a major challenge. This work presents a comprehensive survey of LDPC code design methodologies for CV-QKD, with particular emphasis on three key structural classes: Quasi-Cyclic (QC-LDPC), Multi-Edge Type (MET-LDPC), and their hybrid form (QC-MET-LDPC).

Automation of Patent Searches at INPI: A Web Scraping and Data Analysis Approach

João Alexandre Brito — 2026-07-08

Patent searches are an essential step in technological development and innovation, but the traditional search process can be time-consuming and inefficient. This article presents PATENTIA, a system that automates patent searches at the National Institute of Industrial Property (INPI) using web scraping techniques and relational database data storage. The system allows the separation and analysis of patent data, presenting it in an organized way in a web interface developed with React and Node.js. In addition, the tool allows the export of results in Excel format, making it a useful resource for researchers, inventors, and companies. This study details the development of the tool, the challenges encountered, and the benefits of automation in the patent search process.

A Proposal for Applying Bio-inspired Optimization Algorithms: A Comparative Study of Genetic Algorithms and Particle Swarm Optimization for Sensor Selection

Daniel do Carmo Silva Ribeiro — 2026-07-08

This paper presents an application proposal and a comparative study between two bio-inspired optimization algorithms: Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The main objective is to demonstrate the effectiveness of these algorithms in selecting a subset of sensors, aiming to minimize the variance of the collected data. Through the analysis of results from two distinct datasets, this work explores the convergence characteristics, final population distribution, and the profile of the sensors selected by each algorithm. The results indicate that while both algorithms are capable of finding satisfactory solutions, GA tends to achieve better optimization values (lower standard deviation), whereas PSO demonstrates faster convergence. This study contributes to the understanding of the capabilities and limitations of each approach in problems of feature selection and sensing systems optimization.

Data Acquisition and Communication in CNC Machine Tools for PdM

Marcus Vinicius Ramos Figueiredo — 2026-07-08

In addition to the traditional requirements of quality and productivity, new production paradigms also demand fault prognosis and diagnosis capabilities that classical maintenance methods do not provide. In this scenario, the application of predictive maintenance emerges as a viable alternative. Predictive maintenance is a technique that uses monitoring systems to analyze the condition of assets, based on data collected from sensors, to prevent or avoid failures. By estimating the future condition of machine components, maintenance costs can be reduced, operating time can be increased, and maintenance tasks can be optimized. Despite these advantages, the technique is not yet widely adopted within the manufacturing sector because it requires sensing and data processing resources that make its implementation costly. To facilitate the implementation of this technique in the manufacturing sector, a low-cost hardware for data acquisition was proposed. Based on the system's components, an architecture for communicating the collected data and an application model were proposed, which allow for the visualization of this data and serve as a basis for implementing predictive algorithms for fault detection and anomaly prediction. After implementation on a demonstration machine, the system is expected to be capable of collecting machine data in real-time, enabling the identification of faults and anomalies, thereby reducing downtime and costs. This adds benefits to various organizational levels, such as at the operational level, through the reduction of unplanned stops and increased safety. In the maintenance and process sector, it facilitates a transition from preventive to proactive methods. In terms of strategic results, it leads to the reduction of operational costs and an increase in the reliability and predictability of production.

Trajectory Planning for Manipulators on Mobile Bases and in Dynamic Environments, Using Adaptive Models

