Polyunsaturated fatty acids (PUFAs) and antioxidants are important mediators in the central nervous system (CNS). Lipid derivatives may be used to generate endocannabinoids or prostanoids derived from arachidonic acid, which attenuates excitotoxicity in quadripartite synapses with a focus in astrocytes and microglia; on the other hand, antioxidants, such as glutathione (GSH) and ascorbate, have been shown to signal through transmitter receptors and protect against acute and chronic oxidative stress, modulating the activity of different signaling pathways. Several authors have investigated the role of these nutrients in young and senescent brain, as well as in degenerative conditions such as Alzheimer’s and Parkinson's diseases. Through literature review, we aimed to highlight recent data on the role of fatty acids, antioxidants and physical activity in physiology and in molecular mechanisms of brain senescence. Data indicate the complexity and essentiality of endogenous/dietary antioxidants for maintenance of the redox status and control of neuroglial signaling under stress. Recent studies also indicate that omega-3 and -6 fatty acids act in a competitive manner to generate mediators for energy metabolism, feeding behavior, plasticity and memory mechanisms throughout aging. Finding pharmacological or dietary resources that mitigate or prevent neurodegenerative affections continues to be a great challenge and require additional efforts from researchers, clinicians and nutritionists in the field.

In this work, nine fruits cultivated in the northern Amazon were studied: abiu, acerola, araçá, bacupari, biribá, caçarí, fruta-do-conde, graviola and taperebá, with the objective of carrying out a bromatological and nutritional study of the pulps of fruits studied. Of all of them, are the pulps of graviola (76.83 ± 0.02 kcal 100 g^-1) bacupari (76.83 ± 0.02 kcal 100 g^-1) and fruta-do-conde (46.66 ± 0.02 kcal 100 g^-1). Among the macronutrients, the high concentration of potassium stands out, especially in the graviola (541.16 ± 0.24 mg 100 g^-1) and the biribá (468.21 ± 0.13 mg 100 g^-1). Among the micronutrients, iron concentrations are representative for araçá pulp (3.04 ± 0.02 mg 100g-1), abiu is rich in zinc (3.71 ± 0.02 mg 100 g^-1) and manganese (6.61 ± 0.11 mg 100 g^-1). The presence of cobalt at the level of traces in some of the pulps studied stands out. The Pearson correlation coefficient was evaluated, as well as the statistical treatment by multivariate analysis PCA to establish the correlation between the variables studied.

: The objective of this study was to obtain different dry matter contents and proportions of mel-on plant biomass for silage making. A completely randomized design was adopted with a facto-rial scheme (3 x 2) in four replications. The first factor corresponded to three mixtures of melon biomass on as fed basis (AF) of plant (branch + leaf) and fruit (harvested melon) as follows: 100% plant, 90% plant + 10% fruit, and 100% fruit. The other factor corresponded to the ensiled materi-al with fresh and dehydrated melon plant biomass (40% DM) which was dried in the field, after harvest. Silages with partial dehydration of the biomass available after fruit harvest with 0% and 10% fruit showed the greatest DM values: 297 and 293 g/kg DM, respectively. Silages with 0, 100 and 10% fruit showed medium LAB populations: 5.79, 5.14 and 4.58 logs CFU/g, respectively. Higher concentrations of acetic acid contents were observed in silages with 0 and 10% fresh fruit, which were 14.9 and 14.1 g/kg DM, respectively. Silages with 0% and 100% of dehydrated fruit showed better results for the indicators of good-quality silage. Dehydration improves the fer-mentative profile and quality of the melon silage.

