Federal University of Santa Catarina
  • Florianópolis, Santa Catarina, Brazil
Recent publications
This chapter describes the analysis of rectifier circuits valid for ultra-low-voltage (ULV) operation. Expressions for the output voltage, power conversion efficiency, and input resistance are presented for the Dickson charge pump and for the voltage multiplier. The expressions are derived for both square-wave and sine-wave signals and are expressed as a function of the diode parameters and the load current.
This chapter presents the design, implementation, and measurements of a DC-DC voltage converter for ultra-low-voltage energy-harvesting applications. The converter architecture is comprised of a cold starter, a high-efficiency inductive boost converter, and a control circuit. The cold starter, based on an ultra-low-voltage oscillator and a charge pump, provides the circuit startup for input voltages of down to 11 mV. The inductive boost converter was designed to achieve high-efficiency through the adoption of a nonlinear zero-current-switching scheme that minimizes the synchronization losses. The prototype provides steady-state operation for input voltages in the range of 7.3–140 mV with end-to-end efficiencies higher than 50% for input voltages above 10.5 mV and peak end-to-end efficiency of 85% at 140 mV.
The circumcentered-reflection method (CRM) has been applied for solving convex feasibility problems. CRM iterates by computing a circumcenter upon a composition of reflections with respect to convex sets. Since reflections are based on exact projections, their computation might be costly. In this regard, we introduce the circumcentered approximate-reflection method (CARM), whose reflections rely on outer-approximate projections. The appeal of CARM is that, in rather general situations, the approximate projections we employ are available under low computational cost. We derive convergence of CARM and linear convergence under an error bound condition. We also present successful theoretical and numerical comparisons of CARM to the original CRM, to the classical method of alternating projections (MAP), and to a correspondent outer-approximate version of MAP, referred to as MAAP. Along with our results and numerical experiments, we present a couple of illustrative examples.
Background The implementation of the Sustainable Development Goals (SDGs) requires much planning and the provision of resources, especially regarding the necessary investments, technologies and infrastructures needed. Yet, it is presently unclear how available these elements are, what gaps exist, what changes have taken place in terms of their availability since the adoption of the SDGs and what their requirements will be in the future. The knowledge gap has become even more concerning because of the impact of the COVID-19 pandemic. Using a bibliometric analysis, an assessment of the global progress of SDG implementation and requirements, identifying challenges through the development of a matrix, and a set of 11 case studies to triangulate the holistic analysis, an assessment of the global progress of the SDGs implementation and the impact of the COVID-19 pandemic on this process was carried out. Results The findings suggest that the scope and width of resources limitation are currently undermining the implementation of the SDGs. Apart from the fact that the pace of progress has been insufficient, the potential of the SDGs in pursuing sustainability and improving life quality is not fully realised. This trend suggests that a substantial acceleration of the efforts is needed, especially for the five SDGs whose progress since 2015 has not been optimal, namely SDG2, SDG11, SDG13, SDG15, and SDG16, while SDG3, SDG7, SDG9, SDG14, and SDG17 show signs of progress. The case studies showed that different industries have dissimilar effects on achieving the SDGs, with the food sector correlating with 15 SDGs, as opposed to the energy sector correlating with 6 SDGs. Accordingly, the priority level assessment in terms of achieving the SDGs, points to the need to further advance the above-mentioned five SDGs, i.e., 2, 11, 13, 15 and 16. Conclusions This study fills in a knowledge gap in respect of the current need for and availability of investments, new technologies, and infrastructures to allow countries to pursue the SDGs. It is suggested that this availability is rather limited in specific contexts. In respect of the needs to be addressed, these include resource-related constraints, limited technologies and infrastructures, affecting SDG2, SDG11, SDG13, SDG15, and SDG16, whose progress needs to be enhanced. Since the global progress in the process of implementation of the SDGs depends directly and indirectly on addressing the resource gaps, it is suggested that this topic be further investigated, so that the present imbalances in the three dimensions of sustainable development: the economic, social and environmental, be adequately addressed.
