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Engaged Living (values clarity and committed action) is a main process of psychological flexibility as defined by Acceptance and Commitment Therapy. The Engaged Living Scale (ELS) was designed to measure it. The purpose of this study was to translate the ELS to Spanish and to examine the reliability and validity of its scores in a heterogeneous sample of 752 Spanish pilgrims of the Way of Saint James (pre-post analysis: n = 285). Confirmatory factor analyses were computed to study the structural validity of the ELS scores. In addition, network analyses were computed to examine convergent and discriminant validity. The included variables were engaged living, mindfulness facets, satisfaction with life, subjective happiness, affect, depression, anxiety, and perceived stress. Results showed that the Spanish version of the ELS is two-factorial (valued living [VL] and life fulfillment [LF]). The ELS scores showed good reliability. In addition, it was able to detect VL and LF changes after the Way underscoring its sensitivity to change. The network analyses indicated adequate convergent and discriminant validity of the ELS. Changes in satisfaction with life, life fulfillment, happiness, and valued living scores were most strongly associated with changes in perceived stress, affect, mindfulness facets, depression, and anxiety. In short, the Spanish version of the ELS appeared to be a reliable and valid instrument to assess the engaged response style in the current samples. • As in previous studies, the correlated two-factor structure showed the best fit. • Network Analysis was used to investigate convergent and divergent validity. • Engaged living influenced distress through happiness and satisfaction with life. • Pilgrimage had a significant impact on engaged living. [ABSTRACT FROM AUTHOR]

Adequate measurement of the QT interval is of clinical importance in order to identify patients at higher risk for ventricular arrhythmias. Previous studies have described different methods to estimate baseline QT in patients with left bundle branch block (LBBB). However, the evidence regarding the assessment of the QT in patients with right bundle branch block (RBBB) is scarce. To analyze the feasibility and reliability of the different formulae described for LBBB in the estimation of the baseline QT in the presence of RBBB. We performed an observational study including patients who underwent electrophysiology study and/or ablation. Two types of RBBB were considered: 1) pacing-induced and 2) transient true RBBB. QRS, JT and QT intervals were measured during baseline and RBBB. Estimated QTc was calculated using LBBB formulae: Bogossian, Rautaharju, Tabatabaei, Tang-Rabkin, Yankelson, Wang. Linear correlation and intraclass correlation coefficients (ICC) were used to assess the reliability of these formulae for the estimation of baseline QTc. We finally included a total of 100 patients. Correlations between baseline and estimated QTc were strong (R > 0.7) for all the formulae except for Tabatabaei. Yankelson and Wang showed the highest reliability (ICC = 0.775 and 0.727, respectively). Yankelson appeared to be the most accurate formula, with a mean estimated QTc closest to baseline values. Previously described formulae for LBBB exhibited marked differences regarding reliability in the estimation of the QTc interval in the presence of RBBB. According to our results, Yankelson showed the most consistent and accurate agreement in this setting. [ABSTRACT FROM AUTHOR]

This article investigates the way in which Jacob Bernoulli proved the main mathematical theorem that undergirds his art of conjecturing—the theorem that founded, historically, the field of mathematical probability. It aims to contribute a perspective into the question of problem-solving methods in mathematics while also contributing to the comprehension of the historical development of mathematical probability. It argues that Bernoulli proved his theorem by a process of mathematical experimentation in which the central heuristic strategy was analogy. In this context, the analogy functioned as an experimental hypothesis. The article expounds, first, Bernoulli's reasoning for proving his theorem, describing it as a process of experimentation in which hypothesis-making is crucial. Next, it investigates the analogy between his reasoning and Archimedes' approximation of the value of π, by clarifying both Archimedes' own experimental approach to the said approximation and its heuristic influence on Bernoulli's problem-solving strategy. The discussion includes some general considerations about analogy as a heuristic technique to make experimental hypotheses in mathematics. [ABSTRACT FROM AUTHOR]