Native plants from the Brazilian Amazon Biome are rich in nutrientes, oils and fats and, therefore, represent a very important regional food resource. Althoung there is a global interest in the nutritional potential of tropical fruits, the potential of Amazonian fruits as source of essential fatty acids is still under exploited, since their composition is still understudied. ¹H Magnetic Resonance Nuclear (¹H NMR) is a robust spectroscopic tool to profile fatty acids components in oils. The objectives of this work were to use ¹H NMR to determine the fatty acids profile and the physicochemical properties of crude oils and fats obtained from fruits of Brazilian Amazon: açaí, ata-brava, bacaba, buriti, buritirana, murici amarelo, murici vermelho, piaçaba braba, tucumanzinho, pupunha red and yellow varieties. Oils were obtained by Soxhlet extraction using hexane as a solvent. After solvent removal by rotoevaporation, the resulting oils and fats were analyzed by ¹H NMR spectroscopy. Unsaturated fatty acids oleic (ω9), linoleic (ω6) and linolenic (ω3) acids were quantified in the oils and their physicochemical properties were determined. It was observed that the oils have predominately ω9 fatty acids, followed by ω6 and ω3 representatives. The physicochemical properties confirmed edibility and good quality of oils and fats present in the aforementioned Amazonian fruits.

The aims of study was to evaluate the effects of rates, sources and timing of nitrogen application under cover of transgenic corn yield cultivated in Amazon Biome. The experiments were conducted in Parauapebas city, State of Pará, Brazil, in two years (2016/2017 and 2017/2018). The experimental design was randomized blocks, in a 5x2x2 factorial scheme, consisting of five rates of N (0; 45; 90; 135; and 180 kg ha-1), two nitrogen sources (urea and ammonium sulfate) and two application times of N (phenological stages V4 and V8), with four replications. The factor N rates promoted adjustment of linear equation (leaf area index, mass of thousand grains, and yield) and quadratic equation (dry mass of leaf index). Nitrogen fertilization promoted significant increases in mass of thousand grains and yield, obtaining the best results with 180 kg ha-1 of N applied at V4 phenological stage. Based on results obtained in two years of corn cultivated under conditions of Amazon Biome, the application of N at V4 phenological stage at rates of 121 to 131.39 kg ha-1 of N showed the best results for vegetative growth, while 180 kg ha-1 of N, regardless of source used, urea or ammonium sulfate, promoted greater grain weight and greater yield.

Despite the overall extension of the Amazon basin (approximately 6,000,000),which encompasses such a complex ecosystem and territories belonging to seven different nations, it is worth mentioning that environmental assessment related to changes in land use and land cover (LULC) in this region are often conducted respecting geopolitical boundaries associated with each country or taking into account the so-called Amazon biome. With the purpose of prospecting the intricate and hidden hydrological patterns, we undertake an in-depth evaluation of the water balance along the 2001-2021 time span across the whole basin, whose behavior depends on the features deriving from the metamorphoses in land use and land cover. To accomplish that task, the influence of the components of the water balance, namely rainfall and evapotranspiration, jointly with the terrestrial topographic mapping, are examined to investigate the interactions among the physical mechanisms that make up the hydrological cycle and the corresponding physical hydrological processes triggered by deforestation and reforestation in the region. More specifically, the modeling approach was rigorously designed to also consider, separately or not Negro, Solimões, Madeira, Tapajós and Xingu hydrographic sub-basins, which are the most important ones of the Amazon basin. The results highlight that, in the southern region of the Amazon, specifically within the Madeira river sub-basin, the lowest forest coverage is observed (56.0%), whereas in the northern Negro river sub-basin, the most notable forest coverage is observed (85.0%).The most preserved forest areas, such as the Negro and Solimões river sub-basins, with percentages of 81.9% and 74.2%, respectively, have higher annual rates of precipitation and evapotranspiration over time. On the other hand, regions that suffered the most intense deforestation along the time period studied, such as the Madeira, Tapajós and Xingu sub-basins, have lower annual rates of precipitation and evapotranspiration, with a preservation percentage of 54.6%, 62.6% and 70, 7%, respectively. As the pace of deforestation slowed between 2003 and 2013, annual precipitation rates increased by 12.0%, while evapotranspiration decreased by 2.0%. The hydrological findings of this paper highlight th predominant role of the forest in the context of the global water balance of the Amazon basin and the potential to also produce distinct impacts within different parts of the basin in terms of having more or less rainfall and evaporation. In addition, those variabilities in the hydrological operational components and mechanisms due to changes in land cover and land use also reveals the potential impacts that could be expected in the surrounding areas, closer or farther, notably beyond the limits of the Amazon basin.

