Search

Macroalgae are a natural oceanic resource of inexhaustible abundance for the biomass energy industry with growth rates that are three to four times greater than those of terrestrial plants. The objective of this study was to evaluate the sustainability of macroalgae as biomass for biorefining through two investigations. Firstly, the deposition of macroalgae was sampled through 28 collections on seven beaches in the city of Maceió, Brazil, over a two-year period using a zigzag sampling method, covering a deposition area of 135,000 m2. From this, it was estimated that daily collection would yield 5.03 t/ha of dry biomass. Secondly, the calorific values of macroalgal biomass energy and pellet compounds were calculated. The lower calorific value (8.82 MJ/kg) found from a compound of 13 species analyzed was similar to that of the main biomass used in Brazil to obtain energy, i.e., sugarcane bagasse, which has been evaluated as 8.91 MJ/kg. Macroalgal biomass in the form of condensed energy pellets was found to have a higher calorific value of 20.18 MJ/kg, i.e., 1.2% greater than the average for terrestrial biomass pellets. Based on the results obtained, it was observed that macroalgal biomass has the possibility of becoming a new renewable feedstock with potential for bioenergy. The estimates for the deposition of biomass show possibilities for producing biofuels from marine algal raw material, which provides scope for creating another sustainable alternative for global energy issues with a reduction in environmental problems.

Abstract Background Anthonomus grandis grandis is the main cotton pest in the Americas, with the potential to become a pest in other continents. The insect uses the plant’s reproductive organs for feeding, oviposition, and survival strategies in the off-season, sheltering in dry bolls. This study aimed to know the reproductive potential, feeding, longevity, and morphometric characteristics of boll weevils from dry bolls, squares, and traps. Adults were obtained from infested squares, dry bolls, and traps installed in cotton fields and the Caatinga area. Thirty weevil pairs were maintained in the laboratory to assess the oviposition, feeding holes, longevity, and morphometric measurements of the parental and F1 generations. Results In the parental generation, boll weevils from traps (the Caatinga area and cotton cultivation) showed greater reproductive potential. Boll weevils from squares and the Caatinga area showed greater feeding activity compared with those from cotton cultivation. Greater rostrum length, thorax + abdomen length, and abdomen width were observed in boll weevils from cotton cultivation and dry bolls. The origin of boll weevils parental generation did not affect progeny emergence time. The F1 generation of boll weevils showed significant differences in average longevity depending on the origin of different microhabitats. Furthermore, differences in rostrum lengths were observed, with the boll weevils coming from traps installed in cotton cultivation, the Caatinga area, and dry bolls being the largest. Regarding thorax + abdomen length and abdomen width, the highest values were observed in those from the Caatinga area and cotton cultivation. Conclusion It was proven that dry bolls did not affect the reproductive, feeding, and longevity performance of boll weevils, enabling better insect fitness (reproduction and size) in relation to those coming from squares. The use of dry bolls as off-season shelter is an important survival strategy for the boll weevil.

Abstract Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets. To assess our model, we used a dataset of 144 Human G-protein Coupled Receptors (GPCRs) with over 140,000 measured inhibition constants (Ki) values. Results strongly suggest that our approach performs as well as state-of-the-art ligand-based methods. In a second modeling approach that used 129 targets for training and a separate test set of 15 different protein targets, our model correctly predicted interactions for 73% of targets, with explained variances exceeding 0.50 in 22% of cases. Our findings further verified that the usage of experimentally determined protein structures produced models that were statistically indistinct from the Alphafold synthetic structures. This study presents a proteo-chemometric drug screening approach that uses a simple and scalable method for extracting protein structural information for usage in machine learning models capable of predicting protein-molecule interactions even for orphan targets.

ABSTRACT The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others.