This study proposed an open-source myoelectric robotic hand orthosis prototype to support people with neuromuscular disorders in performing activities of daily living (ADLs). A user-tuned methodology was applied, designing the system's usability and ergonomics with recommendations in literature (2017 to 2020), thus calibrating the prototype by user's metrics. It has two modules: transmitter–interpreter system (TIS) and receiver–actuator system (RAS) that performs three hand pose: (i) pulp pinch, (ii) cylindrical grip, and (iii) resting hand. The system uses a linear discriminant analysis (LDA) classifier with real-time disruptive windowing (80 ms) and a majority vote algorithm (n=3) as post-processing. TIS classifies and transmits a hand pose within 300 ms to RAS, which executes the hand pose. The LDA classifier was trained with ten datasets of surface myoelectric signals (sMES) recorded from a healthy volunteer. The system's accuracy reached 90% in real-time tests with three everyday objects. Splints were 3D-printed with resistant material, so the fitting and range of motion were comfortable for the volunteer. The prototype achieved the recommendations in the literature, and it was the orthosis that most fulfilled said requirements compared to state-of-the-art (2017 to 2020) myoelectric robotic hand orthosis. However, it only assists with finger flexion. The open-source format provides other researchers a starting point to develop an orthosis for in-home rehabilitation that actively assists in ADLs. Additionally, production costs for the orthosis are R$856.35, or 2.98% of the cheapest myoelectric hand orthosis available on the market (PowerGrip), both quoted on November 2021. [Display omitted] • Myoelectric robotic hand orthosis developed following an user-tuned methodology. • Ergonomics and system usability are custom made from the user's metrics. • Open-source project with low manufacturing cost compared to commercial models. • Prototype can execute pulp pinch, cylindrical grip and a resting hand state. • Tested using three daily objects with different shapes and weights. [ABSTRACT FROM AUTHOR]

Processing surface electromyography (sEMG) data in real-time to control robotic devices in applications involving upper-limb prostheses is challenging, especially when the problem involves multi-class recognition. A typical processing pipeline in this kind of system presents the following steps: segmentation, feature extraction, and classification. An under-exploited issue is the segmentation step, usually a windowing technique whose parameters are mostly heuristically defined. In this context, this work examines some segmentation parameters and how it affects the accuracy in the classification of hand gestures using a commercial sEMG wearable device. The main contribution of the work is to point out recommendations and insights about the segmentation step. Our findings show that for most feature sets and classifiers, there is no significant difference in using window lengths over 500 ms; however, for some cases, this value can be smaller without depreciating the accuracy. Moreover, there is no significant difference in using the truncated signal, which means using the first half of the signal in relation to the whole signal; no gesture is privileged in relation to the others due to the change in the segmentation parameters; data augmentation caused by changes on segmentation could affect the classification error; and the best performance was observed using TD9 feature set, SVMR classifier with an overlap fraction of 25%. [Display omitted] • Feature sets and classifiers can be less sensitive for segmentation parameters. • Overlap fraction exert high influence, more overlapping, less was the error. • Signals with only the sEMG transitory provide same response than whole signal. • Segmentation does not privilege classes in the pattern recognition process. • The data augmentation caused by the segmentation parameters is relevant. [ABSTRACT FROM AUTHOR]

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2. [Display omitted] • This study focuses on the design of a multiepitope peptide vaccine against SARS-CoV-2 and its proteins (S, M, N, and E). • 18 epitopes with high anti/immunogenicity, conservation, non-allergenicity, non-toxicity and excellent population coverage. • Docking and QM:MM optimization simulations with the TLR-3 receptor confirmed the stability of the constructed vaccine. [ABSTRACT FROM AUTHOR]