Introduction The consumption of yerba mate (YM), a source of antioxidants, in a fasted state increases fatty acid oxidation (FAT ox ) during low–moderate-intensity exercise and improves performance in high-intensity exercise. However, the impact of a pre-exercise carbohydrate (CHO) meal on YM effects during exercise is unknown. Objective We investigated the effects of yerba mate drink (YMD) consumed in the fasted state (YMD-F) or after a CHO meal (YMD-CHO) on measurements of metabolism, performance, and blood oxidative stress markers in cycling exercise. Methods In a randomized, repeated-measures, crossover design, eight trained male cyclists ingested (i) YMD-CHO, (ii) YMD-F, or (iii) control-water and CHO meal (Control-CHO). The YMD (an infusion of 5 g of ultrarefined leaves in 250 mL of water) was taken for 7 days and 40 min before exercise. CHO meal (1 g/kg body mass) was consumed 60 min before exercise. The cycling protocol included a 40-min low-intensity (~ 53% V̇ O 2peak ) constant load test (CLT); a 20-min time trial (TT); and 4 × 10-s all-out sprints. Blood samples and respiratory gases were collected before, during, and/or after tests. Results During CLT, YMD-CHO increased FAT ox ~ 13% vs . YMD-F ( P = 0.041) and ~ 27% vs . Control-CHO ( P < 0.001). During TT, YMD-CHO increased FAT ox ~ 160% vs . YMD-F ( P < 0.001) and ~ 150% vs . Control-CHO ( P < 0.001). Power output during TT improved ~ 3% ( P = 0.022) in YMD-CHO vs . Control-CHO and was strongly correlated with changes in serum total antioxidant capacity ( r = −0.87) and oxidative stress index ( r = 0.76) at post-exercise in YMD-CHO. Performance in sprints was not affected by YMD. Conclusion CHO intake did not negate the effect of YMD on FAT ox or TT performance. Instead, a synergism between the two dietary strategies may be present. Clinical Trial Registration NCT04642144. November 18, 2020. Retrospectively registered.
This study aims to compare the grain protein profile of four Brazilian cowpea cultivars ( BRS Aracê, BRS Itaim, BRS Pajeú, and BRS Xiquexique) by two-dimensional electrophoresis (2-DE) and principal component analysis (PCA). 2-DE efficiently separate cowpea protein profiles, showing high homogeneity among the four cultivars. In addition, the principal component analysis indicated that there is a difference in abundance of proteins among the cultivars. The cultivars BRS Aracê and BRS Xiquexique, both biofortified in iron and zinc, were separated from the cultivars BRS Itaim and BRS Pajeú. These results demonstrate that protein profiles can be used to discriminate cowpea varieties. Graphical Abstract
Background The production of monoclonal antibodies for immunoglobulin detection is not cost-effective, while polyclonal antibody production depends on laboratory animals, raising concerns on animal welfare. The widespread use of immunoglobulins in the pharmaceutical industry and the increasing number and variety of new antibodies entering the market require new detection and purification strategies. The Tripartite motif-containing protein 21 is a soluble intracellular immunoglobulin G receptor that binds to the constant region of immunoglobulin G from various species with high affinity. We hypothesized that using this protein as an antibody-binding module to create immunoglobulin detection probes will improve the portfolio of antibody affinity ligands for diagnostic or therapeutic purposes. Results We created a chimeric protein containing a mutated form of the C-terminal domain of mouse Tripartite motif-containing protein 21 linked to streptavidin to detect immunoglobulin G from various species of mammals. The protein is produced by heterologous expression and consists of an improved molecular tool, expanding the portfolio of antibody-affinity ligands for immunoassays. We also demonstrate that this affinity ligand may be used for purification purposes since imidazole elution of antibodies can be achieved instead of acidic elution conditions of current antibody purification methods. Conclusion Data reported here provides an additional and superior alternative to the use of secondary antibodies, expanding the portfolio of antibodies affinity ligands for detection and purification purposes.