Anderson Queiroz do Vale — 2026-07-08

This study addresses the challenges of trajectory planning for mobile manipulators whose base moves continuously during capture tasks. The main difficulty lies in adapting planning algorithms to dynamic scenarios, where base displacement compromises motion accuracy and efficiency. Traditional algorithms, developed for static or predictable environments, are unsuitable for unpredictable base movements. Key challenges include recalculating trajectories in real time to maintain safety and efficiency, while considering embedded systems’ computational constraints and the need for rapid responses to avoid collisions and optimize manipulation. To overcome these issues, approaches must integrate dynamic data and generate feasible trajectories regardless of base position. This work proposes adapting and evaluating two widely used motion planning algorithms: Rapidly-exploring Random Tree (RTT) and Real-Time Adaptive Motion Planning (RAMP). Both will be modified to account for base displacement, ensuring safe and efficient trajectories. Adjustment strategies will be embedded into the planning process, enabling algorithms to react dynamically to environmental and base position changes. Implementation will occur in a simulated environment, with a manipulator on a mobile base interacting with dynamically modeled objects. Experiments will assess accuracy, response time, and robustness. Expected outcomes include improved adaptation to base variations, reduced execution times, and enhanced object capture performance. These optimizations aim to advance real-world applications of mobile manipulators in industrial and assistive robotics.

Sodium Bicarbonate and Citric Acid as Blowing Agents in Polymer Composites with Recycled Textiles: An Alternative to Azodicarbonamide

Marcus Vinicius Badaró de Oliveira Ribeiro — 2026-07-08

The study evaluated the influence of sodium bicarbonate (SB) combined with citric acid (CA) as a blowing agent in polymeric compounds produced from recycled polymer and textile waste, comparing its performance with the conventional agent azodicarbonamide (ADC). The compounds were processed in a thermokinetic mixer (DRAISS Homogenizer), and the specimens were prepared by hydraulic press molding, using formulations with 5% and 10% of each blowing agent. Density measurements showed that the SB + CA combination, at a 10% concentration (FCSB10), achieved a 19.29% reduction in density compared to the non- expanded reference, surpassing the applications with azodicarbonamide. Although ADC was slightly more effective at lower concentrations (5%), the combined sodium bicarbonate and citric acid system demonstrated expansion without the need for initiators and without exposure to toxicological risks. The results indicate that this system may be a viable and sustainable alternative to ADC for producing expanded polymers, although adjustments in processing parameters and optimization are still required.

Analysis of the Influence of ISR with TiO₂ Addition on the Compressive Strength and Durability of Structural Self-Compacting Concrete Associated with Porosity

Pedro Victor Correia e Reis — 2026-07-08

In the contemporary global landscape, efforts to reduce energy consumption and mitigate the carbon footprint associated with products and human activities have intensified, with the construction industry emerging as one of the most environmentally impactful sectors due to its substantial consumption of natural resources and significant waste generation. Among the sustainable strategies under investigation, the reuse of industrial or mining residues through their incorporation into construction materials has gained particular relevance. Within this framework, the present study evaluates the utilization of industrial solid residue (ISR) generated during TiO₂ extraction for pigment production as an additive in cementitious matrices, aiming both to ensure the environmentally responsible disposal of this waste and to harness the photocatalytic potential of the residual TiO₂. Specifically, the research investigates the incorporation of 15% ISR into structural self-compacting concrete (fck ≥ 30 MPa), assessing its influence on key physical and mechanical properties, with emphasis on apparent porosity, water absorption, and axial compressive strength. Experimental results revealed marked increases in water absorption (12.03% for ISR vs. 6.73% for REF), void index (24.23% vs. 14.56%), and capillary absorption (1.71 g/cm² vs. 0.86 g/cm²), alongside a reduction in compressive strength (31.32 MPa vs. 32.61 MPa). These findings indicate that ISR incorporation significantly modifies the concrete microstructure, promoting greater capillary pore formation and diminishing mechanical performance. While the resulting material complies with applicable technical standards, the observed microstructural changes underscore the need for further durability investigations to fully ascertain the long-term implications for service life and structural performance.