Mindfulness and self-compassion are emerging as crucial constructs in mental health research. Recent studies have shown that both mindfulness and self-compassion skills may play important roles in well-being and positive emotions associated with mindfulness training. Studies are needed to explain this relationship and to determine what facets may be correlating and mediating the meditation–happiness relationship. The aim of this study was to explore the meditation–happiness relationship and examine which mindfulness and self-compassion facets are better predictors of happiness. A total of 365 participants completed an assessment protocol composed of: the Five Facets of Mindfulness Questionnaire (FFMQ), the Self-Compassion Scale-short form (SCS-SF), and the Pemberton Happiness Index (PHI). Hierarchical regression analysis showed that two FFMQ facets ( Observing and Awareness ) and two SCS components ( Self-kindness and Common humanity ) were significant predictors of happiness. Mediation results revealed a significant total indirect effect of Observing , Awareness , Self-kindness and Common humanity in the meditation frequency–happiness relationship. Significant indirect effects were found for observing , self-kindness and common humanity . The results supported the model of mindfulness and self-compassion facets as partial mediators of the meditation–happiness relationship. Findings are in line with other studies and provide evidence about the influence of mindfulness and self-compassion on happiness. [ABSTRACT FROM AUTHOR]

Current emotion recognition computational techniques have been successful on associating the emotional changes with the EEG signals, and so they can be identified and classified from EEG signals if appropriate stimuli are applied. However, automatic recognition is usually restricted to a small number of emotions classes mainly due to signal’s features and noise, EEG constraints and subject-dependent issues. In order to address these issues, in this paper a novel feature-based emotion recognition model is proposed for EEG-based Brain–Computer Interfaces. Unlike other approaches, our method explores a wider set of emotion types and incorporates additional features which are relevant for signal pre-processing and recognition classification tasks, based on a dimensional model of emotions: Valence and Arousal . It aims to improve the accuracy of the emotion classification task by combining mutual information based feature selection methods and kernel classifiers. Experiments using our approach for emotion classification which combines efficient feature selection methods and efficient kernel-based classifiers on standard EEG datasets show the promise of the approach when compared with state-of-the-art computational methods. [ABSTRACT FROM AUTHOR]

• This manuscript evaluated of 289 military volunteers, in three body regions: temple, forehead and wrist, in Caucasians, Blacks and Half-Black volunteers, using an Infrared Thermometer • It was not found significant changes due to the variation of skin tones, height or weight • The results show different median temperatures in the referred anatomical region, 37.2°C in the temple, 36.8°C in the forehead, and 36.4°C in the wrist. • As opposite of what is common worldwide, the temperature should be measured in the temple to get access to the external carotid artery. Non-contact infrared sensors are widely used as a diagnostic tool for elevated body temperature during initial screening for coronaviruses. The aim of this study was to investigate the thermal differences at three anatomical points: temple, forehead, and wrist, in the initial screening for temperature indicative of febrile and non-febrile states in skin pigmentation variations in Black, Half-Black and Caucasian skins, correlated with height and weight variables. Temperatures were obtained by means of an infrared thermometer in 289 volunteers with mean age of 18.30 ± 0.76, in a controlled environment according to Singapore Standard, SS582 part 1 and 2, normative standard IEC 80601-2-59, with standard technical protocols established by the International Organization for Standardization, ISO / TR 13154. The data were processed in MATLAB® R2021a, and data normality verified by Kolmogorov-Smirnov test, non-parametric data paired between temple / forehead / wrist were compared using the Wilcoxon signed-rank test. The results show different median temperatures in these anatomical regions, 37.2°C at the temple, 36.8°C at the forehead and 36.4°C at the wrist. As the temple region presents a temperature higher than the other investigated regions and, therefore, close to the core temperature, it should be considered for the initial screening of SARS-CoV-2 when using non-contact infrared thermometers. Furthermore, no significant changes were found due to variation in skin tone, height, or weight. [ABSTRACT FROM AUTHOR]

• Chew work reduces towards the point of swallowing. • The trigger for swallowing is not low levels of stickiness. We investigated muscle activity during oral processing of sticky model foods. Chewing Time extracted from the EMG data distinguished the most sticky and least sticky model foods from the others, but was not a good discriminator between the other models. Mean chew work declined by 25.4%, while the median frequency shift (which is related to muscle fatigue) increased by 54.9% during oral processing for all the model foods, with the effect being greatest for the stickiest foods. We conclude that the degree of stickiness is not a trigger for swallowing and changes in the other bolus properties, such as softness, may influence muscle activity to a level at which we can swallow. [ABSTRACT FROM AUTHOR]