A prototype of an autonomous system for the retrieval of oceanographic, wave, and meteorologic data was installed and tested in May 2021 on a Portuguese research vessel navigating on the Atlantic Ocean. The system was designed to be installed in fishing vessels that could operate as a distributed network of ocean data collection. It consists of an automatic weather station, a ferrybox with a water pumping system, an inertial measurement unit, a GNSS unit, an onboard desktop computer, and a wave estimator algorithm for wave spectra estimation. Among several parameters collected by this system’s sensors are the air temperature, barometric pressure, humidity, wind speed and direction, sea water temperature, pH, dissolved oxygen, salinity, chlorophyll-a, roll, pitch, heave, true heading, and geolocation of the ship. This paper’s objectives are the following: (1) describe the autonomous prototype; and (2) present the data obtained during a full-scale trial; (3) discuss the results, advantages, and limitations of the system and future developments. Meteorologic measurements were validated by a second weather station onboard. The estimated wave parameters and wave spectra showed good agreement with forecasted data from the Copernicus database. The results are promising, and the system can be a cost-effective solution for voluntary observing ships.

This paper explores the cooperative control of unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) in maritime rescue and coastal surveillance. The USV-UAV system faces challenges of disturbances and substantial inertia-induced overshooting during path following. A novel position prediction line of sight (LOS) guidance law is proposed to address these issues for USV path following control. Radial basis function-based neural networks (RBF-NNs) are used to estimate disturbances, and a high-order differentiator is used to design a velocity observer for unknown USV velocity. The UAV control system employs proportional–derivative (PD) control with feedforward compensation for quadrotor control design and utilizes a finite-time converging third-order differentiator to differentiate non-continuous functions. The simulation results demonstrate strong robustness in the proposed USV-UAV cooperative control algorithm. It achieves path following control in the presence of wind and wave disturbances and exhibits minimal overshoot.

Abstract Background To control the boll weevil Anthonomus grandis grandis (Coleoptera: Curculionidae), a key pest of cotton in the Americas, insecticides have been intensively used to manage their populations, increasing selection pressure for resistant populations. Thus, this study aimed to detect insecticide resistance and assess insecticide control failure likelihood of boll weevil populations exposed to malathion, profenophos + cypermethrin, and fipronil insecticides. Results Twelve populations of the boll weevil were collected from commercial cotton fileds of the state of Bahia, northeastern Brazil. These populations were exposed to malathion, profenophos + cypermethrin mixture, and fipronil, at their respective maximum label dose for field applications. Three replicates of 10 adult beetles were exposed to the insecticides and mortality was recorded after 24 h treatment. The control failure likelihood was determined after 48 h. Highest median lethal times (LT 50) were observed for malathion and the profenophos + cypermethrin mixture. Resistance to at least one insecticide was detected in 11 populations; three populations were resistant to malathion and profenophos + cypermethrin; seven were resistant to all insecticides tested. The resistance levels were low (

The present review focuses on the theoretical model developments made in floating flexible net fish cages and the floating bodies application to offshore aquaculture. A brief discussion of the essential mathematical equations related to various theoretical models of flexible net cages in the frequency domain is presented. The single and array of floating or submerged flexible net cages connected with or without mooring lines are discussed. Further, as the combined effect of the hydroelastic behaviour of floaters and the flexible behaviour of fish cages are necessary to assess their efficiency and survivability from structural damages, the issues and the knowledge gap between the recent and future models are also discussed. In conclusion, the practical suggestions concerning advancements in future research and directions within floating flexible net cages and the hydroelastic response of elastic floaters are highlighted.

This paper is dedicated to correcting the WAM/ICON numerical wave model predictions by reducing the residue between the model’s predictions and the actual buoy observations. The two parameters used in this paper are significant wave height and wind speed. The paper proposes two machine learning models to solve this task. Both models are multioutput models and correct the significant wave height and wind speed simultaneously. The first machine learning model is based on gradient boosted trees, which is trained to predict the residue between the model’s forecasts and the actual buoy observations using the other parameters predicted by the numerical model as inputs. This paper demonstrates that this model can significantly reduce errors for all used geographical locations. This paper also uses SHapley Additive exPlanation values to investigate the influence that the numerically predicted wave parameters have when the machine learning model predicts the residue. To design the second model, it is assumed that the residue can be modelled as noise added to the actual values. Therefore, this paper proposes to use the denoising autoencoder to remove this noise from the numerical model’s prediction. The results demonstrate that denoising autoencoders can remove the noise for the wind speed parameter, but their performance is poor for the significant wave height. This paper provides some explanations as to why this may happen.