Smart Grid systems have become popular and necessary for the development of a sustainable power grid. These systems use different technologies to provide optimized services to the users of the network. Regarding computing, these systems optimize electrical services by processing a large amount of data generated. However, privacy and security are essential in this kind of system. With a large amount of data generated, it is necessary to protect the privacy of users, because this data may reveal users’ personal information. Today, blockchain technology has proven to be an efficient architecture for solving privacy and security problems in different scenarios. Over the years, different blockchain platforms have emerged, attempting to solve specific problems in different areas. However, the use of different platforms fragmented the market, which was no different in the smart grid scenario. This work proposes a blockchain architecture that uses sidechains to make the system scalable and adaptable. We used three blockchains to ensure privacy, security, and trust in the system. To universalize the proposed solution, we used the OSGP protocol and smart contracts. The results show that architecture security and privacy are guaranteed, making it feasible for implementation in real systems. Although scalability issues regarding the storage of data generated still exists.

The retina is the sensory tissue responsible for the first stages of visual processing, with a conserved anatomy and functional architecture among vertebrates. To date, retinal eye diseases, such as diabetic retinopathy, age-related macular degeneration, retinitis pigmentosa, glaucoma and others, affect nearly 170 million people worldwide, resulting in vision loss and blindness. To tackle retinal disorders, the developing retina has been explored as a versatile model to study intercellular signaling, as it presents a broad neurochemical repertoire. Retina, dissociated and arranged as typical cultures, as mixed or neuron- and glia-enriched, and/or organized as neurospheres or as organoids are valuable to understand both neuronal and glial compartments which have contributed to reveal roles and mechanisms of transmitter systems as well as antioxidants, trophic factors, and extracellular matrix proteins. Overall, contributions in understanding neurogenesis, tissue development, differentiation, connectivity, plasticity, and cell death are widely described. A complete access to the genome of several vertebrates, as well the recent transcriptome at the single cell level at different stages of development also anticipates future advances in providing cues to target blinding diseases or retinal dysfunctions.

Mosquitoes transmit pathogens that cause human diseases such as malaria, Dengue fever, Chikungunya, yellow fever, Zika fever, and filariasis. Chemical pesticides are effective instruments for reducing disease transmission and managing mosquito populations. However, these chemicals have drawbacks such as high production costs and negative effects on the environment and non-target organisms. Furthermore, as mosquitoes develop resistance to chemical insecticides, they become less effective. As a result, researchers are investigating novel insecticides. Advances in microbial biotechnology have resulted in a wide range of value-added products, including biopesticides for agricultural and public health purposes. In this review, we highlight the mainly untapped biotechnological potential of microorganisms for vector mosquito control and disease transmission reduction. Also, we underline the importance of more basic research and improved translational research methodologies, encouraging efforts to bridge the gap between academic research on biopesticides and public health interventions.

Metal corrosion poses a significant challenge for industries by decreasing the lifespan of materials and escalat-ing maintenance and replacement costs. This study is critically important as it assesses the corrosion resistance properties of annealed steel wire electrodes coated with manganese, employing chronoamperometry and linear voltammetry techniques. The electrodes were immersed in an electrolyte solution and subjected to chronoam-perometry at various voltages (-0.55 V, -0.60 V, and -0.70 V) and durations (60 seconds and 1800 seconds). Sub-sequently, linear voltammetry was performed over a potential range from -0.8 V to 0.8 V to generate Tafel plots. The Butler-Volmer equation was applied to the data obtained to determine the corrosion current density. The re-sults indicate that the optimal conditions for forming a highly effective protective manganese layer occur at a potential of -0.70 V for 1800 seconds. Under these conditions, the electrodes exhibited superior corrosion re-sistance. The study also revealed that shorter durations and less negative potentials led to less effective manga-nese coatings, with higher corrosion rates and reduced stability. These findings are significant for developing ef-ficient corrosion protection methods in industrial and research applications, providing clear parameters for op-timizing the manganese electrodeposition process on annealed steel.