Recognizing learning styles is important to maximizing learning outcomes and many instruments are available to investigate learning styles. To investigate instruments with evidence of validity and reliability most commonly used to evaluate undergraduate healthcare student learning styles globally. This scoping review of literature was guided by The Joanna Briggs Institute's recommendations for conducting scoping reviews and the PRISMA-ScR (extension for scoping reviews). The protocol is available for access. Databases searched included Cumulative Index to Nursing and Allied Health Literature, PubMed, Web of Science, and Scopus. Inclusion criteria were: fully accessible; written in English, Portuguese, or Spanish; and used reliable and/or validated instruments to describe healthcare student learning styles. Articles were excluded if the sample included healthcare professionals, there was no report of the instrument validity and reliability, or was not fully accessible. Data were extracted from each article and entered into Microsoft Office Excel documents for analysis. Forty-seven articles were selected for full review, including cross-sectional, interventional, and longitudinal studies. Eleven instruments were identified with evidence of reliability and validity for assessing undergraduate healthcare student learning styles globally. The most frequently used instruments were Visual, Aural, Read-Write, and Kinesthetic; Kolb's Learning Styles Inventory; and the Honey-Alonso Questionnaire. Most instruments were developed based on a theoretical framework and/or model. This scoping review adds to the literature an overview of available instruments which measure healthcare student learning styles with evidence of both reliability and validity. The results indicate the need for further studies to improve learning style instruments for use in intervention studies aimed at improving the teaching-learning process for healthcare students. [ABSTRACT FROM AUTHOR]

• Brain computer interface implementation since activation to shut off. • Register of neuromuscular fatigue in paralyzed muscle through mechanomyography sensor. • Connection among open source softwares to close the loop. • Low cost to create a brain computer interface system and implementation. People with spinal cord injury (SCI) may have their paralyzed muscles activated through functional electrical stimulation (FES). This neuromodulation technique has been used frequently to assist in controlling the movement of neuroprostheses. Electroencephalography (EEG) is able to trigger FES from the motor imagery captured through movements intentions. This research presents an isometric neuromuscular control system of the quadriceps muscle activated by EEG. Additionally, the detection of neuromuscular fatigue through the mechanomyography (MMG) technique is proposed, which is used to shut-off the system. A pilot study was performed on a chronic 42-year-old paraplegic (no voluntary contraction below the spinal cord injury level T8) volunteer. To do so, the training procedure for EEG signals was divided into the calibration and feedback phases. In the first one, four EEG channels and the Linear Discriminant Analysis (LDA) classifier were used to classify between motor imagery of the right leg and remain at rest. The maximum accuracy obtained during this stage was 77%. In the feedback phase, the volunteer was able to activate FES through brain–computer interface (BCI) in two tests (defined as Test 1 and Test 2) with the same procedure in different days. The closed-loop force control was tested with the setpoint of 2 kgf and 2.5 kgf and proved to be stable on both tests, successfully turning off the FES using the fatigue threshold from the MMG signal, being the main contribution of this work. [ABSTRACT FROM AUTHOR]

In vitro – in vivo correlation (IVIVC) allows prediction of the in vivo performance of a pharmaceutical product based on its in vitro drug release profiles and can be used to optimize formulations, set dissolution limits, reduce the number of bioequivalence studies during product development, and facilitate certain regulatory decisions. This review article aimed to assess papers published in the last two decades regarding the use of the IVIVC in the development of oral formulations, to demonstrate the scenario in this area, as well as to describe the main characteristics of the assessed studies. A systematic search of PubMed and Web of Science databases was conducted to retrieve articles reporting the use of the IVIVC in the oral formulation development in the period from 1998 to 2018. The qualified studies were abstracted regarding drug name, dosage form, BCS class, in vitro and in vivo data, level of IVIVC, number of formulations, presence of the validation and predictability. The discussion was supported by these data, which allowed to address broadly strengths and weaknesses in this area. Moreover, a large database has been described in this article containing different IVIVC models, with different substances, providing support to scientists interested in this area. [ABSTRACT FROM AUTHOR]