The control of single-phase Grid connected inverters by Vector Current Control Direct Quadrature (VCC DQ) method is a well-known technique. However, the presence of a Phase-Locked Loop (PLL) affects the dynamic response of the system. This paper proposes a PLL-less Vector Control (PLVC) method in which a single-phase Grid connected inverter is controlled without any PLL. Hence it reduces the complexity and computational burden during implementation on the Digital Signal Processor (DSP) controller as well as the natural coupling of PLL and current controller. The mathematical modeling and controller design for the PLVC method is described. A 5 kW single-phase Grid connected inverter simulation model and a 150 W hardware prototype with TI F28379D processor are developed and tested under steady-state at rated power condition and dynamic conditions like instant variation in the reference powers. Also, the robustness of the controller is tested under adverse conditions voltage sag, swell at the instant of distinct phase angles and frequency deviation also.
This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks.
The characteristic impedance of structures is an important parameter used in the development of overvoltage protection studies and in the insulation coordination in electrical systems. The transmission line towers shapes and the poles shapes make it difficult to calculate the characteristic impedance analytically, or even measuring in laboratory. Thus, this paper presents a methodology to calculate the characteristic impedance of concrete poles in distribution networks and transmission line towers. A model was developed in Q3D Extractor software to run these simulations. A comparison between simulations and an analytical method is made, considering two types of structures, a distribution pole, and a transmission tower. The results show divergences between the calculated values by the various analytical methods and those obtained in this work. At the end, it is concluded that the determination of the characteristic impedance using the proposed methodology is more accurate due to the degree of structure details considered.
The plate and shell heat exchanger (PSHE) was developed to overcome the traditional gasketed plate heat exchangers (PHE) operation limits. Its constructive characteristics allow higher-pressure and thermal applications, suitable for processes found in power plants and the oil and gas industry. However, studies on the PSHE thermo-hydraulic performance are still scarce. This study presents an experimental and theoretical analysis of the flow and heat transfer characteristics of a PSHE. A test rig operates with water and viscous oil to produce turbulent and laminar flow regimes, typical of the oil and gas industry. The heat transfer rate, pressure drop, and flow distribution are measured. The m²-model, developed to predict flow maldistribution on the PHE, is suitable for the plate side of the PSHE. An analytical model is used to correct the effects of maldistribution on the overall heat transfer coefficient and provide Nusselt number correlations. Experiments show that the flow maldistribution increases the heat exchanger pressure drop and deteriorates the heat transfer performance. The maximum and average channel flow rate ratio reaches 2.30 on the shell side and 1.75 on the plate side. Friction factor correlations are created based on the channel pressure drop data. The shell side has an inferior overall performance than the plate side, with a higher maldistribution and a lower Nusselt number. The PSHE effectiveness deterioration due to the maldistribution is 4% in the worst scenario within the experimental range. Results indicate that the PHE thermo-hydraulic performance is superior to the PSHE. Nevertheless, the structural advantages of the PSHE make it appropriate for applications involving high pressures and elevated temperatures.
Asbestos has been used by automobile, construction, manufacturing, power, and chemical industries for many years due to its particular properties, i.e. high tensile strength, non-flammable, thermal and electrical resistance and stability, and chemical resistance. However, such a mineral causes harmful effects to human health, including different types of cancer (e.g., mesothelioma). As a result, the use of asbestos has been banned since the 1980s in many countries. Nonetheless, asbestos is still part of the daily life of the population as asbestos-containing materials (ACMs) are still present in many buildings constructed and renovated before the 1990s. This work aims to present a current literature review about asbestos. The literature review was composed mainly of research articles published in international journals from the medical and engineering disciplines to provide an overview of asbestos use effects reported in interdisciplinary areas. The literature review comprised asbestos characteristics and its relationship to the risks of human exposure, countries where asbestos use is permitted or banned, reducing asbestos in the built environment, and environmental impact due to use and disposal of asbestos. The main findings were that ACMs are still responsible for severe human diseases, particularly in areas where there is a lack of coordinated asbestos management plans, reduced awareness about asbestos health risks, or even a delay in the implementation of asbestos-ban. Such issues may be more prevailing in developing countries. The current research in many countries contemplates several methodologies and techniques to process ACMs into inert and recyclable materials. The identification and coordinated management of ACM hazardous waste is a significant challenge to be faced by countries, and its inadequate disposal causes severe risk of exposure to asbestos fibres. Based on this work, it was concluded that banning asbestos is indicated in all countries in the world.