A 3D analytical model is formulated based on linearised small-amplitude wave theory to analyse the behaviour of a horizontal, flexible membrane subject to wave–current interaction. The membrane is connected to spring moorings for stability. Green’s function approach is used to obtain the dispersion relation and is utilised in the solution by applying the velocity decomposition method. On the other hand, a brief description of the experiment is presented. The accuracy level of the analytical results is checked by comparing the results of reflection and the transmission coefficients against experimental data sets. Several numerical results on the displacements of the membrane and the vertical forces are studied thoroughly to examine the impact of current loads, spring stiffness, membrane tension, modes of oscillations, and water depths. It is observed that as the value of the current speed (CS) rises, the deflection also increases, whereas it declines in deeper water. On the other hand, the spring stiffness has minimal effect on the vibrations of the flexible membrane. When vertical force is considered, higher oscillation modes increase the vertical loads on the membrane, and for a mid-range wavelength, the vertical wave loads on the membrane grow as the CS increases. Further, the influence of the phase and group velocities are presented. The influences of CS and comparisons between them in terms of water depth are presented and analysed. This analysis will inform the design of membrane-based wave energy converters and breakwaters by clarifying how current loads affect the dynamics of floating membranes at various water depths.

A set of planar motion mechanism experiments of the Duisburg Test Case Post-Panamax container model executed in a towing tank with shallow depth is applied to train a neural network to analyse the ability of the proposed model to learn the effects of different depth conditions on ship’s manoeuvring capabilities. The motivation of the work presented in this paper is to contribute an alternative and effective approach to model non-linear systems through artificial neural networks that address the manoeuvring simulation of ships in shallow water. The system is developed using the Levenberg–Marquardt backpropagation training algorithm and the resilient backpropagation scheme to demonstrate the correlation between the vessel forces and the respective trajectories and velocities. Sensitivity analyses were performed to identify the number of layers necessary for the proposed model to predict the vessel manoeuvring characteristics in two different depths. The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.

Proliferative enteropathy is an enteric disease caused by the bacterium Lawsonia intracellularis, which affects several species of domestic and wild animals. The mechanisms underlying the mechanisms employed by L. intracellularis to cause host cell proliferation are poorly understood, mostly because this bacterium is extremely difficult to isolate and propagate in vitro. Comparative genomics methods for searching for genes orthologous to genes known to be associated with pathogenesis allow identification of genes potentially involved in pathogenesis by the pathogen of interest. The goal of this study was to carry out in silico research on L. intracellularis genes orthologous to genes required for intracellular invasion and survival present in other pathogenic bacteria, particularly Brucella abortus, B. melitensis, B. suis, Listeria monocytogenes, Mycobacterium tuberculosis, Mycobacterium avium subspecies paratuberculosis, Salmonella enterica, Yersinia pestis, Y. enterocolitica, and Y. pseudotuberculosis. A total of 127 genes associated with invasion and intracellular survival from five known intracellular bacteria were mapped against the predicted proteomes of all L. intracellularis strains publicly available on GenBank, using the OrthoFinder program. A total of 45 L. intracellularis genes were orthologous to genes associated with pathogenesis of other intracellular bacteria. Genes putatively associated with signal the transduction of chemotaxis and cell motility were identified. Genes related to DNA binding and repair were also identified, with some of them supporting a possible association of bacteria with macrophages or inducing pro-inflammatory responses. The homology-based identification of these genes suggests their potential involvement in the virulence and pathogenicity of L. intracellularis, opening avenues for future research and insights into the molecular mechanisms of Lawsonia-elicited proliferative enteropathy.