In this paper, a novel dual-fuel, dual-swirl burner is presented and its potential to mitigate thermoacoustic coupling for ammonia-hydrogen-air flames is explored. The key feature of this burner is that the extent of mixing between ammonia and hydrogen before injection into the combustion chamber can be tuned by recessing an inner dividing tube. Non-reacting, 1-D Raman measurements confirm that recessing the dividing tube changes the radial profile of fuel composition at the injector's outlet. Time-averaged flame imaging shows that this modifies, in turn, the flame morphology. Specifically, the more stratified is the fuel, the least compact is the flame. In the most stratified case, a "blue" flame, predominantly burning hydrogen, pilots another "orange" flame, predominantly burning ammonia, further downstream. Acoustic measurements show that the least stratified (most compact) flame exhibits intrinsic thermoacoustic modes (ITA), while these modes are not featured for the most stratified (least compact) flame. Consequently, this study demonstrates that the thermoacoustic behavior of this carbon-free burner can be altered by tailoring the injection of ammonia and hydrogen while keeping the thermal power (7.4 kW), global equivalence ratio (0.64), and fuel flow rates strictly constant. This lays the foundation for the development of future practical burners in which the extent of mixing between ammonia and hydrogen upstream of the flame would be actively controlled to mitigate thermoacoustic coupling. [ABSTRACT FROM AUTHOR]

Background: Little is known about changes of mental health during the COVID-19 pandemic in potentially disadvantaged groups. We investigated changes in anxiety and depression symptoms during the first year of the pandemic in six European countries and Australia by prior mental disorders and migration status.Methods: Overall, 4674 adults answered a web-based survey in May-June 2020 and were followed by three repeated surveys up to February 2021. Information on psychosocial, financial and demographic, living conditions, prior mental disorders, depression and anxiety symptoms during the pandemic and migration status was collected. Weighted general estimation equations modelling was used to investigate the association between prior mental disorders, migration status, and symptoms over time.Results: Most participants were <40 years old (48%), women (78%) and highly educated (62%). The baseline prevalence of depressive and anxiety symptoms ranged between 19%-45% and 13%-35%, respectively. In most countries, prevalence rates remained unchanged throughout the pandemic and were higher among people with prior mental disorders than without even after adjustment for several factors. We observed interactions between previous mental disorders and symptoms of anxiety or depression over time in two countries. No difference by migration status was noted.Limitations: Convenience sampling limits generalizability. Self-assessed symptoms of depression and anxiety might involve some misclassification.Conclusions: Depression and anxiety symptoms were worse among individuals with prior mental disorders than without, but there was no clear trend of worsening mental health in the observed groups during the observed period. [ABSTRACT FROM AUTHOR]

Nowadays, EGR systems are being incorporated in the research focused on spark-ignition direct-injection engines as a solution to the problems presented by them; i.e. knock risk and high combustion temperature which produces high NOx emission. Since the major part of the investigations are centered on engine performance or engine simulation aside pollutants emission and aftertreatment evaluation, this paper focuses on these topics: gaseous and particle emission analysis and aftertreatment efficiency evaluation when cooled LP-EGR system is applied to a GTDi engine. This work has been performed in a 4-cylinder, turbocharged, direct-injection gasoline engine with 2.0 L displacement. The equipment used in this study are TSI-EEPS for particle measurement and HORIBA MEXA 1230-PM for soot measurement being HORIBA MEXA 7100-DEGR with a heated line selector the system employed for regulated gaseous emission measurement and aftertreatment evaluation. A reduction around 50% of NOx with an increase of HC and CO emissions was found in medium-load operating points. At full-load conditions, the suppression of fuel enrichment including EGR leads in a drastically reduction in CO maintaining similar HC and NOx emissions. Furthermore, PN and soot emissions also decrease as EGR is included and spark timing advanced in all the tested conditions. [ABSTRACT FROM AUTHOR]

