Federal Center for Technological Education of Minas Gerais

The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of noncovalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, the performance assessment of three software single-phase phase-locked loop (PLL) algorithms is carried out by means of dynamic analysis and experimental results. Several line disturbances such as phase-angle jump, voltage sag, frequency step, and harmonics are generated by a DSP together with a D/A converter and applied to each PLL. The actual minus the estimated phase-angle values are displayed, providing a refined method for performance evaluation and comparison. Guidelines for parameters adjustments are also presented. In addition, practical implementation issues such as computational delay effects, ride-through, and computational load are addressed. The developed models proved to accurately represent the PLLs under real test conditions. </para>

Images held by 271 college students and 36 junior high school teachers for the concept of a mathematical function were compared to the definitions they gave for the concept. A questionaire was designed to exhibit the cognitive schemes for the function concept that become active in identification and construction problems and to make possible the comparison of these schemes with the definition. Many of the definitions and even more of the images were primitive among all but the mathematics majors and the teachers. Discrepancies between image and definition were frequent for all subjects who gave the Dirichlet-Bourbaki definition.

BACKGROUND: The application of artificial intelligence (AI) opens an interesting perspective for predicting injury risk and performance in team sports. A better understanding of the techniques of AI employed and of the sports that are using AI is clearly warranted. The purpose of this study is to identify which AI approaches have been applied to investigate sport performance and injury risk and to find out which AI techniques each sport has been using. METHODS: Systematic searches through the PubMed, Scopus, and Web of Science online databases were conducted for articles reporting AI techniques or methods applied to team sports athletes. RESULTS: Fifty-eight studies were included in the review with 11 AI techniques or methods being applied in 12 team sports. Pooled sample consisted of 6456 participants (97% male, 25 ± 8 years old; 3% female, 21 ± 10 years old) with 76% of them being professional athletes. The AI techniques or methods most frequently used were artificial neural networks, decision tree classifier, support vector machine, and Markov process with good performance metrics for all of them. Soccer, basketball, handball, and volleyball were the team sports with more applications of AI. CONCLUSIONS: The results of this review suggest a prevalent application of AI methods in team sports based on the number of published studies. The current state of development in the area proposes a promising future with regard to AI use in team sports. Further evaluation research based on prospective methods is warranted to establish the predictive performance of specific AI techniques and methods.

The very last wireless network technology, created to increase the speed and the connections responsiveness, the Fifth-Generation Network (5G) can transmit a great volume of data. It uses wireless broadband connections to support specific end-users and businesses services. It is specifically useful for the Internet of Vehicles (IoV), guaranteeing fast connections and security. The 5G network technology can be used to support Vehicle-to-Everything (V2X) communications and applications on autonomous vehicles. It can enable information exchanges between vehicles and other infrastructures and people. It can also provide a more comfortable and safer environment and accurate traffic knowledge. The traffic ?ow can be improved, reducing pollution and accident rates. The cellular network can be associated with V2X as a communicating base to offer enhanced road safety and autonomous driving, and also to offer the IoV connections. This survey presents the 5G technology evolution, standards, and infrastructure associated with V2X ecosystem by IoV. In other words, it presents the IoV supported by 5G V2X communications, considering its architecture, applications and also the V2X features and protocols, as well as the modes, the evaluation and the technological support in such combination. The contribution of this paper is a systematized study about the interaction among these three contents: IoV, 5G, and V2X. Eighty four works were selected to present concepts, standards and to identify the ways to overcome challenges. This survey aims to guide the development of new 5G-V2X services and technologies dedicated to vehicle communications, and also to indicate future directions.