Repetitive movements and the speed of upper limbs increase the risk of musculoskeletal disorders. This study aimed to analyse the risk of shoulder injuries in repetitive tasks by evaluating the humerus angle, angular velocity, and angular acceleration during simulated chicken wing cutting. The study was conducted in a laboratory simulating a real environment. Thirty-six healthy right-handed volunteers were assessed using an electromagnetic tracking device, TrakSTAR, integrated with MotionMonitor™ (Innovative Sports Training, Inc. Chicago, IL) and software to collect 3-D kinematic data developed in the research centre. The equipment measured the angles performed by the upper limbs during the entire movement. The humerus angles were automatically transformed into angular velocity (°·s−1) and angular acceleration (°·s−2). Maximum angular velocities were 27.39°·s−1 (men, right humerus) and 22.39°·s−1 (women, left humerus), both below the safe limit. Maximum accelerations were 25.32°·s−2 (men, left side) and 28.94°·s−2 (women, left side); safety values for these accelerations are not established. Monotony is a risk factor, especially for the dominant side. Future studies should evaluate risk factors simultaneously in repetitive tasks. Repetitiveness exceeds the safe limit according to the OCRA method.

The novel hydrosoluble silver coordination polymer [Ag(NO3)(μ-1κN;2κN′,N″-TPMOH)]n (1) (TPMOH = tris(1H-pyrazol-1-yl)ethanol) was obtained and characterized. While single crystal X-ray diffraction analysis of compound 1 disclosed an infinite 1D helical chain structure in the solid state, NMR analysis in polar solvents confirmed the mononuclear nature of compound 1 in solution. Compound 1 and the analogue [Ag(μ-1κN;2κN′,N″-TPMS)]n (2) (TPMS = tris(1H-pyrazol-1-yl)methane sulfonate) were evaluated with regard to their antimicrobial activities towards the Gram-negative Escherichia coli, Pseudomonas aeruginosa, and Burkholderia contaminans, the Gram-positive Staphylococcus aureus, and the fungal species Candida albicans and Candida glabrata. Compound 1 exhibited minimal inhibitory concentration (MIC) values ranging from 2 to 7.7 µg/mL towards the tested Gram-negative bacteria, 18 µg/mL towards the Gram-positive S. aureus, and 15 and 31 µg/mL towards C. albicans and C. glabrata, respectively. Compound 2 was less effective towards the tested bacteria, with MIC values ranging from 15 to 19.6 µg/mL towards the Gram-negative bacteria and 51 µg/mL towards S. aureus; however, it was more effective against C. albicans and C. glabrata, with MIC values of about 6 µg/mL towards these fungal species. The toxicity of compounds 1 and 2 was assessed by evaluating the survival of the Caenorhabditis elegans model organism to concentrations of up to 100 µg/mL. The value of 50% lethality (LD50) could only be estimated as 73.2 µg/mL for compound 1 at 72 h, otherwise LD50 was >100 µg/mL for both compounds 1 and 2. These results indicate compounds 1 and 2 as novel silver complexes with interesting antimicrobial properties towards bacterial and fungal pathogens.

The calcium dependent Calpain proteases are modulatory enzymes with important roles in cell cycle control, development and immunity. In the fly model Drosophila melanogaster Calpain A cleaves Cactus/IkappaB and consequently modifies Toll signals during embryonic dorsal-ventral (DV) patterning. Here we explore the role of Calpains in the hemiptera Rhodnius prolixus, an intermediate germband insect where the Bone Morphogenetic Protein (BMP) instead of the Toll pathway plays a major role in DV patterning. Phylogenetic analysis of Calpains in species ranging from Isoptera to Diptera indicates an increase of Calpain sequences in the R. prolixus genome and other hemimetabolous species. One locus encoding each of the CalpC, CalpD and Calp7 families, and seven Calpain A/B loci are present in the R. prolixus genome. Several predicted R. prolixus Calpains display a unique architecture, such as loss of Calcium-binding EF-hand domains and loss of catalytic residues in the active site CysPc domain, yielding catalytically dead Calpains A/B. Knockdown for one of these inactive Calpains results in embryonic DV patterning defects, with expansion of ventral and lateral gene expression domains and consequent failure of germ band elongation. In conclusion, our results reveal that Calpains may exert a conserved function in insect DV patterning, despite the changing role of the Toll and BMP pathways in defining gene expression territories along the insect DV axis.