The pressure drop across DPFs directly affects the exhaust back-pressure and fuel economy of compression ignition engines. Pressure drop is related to the soot trapped inside the DPF, increasing exhaust back-pressure as the soot mass loading does. Consequently, regeneration strategies are required to remove the soot collected in the DPF. However, these processes usually involve additional fuel consumption. Considering this context, control techniques to reduce the exhaust back-pressure dependence on DPF soot loading are arising. One technique is based on the pre-DPF water injection events to get an optimum redistribution of the soot layer leading to a reduction of DPF pressure drop. This paper is focused to establish a comprehensive analysis of the change in pollutants emitted due to this technique application. The effects of this technique on filtration efficiency and particle size distribution are also analysed during and after a DPF loading test. Results have shown a dilution effect on gaseous compounds and a negligible particle emission during the pre-DPF water injection event (<2 mg), increasing PSD mode downstream the DPF to the mode of the raw emission. Nevertheless, there are not relevant effects on overall filtration efficiency, which keeps value comparable to baseline operation clearly higher than 99%. [ABSTRACT FROM AUTHOR]

In this study, an experimental investigation of particle size distribution emission over performance of transient conditions in a high speed diesel engine fuelled with diesel, biodiesel and Fischer Tropsch fuels have been assessed. Six fuels with different properties have been tested in a 4-cylinder light-duty diesel engine typically used for European passenger cars. The cycle used in this study was the New European Driving Cycle (NEDC) and each test was carried out after a stabilization warming period in order to avoid cold start effects. A comparative analysis between nucleation and accumulation particle mode concentration, particle size distributions and a geometric mean diameter calculation are presented in this paper. In this sense, a reduction in the range of particle diameter emitted and a decrease in accumulation particle mode concentration with Fischer Tropsch fuel during the EUDC were found. In contrast, all biofuels used show an increase of particle number concentration in nucleation-mode during the urban cycles (ECE-15) related to combustion damage at low load conditions. Finally, an increase in the sulfur content diesel fuel leads to an increase in the geometric mean diameter of particle size distribution related to the increase in accumulation particle concentration during the entire cycle. [ABSTRACT FROM AUTHOR]

Abstract: Diesel particulate filters are a standard technology used in diesel engines in order to comply with actual and forthcoming regulations, regarding soot emissions and particulate matter in exhaust gases. In recent years, pre-turbo aftertreatment response has been investigated as opposed to the traditional aftertreatment location downstream from the turbine but just regarding engine performance. Previous studies do not deal in detail with gaseous and particle emission analysis in a pre-turbo aftertreatment configuration. This paper focuses on these topics. The gaseous and particle emissions have been assessed in a 4-cylinder, light-duty diesel EURO 4 engine typically used in European passenger car vehicles. Different steady-state operating points have been considered in order to extend the study over a wide range of operating conditions. Additionally, the New European Driving Cycle has been performed with the aim of reaching a comprehensive understanding of the aftertreatment dynamic response in terms of pollutant emissions. An increase in the amount of NO2 converted from NO and a reduction in emitted CO have been found at low load steady-state operating conditions with pre-turbo aftertreatment placement. In driving cycle conditions, a shift from nucleation to accumulation mode particles have been found, being the filtration efficiency scarcely affected. [Copyright &y& Elsevier]

The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6 K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions. • The study is focused on design of a multi-epitope peptide vaccine against Mayaro. • The vaccine prototype is composed of immunodominant regions of Mayaro structural proteins (capsid, E1, E2, E3, and 6K). • The design is based on stitching together 4 CTL and 25 HTL epitopes with high immunogenicity and excellent population coverage. [ABSTRACT FROM AUTHOR]