BACKGROUND: Fungi are among the most abundant and diverse organisms on Earth. However, a substantial amount of the species diversity, relationships, habitats, and life strategies of these microorganisms remain to be discovered and characterized. One important factor hindering progress is the difficulty in correctly identifying fungi. Morphological and molecular characteristics have been applied in such tasks. Later, DNA barcoding has emerged as a new method for the rapid and reliable identification of species. The nrITS region is considered the universal barcode of Fungi, and the ITS1 and ITS2 sub-regions have been applied as metabarcoding markers. In this study, we performed a large-scale analysis of all the available Basidiomycota sequences from GenBank. We carried out a rigorous trimming of the initial dataset based in methodological principals of DNA Barcoding. Two different approaches (PCI and barcode gap) were used to determine the performance of the complete ITS region and sub-regions. RESULTS: For most of the Basidiomycota genera, the three genomic markers performed similarly, i.e., when one was considered a good marker for the identification of a genus, the others were also; the same results were observed when the performance was insufficient. However, based on barcode gap analyses, we identified genomic markers that had a superior identification performance than the others and genomic markers that were not indicated for the identification of some genera. Notably, neither the complete ITS nor the sub-regions were useful in identifying 11 of the 113 Basidiomycota genera. The complex phylogenetic relationships and the presence of cryptic species in some genera are possible explanations of this limitation and are discussed. CONCLUSIONS: Knowledge regarding the efficiency and limitations of the barcode markers that are currently used for the identification of organisms is crucial because it benefits research in many areas. Our study provides information that may guide researchers in choosing the most suitable genomic markers for identifying Basidiomycota species.

Most of the available data concerning lightning current parameters were obtained by means of measurements made in temperate regions in the Northern Hemisphere. Considering the influence of regional aspects on such parameters, the need for references concerning lightning protection practices specifically in tropical zones requires dedicated data. An experimental investigation program has been carried on in Brazil since 1971 in order to provide data for characterization of local lightning current parameters. The authors of the present work are involved in that research. With such purpose, they have evaluated a significant amount of data, obtained by means of measurements taken at an instrumented tower located at “Morro do Cachimbo” Station, in Southeastern Brazil. The lightning current wave registers correspond to 157 strokes, which were measured during 13 years at the station. In this paper, the authors present a statistical evaluation of measured current waves, with particular interest in front wave parameters. The considered parameters (peak current, front duration and front steepness) are compared with those traditionally presented in literature. The cumulative frequency distributions and the correlation coefficients between parameters were determined. One main result was derived from this work, concerning the negative downward discharges: the median (and average) value of current peak measured at tower basis was found to be around 50% and 30% higher, respectively for the first and subsequent strokes, than the usual Berger references measured at tower top.

An original semitheoretical causal model was developed to describe the frequency dependence of electrical parameters of soil in the representative frequency range of lightning currents. The expressions of such model, based simply on the measured low-frequency soil resistivity, can be promptly applied to general soils in practical problems. The model allows the user to adopt different levels of conservativeness to take the dispersion of the frequency dependence of soil and eventual uncertainties into account. The comparison of experimental results and those provided by this model denoted its consistency.

The objective of this study was to test an artificial neural network (ANN) for estimating the reference evapotranspiration (ETo) as a function of the maximum and minimum air temperatures in the Campos dos Goytacazes county, State of Rio de Janeiro. The data used in the network training were obtained from a historical series (September 1996 to August 2002) of daily climatic data collected in Campos dos Goytacazes county. When testing the artificial neural network, two historical series were used (September 2002 to August 2003) relative to Campos dos Goytacazes, and Viçosa, State of Minas Gerais. The ANNs (multilayer perceptron type) were trained to estimate ETo as a function of the maximum and minimum air temperatures, extraterrestrial radiation, and the daylight hours; and the last two were previously calculated as a function of either the local latitude or the Julian date. According to the results obtained in this ANN testing phase, it is concluded that when taking into account just the maximum and minimum air temperatures, it is possible to estimate ETo in Campos dos Goytacazes.