Acquired resistance to drugs that modulate specific protein functions, such as the human proteasome, presents a significant challenge in targeted therapies. This underscores the importance of devising new methodologies to predict drug binding and potential resistance due to specific protein mutations. In this work, we conducted an extensive computational analysis to ascertain the effects of selected mutations (Ala49Thr, Ala50Val, and Cys52Phe) within the active site of the human proteasome. Specifically, we sought to understand how these mutations might disrupt protein function either by altering protein stability or by impeding interactions with a clinical administered drug. Leveraging molecular dynamics simulations and molecular docking calculations, we assessed the effect of these mutations on protein stability and ligand affinity. Notably, our results indicate that the Cys52Phe mutation critically impacts protein-ligand binding, providing valuable insights into potential proteasome inhibitor resistance.

Selection of adjuvant to be combined with the antigen is an extremely important point for formulating effective vaccines. The aim of this study was to evaluate reactogenicity, levels of IgM, IgG and subclasses (IgG1, IgG2b and IgG3), and protection elicited by vaccine formulations with association of chitosan coated alginate or Montanide ISA 61 with γ-irradiated Brucella ovis. The alginate/chitosan biopolymers as well as the Montanide ISA 61 emulsion elicited intense and long-lasting local response, especially when associated with the antigen. However, Montanide ISA 61 induced less intense reactogenicity when compared to alginate/chitosan. Furthermore, γ-irradiated B. ovis with Montanide ISA 61 induced higher levels of IgG2b an important marker of cellular immune response. In conclusion, Montanide ISA 61 resulted in milder reactogenicity when compared to the alginate/chitosan, while it induced a high IgG2b/IgG1 ratio compatible with a Th1 profile response.

The maritime industry faces many pressing challenges due to increasing environmental and safety regulations and crew safety concerns [...]

As the impact of fossil fuels on the planet becomes clear, the world is increasingly focusing on renewable energy sources [...]

Tuberculosis (TB) continues to be a major global health challenge and a leading cause of death from infectious diseases. Inspired by the results from a previous work by our group on antimycobacterial N-alkylnitrobenzamides, which are structurally related to the nitrobenzamide family of decaprenylphosphoryl-β-d-ribose oxidase (DprE1) inhibitors, the present study explored a broad array of substituted benzamides. We particularly focused on previously unexplored 3,5-dinitrobenzamide derivatives. Starting with 3,5-dinitrobenzoic acid, we synthesized a diverse library of amides, incorporating both linear and cyclic amine moieties and also assessed the impact of terminal aromatic groups connected through ether, ester, or amide bonds on the bioactivity of the compounds. The synthesis primarily utilized nucleophilic addition/elimination, SN2, and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of linker. The most interesting compounds (c2, d1, and d2, MIC = 0.031 μg/mL) exhibited activities against Mycobacterium Tuberculosis (Mtb) H37Rv comparable to isoniazid. Complementary computational studies helped elucidate potential interactions with DprE1, enhancing our understanding of the molecular basis of their action. Our findings suggest that the most active compounds provide a promising foundation for the continued development of new antimycobacterial agents.