An Intelligent Data Platform for Older Adults Health Monitoring Using Wearable Technologies

Lucas de Freitas Gomes — 2026-07-08

The aging of the global population has intensified the demand for innovative and sustainable healthcare strategies. Wearable technologies stand out as a promising alternative to enable real-time monitoring, early detection of clinical changes, and the promotion of autonomy and well-being among the older adults. This study presents a proposal for an integrated data platform aimed at monitoring elderly health through wearable devices. The proposed architecture comprises biometric sensors, secure wireless connectivity, intelligent data processing using machine learning algorithms, and interactive dashboards for decision-making. Through a comprehensive literature review and analysis of current applications, the platform was designed to ensure interoperability with healthcare systems, compliance with data protection laws, and usability for older adults. The results point to the potential of wearable technologies to support preventive, personalized, and population-based care models. Future challenges include issues of data integration, user acceptance, cost-effectiveness, and regulatory frameworks. The implementation of such platforms may contribute significantly to transforming the current healthcare model into a more inclusive, proactive, and data-driven system.

Evaluation of the Bioactive Compounds Present in Peanut Skin (Arachis hypogaea L.) for Antioxidant and Antifungal Activity

Letícia de Lima Santos Ferreira — 2026-07-08

Studies on peanuts (Arachis hypogaea L.) have shown that this food is rich in beneficial substances such as phenolic compounds and flavonoids. Peanut skin, the reddish-pink layer that surrounds the seed, is considered a by-product of processing and has a rich nutritional composition, containing a variety of phenolic compounds, including resveratrol and flavonoids, especially proanthocyanidins and their derivatives, which are predominant. These compounds have high antioxidant capacity and are able to neutralize free radicals, reducing oxidative stress associated with several chronic diseases. Some phenolic compounds also exhibit antifungal activity by inhibiting cell wall synthesis or altering fungal membranes. This study aimed to evaluate the presence and activity of phenolic compounds in peanut skin, focusing on antioxidant and antifungal properties. Ethanol extracts were tested through spectrophotometric quantification of total phenolics, flavonoids, and tannins, antioxidant activity using the DPPH method, and antifungal activity via agar disk diffusion against Fusarium sp. The extract showed strong antioxidant activity and high levels of phenolic compounds but limited antifungal activity. These findings support the potential of peanut skin compounds in food and pharmaceutical applications.

Assessment of the Nutraceutical Potential of the Biochemical Profile of Dunaliella salina Biomass

Sabrina dos Santos Rocha — 2026-07-08

Microalgae are recognized as promising sources of bioactive compounds for human health; however, gaps remain in the characterization and functional application of their biomass in dietary supplements. Dunaliella salina, despite its high biotechnological value, still lacks integrated studies addressing its nutraceutical potential and applicability in food products. Therefore, this study evaluated D. salina biomass as a sustainable food ingredient. The cultivation exhibited a well-defined exponential growth phase (µ = 0.0113 h⁻¹), allowing the identification of an optimal harvesting window (~10 days), which supported the efficient production of nutritionally rich biomass containing high levels of proteins (25.7 ± 0.42%), lipids (18.5 ± 0.06%), carbohydrates (28.5 ± 0.71%), and ash content (26%), along with phenolic compounds (2.16 ± 0.21 mg GAE 100 g⁻¹ DW) associated with antioxidant activity and oxidative stress reduction. These findings highlight the biotechnological potential of D. salina biomass as a sustainable nutraceutical supplement.

Comparative Performance Analysis of Public Lighting Luminaires According to NBR 5101:2018 and 2024 Standards

Rafael Argolo Ferreira — 2026-07-08

This study compares the performance of approximately 1,300 public lighting luminaires according to Brazilian standards NBR 5101:2018 and NBR 5101:2024. Using Dialux® software, over 37,500 simulations were conducted with IES photometric data from luminaires certified by INMETRO and listed by PROCEL. Five standard installation scenarios were modeled based on NBR 5101:2018 reference layouts. Results identify the most efficient luminaires for each case and outline the main changes in the 2024 standard, including correlated color temperature limits, stricter light pollution control, and reduced mounting angles. The findings indicate significant impacts on current projects and provide guidance for future public lighting implementations.