INTRODUCTION: Sarcopenia is a chronic condition that is associated with aging and characterized by a reduction of muscle mass, strength, and function. Sarcopenia is prevalent in patients with chronic kidney disease (CKD) and associated with increased morbidity and mortality, as well as cardiovascular complications. OBJECTIVES: To investigate the prevalence of sarcopenia in patients with CKD not yet on dialysis and its correlation with clinical and laboratory variables and inflammatory markers. METHODS: A total of 100 patients of both sexes aged over 18 were evaluated. Sarcopenia was defined using the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP) and of the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project. Sociodemographic and clinical data, activities of daily living, functional capacity, and physical activity were also evaluated. Inflammation was assessed by the serum levels of high-sensitivity C-reactive protein (hsCRP) and interleukin (IL) 4 and 6. RESULTS: The prevalence of sarcopenia was 11.9% and 28.7% using the EWGSOP and FNIH criteria, respectively. Sarcopenia was more prevalent in the more advanced stages of CKD (34.5% in stages 2 and 3A; and 65.5% in stages 3B, 4, and 5) and associated with worse performance in activities of daily living (p = 0.049), lower walking speeds (p < 0.001), and higher body mass indexes (BMIs) (p = 0.001) in the non-adjusted model. In addition, patients with sarcopenia had lower functional capacity (p = 0.012) and higher prevalence of physical inactivity (p = 0.041) compared with patients without sarcopenia. After adjustment for confounding variables, sarcopenia was still significantly correlated with walking speed (p = 0.004) and BMI (p = 0.002). HsCRP levels were inversely correlated with appendicular lean mass adjusted for BMI (p = 0.007) and were also positively associated with BMI (p = 0.001). IL4 levels were positively correlated with walking speed (p = 0.007) and lean mass in the lower limbs (p = 0.022). CONCLUSIONS: Sarcopenia is common in patients with CKD, particularly in the most advanced stages of the disease. We observed an association between the levels of inflammatory markers and peripheral lean body mass, physical performance, and BMI. This association between sarcopenia and modifiable factors highlights the importance of early diagnosis and the implementation of therapeutic measures to minimize adverse outcomes in patients with CKD not yet on dialysis.

The thermal stability of natural fiber composites is a relevant aspect to be considered since the processing temperature plays a critical role in the manufacturing process of composites. At higher temperatures, the natural fiber components (cellulose, hemicellulose, and lignin) start to degrade and their major properties (mechanical and thermal) change. Different methods are used in the literature to determine the thermal properties of natural fiber composites as well as to help to understand and determine their suitability for a certain applications (e.g., Thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and differential mechanical thermal analysis (DMA)). Weight loss percentage, the degradation temperature, glass transition temperature (Tg), and viscoelastic properties (storage modulus, loss modulus, and the damping factor) are the most common thermal properties determined by these methods. This paper provides an overview of the recent advances made regarding the thermal properties of natural and hybrid fiber composites in thermoset and thermoplastic polymeric matrices. First, the main factors that affect the thermal properties of natural and hybrid fiber composites (fiber and matrix type, the presence of fillers, fiber content and orientation, the treatment of the fibers, and manufacturing process) are briefly presented. Further, the methods used to determine the thermal properties of natural and hybrid composites are discussed. It is concluded that thermal analysis can provide useful information for the development of new materials and the optimization of the selection process of these materials for new applications. It is crucial to ensure that the natural fibers used in the composites can withstand the heat required during the fabrication process and retain their characteristics in service.

A sufficient condition for robust D-stability of linear systems with polytope type uncertainties is proposed. The result is based on a linear parameter-dependent Lyapunov function obtained from the feasibility test of a set of linear matrix inequalities (LMIs) defined at the vertices of the polytope. This improved LMI condition encompasses previous results based on additional inequalities, as well as results based on extra variables.