Despite the existence of several studies about the scapula’s position and motion, in shoulder pain conditions, there are still conflicting findings regarding scapular adaptations and reduced research about the scapula’s role during functional tasks. The present study aimed to compare scapular-related kinematic and electromyographic outcomes during different shoulder movements (with and without load) and the drinking task, between symptomatic and asymptomatic subjects. Forty subjects (divided into two groups) participated in this cross-sectional observational study. Scapulothoracic motion, scapulohumeral rhythm, and movement quality (considering trunk compensation, time-to-peak acceleration, and smoothness), as well as the relative surface electromyographic activity and muscle ratio considering the trapezius, serratus anterior, and levator scapulae (LS), were assessed. The symptomatic group presented the following: (1) changes in scapular upward rotation (p = 0.008) and winging (p = 0.026 and p = 0.005) during backward transport and drink phases; (2) increased muscle activity level of the middle trapezius (MT) in all tasks (p < 0.0001 to p = 0.039), of LS during shoulder elevation with load (p = 0.007), and of LS and LT during most of the drinking task phases (p = 0.007 to p = 0.043 and p < 0.0001 to p = 0.014, respectively); (3) a decreased serratus anterior lower portion activity level (SAlow) during shoulder lowering with load (p = 0.030) and drink phase (p = 0.047); and (4) an increased muscular ratio between scapular abductors/adductors (p = 0.005 to p = 0.036) and elevators/depressors (p = 0.008 to p = 0.028). Compared to asymptomatic subjects, subjects with chronic shoulder pain presented scapular upward rotation and winging adaptations; increased activity levels of MT, LT, and LS; decreased activity levels of SAlow; and increased scapular muscle ratios.

Plant-based milk alternatives are in the spotlight of novelty and Amazonian nut has a great potential for the preparation of these beverages. In the present study, extraction of Amazonian nut was carried out with water and creaming index was evaluated. Hydroethanolic annatto extract was subjected to spectrophotometric analysis in order to determine bixin content. Annatto nanodispersions were prepared through a low energy method involving stepwise addition of deionized water to organic phase. Dynamic light scattering analysis was performed for particle size distribution and encapsulation efficiency determined by ultracentrifugation. In the present paper, we prepared an Amazonian-nut milk alternative, being the prototype added of annatto nanodispersion. Sensory analysis with untrained panelists was performed. Nanosizing (diameter

In this paper, the oxidation behavior of silicon nitride with different contents of TiN was evaluated at 1400 oC for 64 hours in air. The oxidized samples were characterized by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy. Weight gain measurements have shown that the oxidation followed a multiple-law model with linear, parabolic, and logarithmic contributions. The samples presented high weight gain at the beginning of the process followed by the formation of an amorphous silica surface layer containing Y2Ti2O7 and rutile crystals. Cracks and holes were detected on the oxide layer. The oxidation resistance of the composites was strongly influenced by the initial content of TiN.

Although screen readers have made significant technological advancements, mathematics remains a challenging subject for people with visual disabilities. Due to its complex notations and abstract nature, mathematics presents difficulties in understanding through means other than visual. Consequently, reading mathematical content with screen readers poses challenges such as ambiguity, comprehension of long formulas, and identification of specific elements. Furthermore, even with reading difficulties, few screen readers support reading this type of content in Portuguese. This study presents an extension of a previous study which described the development and evaluation of an add-on for NVDA, which enables contextual exploration and navigation of mathematical formulas. The add-on, called Access8Math-NavMatBR, allows for internal exploration of formulas by providing contextual delineations of mathematical elements with support for the Brazilian variant of the Portuguese language. Based on the open-source Access8Math add-on, the new version was developed and evaluated in usability tests with six people with visual disabilities. Results showed that the new system improved understanding of formulas and provided better access to specific elements through formulas abstraction. The evaluation identified 52 issues, such as problems with commands and interaction approaches, verbalization by the screen reader, and platform structure. This extended version extends the analysis by presenting a teaching scenario in the context of numerical analysis and how the contextual exploration can be applied to aid in the understanding of complex elements. The paper presents design implications for systems for reading mathematical formulas in the Brazilian context and considerations for exploring patterns used by Brazilian users when reading and browsing mathematical formulas, dialoguing with the practical example presented.