The COVID-19 pandemic plagues the whole world, bringing numerous challenges which need to be addressed. One of them is the privacy of patient data. There are several problems related to data privacy in IoT environments, the use of applications, devices, and functionalities in hospital processes. Therefore, we have compared works from the literature and developed a taxonomy consisting of the requirements necessary to control patient privacy data in a hospital setting in the current pandemic. Based on the studies, an application was modeled and implemented. According to the tests and comparisons drawn between the variables, the application yielded satisfactory results.

According to the World Health Organization, about 15% of the world’s population has some form of disability. Assistive Technology, in this context, contributes directly to the overcoming of difficulties encountered by people with disabilities in their daily lives, allowing them to receive education and become part of the labor market and society in a worthy manner. Assistive Technology has made great advances in its integration with Artificial Intelligence of Things (AIoT) devices. AIoT processes and analyzes the large amount of data generated by IoT devices and applies Artificial Intelligence models, specifically Machine Learning, to discover patterns for generating insights and assisting in decision making. Based on a systematic literature review, this article aims at identifying the Machine Learning models used in multiple different research about Artificial Intelligence of Things applied to Assistive Technology. The survey of the topics approached in this article also highlights the context of such research, their application, IoT devices used, and gaps and opportunities for further development. Survey results show that 50% of the analyzed research address visual impairment, and for this reason, most of the topics cover issues related to computational vision. Portable devices, wearables, and smartphones constituted the majority of IoT devices. Deep Neural Networks represent 81% of the Machine Learning models applied in the reviewed research.

The dogs with canine visceral leishmaniasis (CVL) play a key role in the transmission cycle of Leishmania infantum to humans in the urban environment. There is a consensus regarding the importance of developing a vaccine to control this disease. Despite many efforts to develop a protective vaccine against CVL, the ones currently available, CaniLeish®, Leish-tec® and LetiFend® have limited effectiveness. This is due, in part, to the complexity of the immune response of the naturally infected dogs against the parasite and the complexity of the parasite transmission cycle. Thus, strategies such as the development of a transmission-blocking vaccines (TBVs), already being applied to other vector-borne diseases like malaria and dengue, would be an attractive alternative to control leishmaniasis. TBVs induce the production of antibodies in the vertebrate host, which can inhibit parasite development in the vector and/or interfere with aspects of vector biology, leading to an interruption of parasite transmission. To date, there are few TBVs studies for CVL and other leishmaniasis forms. However, the few studies that exist show promising results justifying further development of this approach.

Language learners often face communication problems when they need to express themselves and do not have this ability. On the other hand, continuous advances in technology create new opportunities to improve second language (L2) acquisition through context-aware ubiquitous learning (CAUL) technology. Since vocabulary is the foundation of all language acquisition, this article presents the ULearnEnglish, an open-source system to allow ubiquitous English learning focused on incidental vocabulary acquisition. To evaluate the proposal, 15 learners used the system developed, and 10 answered a survey based on the Technology Acceptance Model (TAM). Results indicate a favorable response to the use of the learner context to assist them in their learning. The ULearnEnglish achieved an acceptance of 78.66% for the perception of the utility, 96% for the perception of ease of use, 86% for user context assessment, and 88% for ubiquity. This study presented a positive response in using the location of users to assist their learning. Among the main contributions, this study demonstrates an opportunity for ubiquity use in future research in language learning. Also, furthers studies can use the source available to evolve the model and system.

Bone morphogenetic protein (BMP) and platelet-derived growth factor (PDGF) are known to regulate and stimulate osteogenesis, both proteins playing an important role in bone homeostasis, constituting good candidates for osteoporosis´ treatment. Herein we aim to evaluate the effects of recombinant human BMP-7 (rhBMP7) and PDGF-BB (rhPDGF-BB) in oophorectomy-induced osteoporosis in rats. To this end, 40 Sprague-Dawley rats were submitted to oophorectomy surgery and treatments were started at the 100th day after the surgery, when all animals showed signs of osteoporosis. These peptide growth factors were applied intravenously once or twice a week and animals were followed for a total of five weeks. Two weeks after the end of the treatments, the animals were euthanized, the tissues were collected and Alkaline Phosphatase, X-ray, micro-CT and histology were assessed. The results indicate that the most promising treatments are: 20 µg/kg PDGF-BB + 30 µg/kg BMP-7 2x/week and 30 µg/kg BMP-7 2x/week, presenting an increase of 15% (p<0.05) and 13% (p<0.05) in bone volume fraction and 21% (p<0.05) and 23% (p<0.05) in trabecular number, respectively. In conclusion, rhPDGF-BB and rhBMP-7 are capable of inducing an increase in bone volume and density in this osteoporotic animal model, constituting interesting candidates for osteoporosis treatment.