Quali-Quantitative Evaluation of Ficus benjamina L. in Street Tree Planting of Áureo Filho Housing Complex – Feira de Santana, BA, Brazil

Luciana Knop — 2026-07-08

Urban tree planting plays an essential role in the environmental quality of cities, offering ecological, aesthetic and social benefits. Among the species commonly used in Brazilian urban landscaping, Ficus benjamina L. stands out, although there is a scarcity of studies addressing its behavior and adaptability in the urban environment. Considering this, the present work aims to evaluate qualitatively and quantitatively the individuals of the species present in the street tree planting of the Áureo Filho Housing Complex, in Feira de Santana (BA). For this purpose, an in loco inventory was carried out, considering variables such as total height and bifurcation height, in addition to aspects such as the phytosanitary condition and the need for management. The results showed that the species represents a high percentage of the local tree planting, with heights that vary between 2 and 17 meters (average of 9.7 m). The presence of recurrent damage caused by drastic and inadequate pruning was also found. The general analysis indicated that 48.7% of the trees had phytosanitary issues, and that 53.8% need corrective actions. Therefore, the high frequency of planting the species, associated with the proximity between individuals, may be favoring the dissemination of pests and diseases. The data indicate the low suitability of Ficus benjamina L. to local conditions, thus reinforcing the need for careful planning in the selection of species for urban tree planting.

Numerical and Experimental Analysis of a Pre-Stressed Aluminum 6061-T6 Chassis for Offshore Structural Applications

Juan Carlos Romero Albino — 2026-07-08

This paper presents an integrated experimental and numerical investigation of the tensile and modal behaviors of a pre-stressed aluminum chassis (Al 6061-T6) designed for offshore structural applications. The chassis, composed of four metallic parts assembled with a 0.15 mm interference fit, was subjected to a tensile test in which the base was fixed using bolted plates and the upper part was pulled via a gripping device. The experimental force–displacement curve revealed a maximum force of 486.6 N at 1.25 mm displacement. To complement the experimental results, a finite element analysis (FEA) was performed in ANSYS Workbench, employing a nonlinear contact model with friction. Simulations were conducted with friction coefficients of 0.15 and 0.3, and the best agreement with the experimental data was achieved for μ = 0.15, yielding a maximum force of 474.9 N at the same displacement. Modal analyses were carried out for two assembly conditions: bonded contact (no interference) and interference fit with μ = 0.15. The bonded model exhibited natural frequencies of 29.015 Hz, 117.47 Hz, 137.76 Hz, 142.81 Hz, 168.04 Hz, and 344.21 Hz, while the pre-stressed model showed significantly higher values: 72.543 Hz, 73.861 Hz, 83.645 Hz, 217.59 Hz, 264.61 Hz, and 267.74 Hz. These results demonstrate that pre-stressing through interference fit not only enhances the static load-bearing capacity but also increases the dynamic stiffness, shifting natural frequencies to higher values. The findings provide valuable insights for the design and reliability assessment of pre-stressed metallic components in offshore environments. This integrated approach, combining experimental validation and advanced numerical modeling, supports the development of safer and more efficient offshore structural systems, ensuring improved performance under demanding operational conditions.

Unraveling Improvements in Underwater Leak Detection Using Color Channel Operations

Diego Perpétuo Andrade de Oliveira — 2026-07-08

This paper presents a computer vision approach for detecting underwater liquid leaks in the oil and gas industry, focusing on scenarios with limited datasets. We propose the use of color indices—originally developed for vegetation studies, such as ExGR and CIVE—as preprocessing to enhance visual contrast and improve deep learning performance. A custom dataset of 240 simulated leak images, captured in an aquarium under blue lighting, was processed using ExGR, CIVE, and a modified CIVE index developed in this study. The YOLO12n model was trained and evaluated across these configurations. Results show that the modified CIVE index achieved the highest accuracy, surpassing RGB and other indices, with notable gains in mAP. These findings demonstrate that combining tailored color indices with lightweight object detection models can enhance leak identification under adverse conditions, offering a cost-effective and efficient solution for environmental monitoring and operational safety.