DC microgrids have been known to be a promising solution for improving renewable energy integration with electrical grid and enhancing the system's overall energy efficiency. A key component of this microgrid is the energy storage system, which besides smoothing the intermittent behavior of renewable sources, also allows intentional islanding and the execution of optimization routines to improve the microgrid performance. Assuming that storage systems in commercial and residential buildings will mostly be composed of multiple storage units, an energy storage management system, which provides charge/discharge monitoring and state-of-charge (SOC) equalization, is needed to prevent overcharging the units or their uneven use, which can lead to faster deterioration of battery banks. This paper proposes an energy storage management system based on distributed secondary level control, which promotes charge/discharge control and provides SOC equalization simultaneously. The SOC imbalance compensation alters the energy storage unit virtual droop resistance according to the difference between the unit SOC and the microgrid average SOC, thus the compensation intensity is dependent on the imbalance level being suitable to be employed in dc bus signaling controlled microgrids.

This work presents a novel current multilevel (CML) inverter topology, named boost CML inverter, and its application on energy processing of single-phase grid-connected photovoltaic (PV) systems. The structure allows a high power factor operation of a PV system, injecting a quasi-sinusoidal current into the grid, with virtually no displacement in relation to the line voltage at the point of common coupling among the PV system and the loads. The major appeals of using the CML technique are the balanced current sharing among semiconductor switches and the decrease of the current slope in the circuit devices, with a consequent reduction of conducted and radiated electromagnetic interference (EMI). The CML technique also allows adapting or minimizing current waveforms harmonic content. System description, mathematical approach, and design guidelines are presented, providing an overview of the new topology. In order to validate the proposed concepts, experimental measurements, made in a small-scale laboratory prototype, are also presented. The obtained results evidence the feasibility of the application of this new topology on singlephase grid-connected PV systems.

Despite offering very attractive advantages over traditional joining methods, one of the setbacks of adhesive bonding is its long-term strength in aggressive environments, such as environments with high moisture and extreme temperatures. With the rise of new lightweight materials and their recent use in everyday vehicles, transportation industries have been very interested in determining the long-term behavior of adhesive joints. The aim is to build durable, lighter vehicles, which consume less energy and emit less pollution. The two main factors that affect the strength of vehicle adhesive joints are exposure to moist environments and high and low temperatures. There are some works concerning the effect of these two factors separately and some predictive models have been developed, which help the engineer to design reliable, safe, and efficient adhesive joints. However, the combined effect of temperature and moisture is not yet totally understood. This paper presents a review on the temperature and moisture degradation of adhesive joints.

AIMS: The aim was to investigate the biosorption of chromium, nickel and iron from metallurgical effluents, produced by a steel foundry, using a strain of Aspergillus terreus immobilized in polyurethane foam. METHODS AND RESULTS: A. terreus UFMG-F01 was immobilized in polyurethane foam and subjected to biosorption tests with metallurgical effluents. Maximal metal uptake values of 164.5 mg g(-1) iron, 96.5 mg g(-1) chromium and 19.6 mg g(-1) nickel were attained in a culture medium containing 100% of effluent stream supplemented with 1% of glucose, after 6 d of incubation. CONCLUSIONS: Microbial populations in metal-polluted environments include fungi that have adapted to otherwise toxic concentrations of heavy metals and have become metal resistant. In this work, a strain of A. terreus was successfully used as a metal biosorbent for the treatment of metallurgical effluents. SIGNIFICANCE AND IMPACT OF THE STUDY: A. terreus UFMG-F01 was shown to have good biosorption properties with respect to heavy metals. The low cost and simplicity of this technique make its use ideal for the treatment of effluents from steel foundries.

Abstract Starch is a natural, renewable, and biodegradable polymer produced by many plants as a source of stored energy. The structural and functional diversity of starches makes them suitable for different applications. Various physical, chemical, and enzymatic modifications can change and improve functional properties of starch to facilitate its use for different pharmaceutical purposes. Currently, some types of starches—for example, native starch, sodium starch glycolate (chemically modified starch), and pregelatinized starch (physically modified starch)—are approved by the United States Food and Drug Administration (FDA) for use either as an isolated excipient or as a matrix for drug delivery systems in granules, capsules, tablets, suppositories, implants, stents, transdermal, and ophthalmic systems. However, the increasing number of drug moieties with varying physicochemical and stability properties along with the development of new drug production processes and drug delivery systems exert pressure on formulators to search for new excipients that achieve the desired set of functionalities. This paper offers a clear overview of native and modified starches and their use in pharmaceutical and biomedical applications, either as excipients or as drug delivery systems. In addition, some drug release mechanisms, which include encapsulants, micro/nanoparticles hydrogels and scaffolds, are discussed.