This paper describes the preparation and description of four new complexes [Bu₂Sn(AA)Cl] (AA = glycine, DL-valine and L-leucine) and [Bu₂SnPhen₂] (Phen = DL-phenylalanine) They were characterized by elemental analyses of carbon, hydrogen, nitrogen, chlorine and tin; and by infrared, ^119mSn-Mössbauer and ^119mSn-RMN spectroscopies, and by the applications of TG and DSC techniques in dynamic helium atmosphere. For the [Bu₂Sn(AA)Cl], trigonal bipyramidal tin species, AA were coordinated bidentatedly by the carboxylic oxygen and by the NH₂ group. The [Bu₂SnPhen₂)], with tin atoms in trans-octahedral sites, had the Phen-coordinated by both carboxylic oxygen atoms.

In Brazil, malaria transmission is mostly confined to the Amazon, where substantial progress has been achieved towards disease control in the past decade. Vector control has been historically considered a fundamental part of the main malaria control programs implemented in Brazil. However, the conventional vector-control tools have been insufficient to eliminate local vector populations due to the complexity of the Amazonian rainforest environment and ecological features of malaria vector species in the Amazon, especially Anopheles darlingi. Malaria elimination in Brazil and worldwide eradication will require a combination of conventional and new approaches that takes into account the regional specificities of vector populations and malaria transmission dynamics. Here we present an overview on both conventional and novel promising vector-focused tools to curb malaria transmission in the Brazilian Amazon. If well designed and employed, these new vector-based approaches may improve the implementation of malaria-control programs, particularly in remote or difficult-to-access areas and in regions where existing interventions have been unable to eliminate disease transmission. However, much effort still has to be put on research expanding the knowledge of neotropical malaria vectors to set the steppingstones for the development of such innovative tools.

With the evolution of technology over the years, it has become possible to develop intelligent environments based on the concept of the Internet of Things, distributed systems, and machine learning. Such environments are incorporated with various solutions to solve user demands from services. One of these solutions is UBIPRI middleware, whose central concept is to maintain privacy in smart environments and to receive notifications as one of its services. However, this service is freely performed, disregarding the privacy that the environment employs. Another consideration is that based on the researched related works, it was possible to identify that the authors do not use statistical hypothesis tests in their solutions developed in the presented context. This work proposes an architecture for notification management in smart environments, composed by a notification manager named PRIPRO to assign it to UBIPRI and to aim to perform tests and comparisons between classification algorithms to delimit which one is most feasible to implement in the PRINM decision-making mechanism. The experiments showed that the J48 algorithm obtained the best results compared to the other algorithms tested and compared.

The high protein content of several microalgal species makes them attractive and unconventional for applications in the food and pharmaceutical industries. Due to microalgae's robust cell wall, cell rupture is necessary to improve the extraction of their intracellular proteins. Thus, choosing a suitable cell-breaking treatment before protein extraction is a vital downstream processing step. Additionally, it is necessary to use an effective technique for monitoring and measuring the impact of rupture treatments on microalgal cell walls. In our study, Tetradesmus obliquus cells were disrupted by three different mechanical rupture methods: high-pressure homogenization (HPH), ultrasound (US), and ball milling (BM). The ruptured biomass cells were counted, and soluble proteins were extracted and quantified. The cell counting technique did not detect differences between intact and damaged cells after BM treatment because the dye (erythrosine B) did not permeate the microalgae biomass accurately. The US treatment promoted the highest yield of total protein extraction (19.95%). The yields of protein extraction of T. obliquus with HPH (15.68%) and BM (14.11%) were significantly (p value ≤ 0.05) lower than that achieved in the US treatment. The increase in the number of extraction steps increased the protein recovery. Thus, the content of extracted soluble protein was a reliable indirect index for a quantitative comparison of the cell disruption level.