Advances in Continuous Glucose Monitoring Systems: A Systematic Review of Sensor Technologies and Mobile Health Integration

Sara Lorena Martins Silva das Virgens — 2026-07-08

Several studies have focused on the evolution of Continuous Glucose Monitoring Systems (CGMS), particularly regarding their integration with mobile devices and the application of predictive strategies. Considering the increasing relevance of this technology in the healthcare sector, this systematic literature review aims to explore recent scientific advances, highlighting the main types of sensors, algorithms, and connectivity solutions described in the selected studies. The included articles presented innovative approaches involving microwave and electrochemical sensors, as well as techniques for glycemic trend prediction and mobile communication. The findings indicate significant progress in the development of CGMS, especially in real-time monitoring capabilities and the integration of artificial intelligence models for data analysis. However, challenges remain, such as improving sensor sensitivity and specificity, achieving clinical validation in real-life scenarios, and ensuring interoperability between different platforms and devices. The literature also emphasizes the importance of advancing user-centered design, data privacy, and regulatory compliance to facilitate the adoption of these systems in both clinical and personal health monitoring contexts. It is concluded that expanding the technological maturity and accessibility of CGMS is essential to support personalized diabetes management and to improve the quality of life for patients worldwide.

Literature Review on the Feasibility of Recycling Electrical and Electronic Waste (WEEE)

Alice Bispo dos Santos — 2026-07-08

The growing amount of waste electrical and electronic equipment (WEEE) is a global problem, with generation increasing five times faster than documented recycling. In 2022, 62 million tons of e-waste were produced, but less than 22.3% was collected and recycled properly. The aim of the work was to analyze the main polymers in WEEE, discuss the challenges of recycling and characterizing them, and explore the feasibility of applying them in the production of filaments for 3D printing. The methodology consisted of a qualitative analysis of 8 scientific articles selected from the Scopus and Web of Science databases. The research was limited to publications in English between 2003 and 2025. The results highlight the importance of characterization for recycling. Techniques such as FTIR, TGA and DSC are essential for understanding the chemical, thermal and mechanical properties of polymers. FTIR identifies compounds such as hydrocarbons and aromatic rings and is useful for unknown polymers. TGA measures the loss or gain of mass with temperature, indicating thermal degradation. DSC identifies changes in physical state, such as melting temperature (Tm), glass transition temperature (Tg) and crystallization temperature (Tc). Two recycling techniques are promising: chemical and mechanical. Chemical recycling, via pyrolysis, can convert plastics into useful monomers or fractions. However, plastics with brominated flame retardants (BFRs) can generate toxic substances. Pre-treatment methods, such as the CreaSolv® process, have proven effective in removing BFRs. Mechanical recycling faces challenges such as property degradation and material heterogeneity. Additive manufacturing (AM), especially FDM/FFF technology, is an alternative for reusing WEEE plastics and adding value. However, the variability of equipment shapes and sizes makes process automation complex.

Energy Justice and Microgrids in Vulnerable Urban Areas: A Sustainable Approach

Celso Barreto da Silva — 2026-07-08

This article explores the critical intersection between energy justice and the transformative role of microgrids in socially vulnerable urban areas. The research addresses inequalities in energy access that affect these communities, highlighting how the implementation of microgrids can promote equity, resilience, and sustainable development. The social, economic, and environmental benefits of integrating microgrids were analyzed, including benefits to communities, fostering the local economy, and reducing carbon emissions. The results achieved demonstrate that microgrids not only ensure a more reliable and accessible energy supply but also empower communities, allowing them greater control over their energy resources. The analysis of global success cases illustrates the viability and positive impact of these solutions, despite technical, financial, and regulatory challenges. We conclude that microgrids are an ally in building a more just and equitable energy future, with significant implications for public policies and future research aimed at overcoming energy poverty and promoting urban sustainability.