Melanoma is one of the most common recurrent malignancies in humans.A new Laponite® (LAP) gel containing the drug simvastatin (SIM), targeting topical treatment of melanoma, was developed, and evaluated using different techniques. First, a preformulation study was carried out, where the impact of LAP concentrations, gelation time and temperature on the gel's apparent viscosity were evaluated. The effect of chemical enhancers of permeation, isopropyl myristate (MYR) and squalene (SQ), on the gel's apparent viscosity was also assessed at this point. Based on the results obtained in preformulation, three optimized gels were proposed to incorporate the drug, named GS, GMS, and GSS. The gels were evaluated by SIM content, polarized light microscopy (PLM) and ex vivo permeation studies. The results obtained demonstrated a good drug loaded for all gels, GS (98.70 ± 0.69%), GMS (100.74 ± 5.68%), and GSS (97.46 ± 7.45%). The PLM showed the formation of tactoid structures for the samples containing the permeation enhancers MYR and SQ in the presence of SIM. The amount of drug permeated through the human skin (epidermis+dermis) after 24 h for each tested formulation was lower than 0.01% of total initial amount, suggesting a topical action of SIM. The stability studies performed for the final proposed formulation (GS) suggested a good stability for the evaluated parameters, SIM content, pH, apparent viscosity and for the count of viable microorganisms. The antibacterial and melanoma antitumoral activities for SIM were experimentally confirmed. LAP showed to be a good carrier for pharmaceutical formulations containing SIM, and it is a promising material for the development of products that aim to treat melanoma topically.
The Navier–Stokes–Voigt model that governs flows with non-constant density of incompressible fluids with elastic properties is considered in the whole space domain Rd and in the entire time interval. If d∈{2,3,4}, we prove the existence of weak solutions (velocity, density and pressure) to the associated Cauchy problem. We also analyse some issues of regularity of the weak solutions to the considered problem and the large time behavior in special unbounded domains.
In this paper, a practical nonlinear model predictive control with iterative nonlinear prediction and linearization is proposed, considering a long short-term memory (LSTM) artificial neural network (PNMPCi-LSTM) as process model for making the predictions. The prediction model is divided into two portions, the base output prediction, obtained with the LSTM nonlinear model, and the incremental output prediction, obtained using a linearized version of the LSTM model. The base response and the dynamic matrix of the system, which is obtained using the linearized version, are used to find an optimal control effort by solving a quadratic programming problem. This procedure is performed iteratively by updating the base input with the candidate control effort until the incremental response term is small enough compared with the base response term. The advantages of the proposed method in terms of performance and computing times are illustrated using the control of a simulated nonlinear neutralization reactor. For the evaluated case study, the results show that by using the proposed iterative procedure the closed-loop performance measured using the integral absolute error is improved by 8% for a setpoint tracking scenario while keeping the computation times within reasonable levels. In addition, the results support the idea that the proposed PNMPCi-LSTM is an alternative to implement a nonlinear MPC with reasonable computation times.
Coffee consumption continues to grow all over the world and in 2019 the equivalent of 167.90 million 60-kg bags were consumed worldwide, with Brazil being the largest producer and exporter and the second largest consumer of the beverage. The amount of coffee by-products generated is extremely high, being mainly composed of immature/defective coffee, coffee husks, silver skin and spend coffee grounds (SCG). Studies indicate that SCG oil contains high concentrations of polyunsaturated fatty acids, primarily linoleic and palmitic acids, which have excellent skin emollient and moisturizing properties. This paper reports an analysis of the degree of toxicity, collagen synthesis and the potential for proliferation and cell migration of SCG oil after passing through a pre-extraction process with innovative non-thermal plasma (NTP) technology. It was found that coffee oil subjected to NTP has low toxicity and great potential for cell proliferation and migration compared to oil extracted without NTP treatment. This will be of great interest to the pharmaceutical and cosmetic industries, adding value to a waste product available in large quantities in association with the use of a clean technology (non-thermal plasma).