This paper presents a three-phase line-interactive uninterruptible power supply (UPS) system with series-parallel active power-line conditioning capabilities, using a synchronous-reference-frame (SRF)-based controller, which allows an effective power-factor correction, load harmonic current suppression, and output voltage regulation. The three-phase UPS system is composed of two active power filter topologies. The first one is a series active power filter, which works as a sinusoidal current source in phase with the input voltage. The other is a parallel active power filter, which works as a sinusoidal voltage source in phase with the input voltage, providing to the load a regulated and sinusoidal voltage with low total harmonic distortion. Operation of a three-phase phase-locked loop structure, used in the proposed line-interactive UPS implementation, is presented and experimentally verified under distorted utility conditions. The control algorithm using the SRF method and the active power flow through the UPS system are described and analytically studied. Design procedures, digital simulations, and experimental results for a prototype are presented to verify the good performance of the proposed three-phase line-interactive UPS system.

Schistosomiasis remains a serious health issue nowadays for an estimated one billion people in 79 countries around the world. Great efforts have been made to identify good vaccine candidates during the last decades, but only three molecules reached clinical trials so far. The reverse vaccinology approach has become an attractive option for vaccine design, especially regarding parasites like Schistosoma spp. that present limitations for culture maintenance. This strategy also has prompted the construction of multi-epitope based vaccines, with great immunological foreseen properties as well as being less prone to contamination, autoimmunity, and allergenic responses. Therefore, in this study we applied a robust immunoinformatics approach, targeting S. mansoni transmembrane proteins, in order to construct a chimeric antigen. Initially, the search for all hypothetical transmembrane proteins in GeneDB provided a total of 584 sequences. Using the PSORT II and CCTOP servers we reduced this to 37 plasma membrane proteins, from which extracellular domains were used for epitope prediction. Nineteen common MHC-I and MHC-II binding epitopes, from eight proteins, comprised the final multi-epitope construct, along with suitable adjuvants. The final chimeric multi-epitope vaccine was predicted as prone to induce B-cell and IFN-γ based immunity, as well as presented itself as stable and non-allergenic molecule. Finally, molecular docking and molecular dynamics foresee stable interactions between the putative antigen and the immune receptor TLR 4. Our results indicate that the multi-epitope vaccine might stimulate humoral and cellular immune responses and could be a potential vaccine candidate against schistosomiasis.

Hybrid joining (HJ) is the combination of two or more joining techniques to produce joints with enhanced properties in comparison to those obtained from their parent techniques. Their adoption is widespread (metal to metal joint, composite to composite and composite to metal) and is present in a vast range of applications including all industrial sectors, from automotive to aerospace, including naval, construction, mechanical and utilities. The objective of this literature review is to summarize the existing research on hybrid joining processes incorporating structural adhesives highlighting their field of application and to present the recent development in this field. To achieve this goal, the first part presents an introduction on the main class of adhesives, subdivided by their chemical nature (epoxy, polyurethane, acrylic and cyanoacrylate, anaerobic and high-temperature adhesives) The second part describes the most commonly used Hybrid Joining (HJ) techniques (mechanical fastening and adhesive bonding, welding processes and adhesive bonding) The third part of the review is about the application of adhesives in dependence of performance, advantage and disadvantage in the hybrid joining processes. Finally, conclusions and an outlook on critical challenges, future perspectives and research activities are summarized. It was concluded that the use of hybrid joining technology could be considered as a potential solution in various industries, in order to reduce the mass as well as the manufacturing cost.