Two low-value agro-industrial residues, passion fruit peel waste (PF) and pineapple peel waste (PA), were considered in this study as feedstocks to produce solid biofuels by torrefaction. The experiments were conducted in a macro-TGA with GC-TCD/FID analysis to investigate their torrefaction characteristics. The GC-TCD/FID analysis allowed quantifying the non-condensable gases, including CO, CO2, CH4 and H2. The impacts of pretreatment with torrefaction on the physicochemical properties were investigated by using proximate analysis, ultimate analysis, and calorific values. The torrefaction of PF and PA was investigated at three different temperatures (200, 250, and 300 °C) and two residence times (15 and 60 min). The torrefaction pre-treatment led to higher levels of elemental carbon, fixed carbon, HHV and energy density than in the raw biomass. Experimental results showed that the most favorable torrefaction condition for producing a solid biofuel with a high energy density is a moderate temperature of 250 °C and 15 min of residence time. Two models were applied to the torrefaction kinetics of the two agro-industrial wastes: one with the one-step method and the other with the two-step method. The two-step reaction method was the most appropriate for describing the torrefaction behavior of the two agro-industrial wastes in all conditions studied. As determined by the two-step reaction method, the torrefaction activation energies ranged from 17.9–199.9 kJ mol−1 for PF and 5.3–84.0 kJ mol−1 for PA. Findings from this study are potentially valuable for the design of large-scale equipment for the torrefaction of PF and PA residues.
Purpose of Review Graphene is introduced in dentistry as a material to be used in the fabrication or coating of dental implants due to its biocompatibility, ability to physically interact with biomolecules and very high surface area. This review highlights the current knowledge on the general properties of graphene, potential benefits especially when used in zirconia-based implants, as composite materials and coatings. Recent Findings The literature reviewed showed a growing body of evidence supporting the use of graphene-based material, associated with titanium or zirconia as a coating or composite material that helps in cell viability, differentiation and proliferation, improving the bioactivity, osseointegration, physical, chemical and mechanical properties particularly zirconia. Graphene-based materials present great potential for biomedical applications especially when used in the form of nanostructured biological coatings that can be obtained through reproducible and economical processes. Summary The use of graphene as a composite implant material or coating may have great potential for osseointegration and bone regeneration, providing that, features including hydrophilicity, protein adsorption capacity, oxygen content and effect of external parameters such as temperature, pH and ionic strength need further elucidations before they can be implemented as a coating or composite material for dental implants.
With the advance of Wide-Area Measurement Systems (WAMS), power system operators have direct access to a large amount of data with valuable information about the power system dynamic performance. As a result, there is a clear need for new data-driven methodologies capable of extracting relevant information from this collected data. One of the key challenges is correctly detecting power system disturbances to avoid false alarms during real-time operation as well as off-line disturbance analysis. This paper proposes a two-level robust event detection methodology aiming to reduce false disturbance detection (false positives/alarms) and validate true events. The methodology is divided into two-levels:(i) signal processing analysis (ii) deep neural network (DNN) classification. In the first level, we apply a widely used spectral analysis based on the Discrete Wavelet Transform (DWT) to event detection. In the second level, the events detected by the DWT are processed by a DNN to check if they are real events or false alarms. Finally, the proposed methodology is evaluated using real synchrophasor event records from the Brazilian Interconnected Power System (BIPS).
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Robert Wayne Samohyl
  • Departamento de Engenharia de Produção e Sistemas
Sayonara Barbosa
  • Departamento de Enfermagem
Vinicius Albani
  • Departamento de Matemática
Maria Luiza Bazzo
  • Departamento de Análises Clínicas
Natália Mezzomo
  • Departamento de Engenharia Química e Engenharia de Alimentos
Campus Universitário, 89520-000, Florianópolis, Santa Catarina, Brazil
Head of institution
Ubaldo César Balthazar
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