Due to the increasing use of computer equipment, institutions and companies face challenges, such as sensitive data leaks and the spread of hate speech, which have severe consequences for organizations and their employees. Addressing these challenges is essential to avoid financial losses, reputational damage, and impacts on the psychological health of those involved. This paper presents a solution based on microservices for monitoring computers used by employees in organizations, including capturing information from the equipment using spyware techniques and a web application for managing alerts. The solution seeks to detect data leaks, suspicious behaviour, and hate speech. The results of the evaluation indicate that the proposed solution has an efficient data capture time and can identify unwanted behaviour in a short period. The solution also includes applying prediction models to detect hate speech, achieving an average accuracy of approximately 87%. The performance, scalability, and security evaluation demonstrate that the solution is suitable for dealing with data leakage and hate speech challenges in the corporate environment.

Angiogenesis is a process whereby new blood vessels are born from preexistent ones, which has a role in transporting oxygen and nutrients. On the other hand, inhibiting this process is a strategy used to treat some diseases, including cancers, diabetic retinopathy, and rheumatoid arthritis. This study investigates the effect of a new nutraceutical (Terasen®) on angiogenesis. Terasen® is made from a standardized extract of Euterpe oleraceae (Açaí), Myrciaria dubia (Camu-Camu), and purified oil of Bixa orellana (Annatto) and Astrocaryum aculeatum (Tucumã). The in vivo angiogenesis model used was the chorioallantoic membrane (CAM) from chicken embryos. The embryos were divided into seven groups: a vehicle control treated with ethanol solution (ETH), a naïve control treated only with saline solution (SOR), a positive control treated with dexamethasone (DEX), and four groups treated with Terasen® at different concentrations (0.5, 1, 2, and 3 mg/ml). The parameters assessed were the vessels’ area, length, and amount. The results show a statistically significant and concentration-dependent inhibition of angiogenesis caused by Terasen®. Our results suggest the nutraceutical has a high antiangiogenesis potential, possibly due to its bioactive compounds, including anthocyanins, quercetin, and tocotrienols.

Baía de Todos os Santos is the second largest bay in Brazil and is home to important ecosystems, including estuarine systems and mangroves. However, studies on the seasonal variability of its soil properties and composition are still scarce. For this study, soil and leaf samples were seasonally collected from mangrove forests at four sites (Cacha Prego, Ponta Grossa, Ilha de Maré, and Pitinga), which are representative of different environmental conditions within the BTS. Soil physicochemical properties, soil composition and partition of Fe forms were determined, and analysis of minerals by Scanning Electron Microscope, was performed on soil samples. Isotopic ratios (δ13C, δ15N) were also determined on soil and leaf samples. Soils showed significant spatial and temporal changes affecting both their properties (pH, Eh) and their composition (TOC, pyrite and Fe oxyhydroxide contents). Clear spatial changes were observed in redox potential, significantly affecting the concentrations of the different geochemical forms of Fe, particularly the concentrations of crystalline oxyhydroxydes and pyrite in one of the studied sites. In three of the study sites, pyrite crystals showed clear evidence of degradation associated with sandy soils. Finally, δ13C and N/C ratios in soils seem to suggest a mixed origin of organic matter.

The N-acylhydrazone function has been reported as a pharmacophore group of molecules with diverse pharmacological activities, including anti-inflammatory effects. Thus, this study evaluated the anti-inflammatory potential of the compound N'-(3-(1H-indol-3-yl)benzylidene)-2-cyanoacetohydrazide (JR19) in vivo. The study started with the carrageenan-induced peritonitis model, followed by an investigation of leukocyte migration using the subcutaneous air pouch test and an assessment of the antinociceptive profile using formalin-induced pain. To find out the likely mechanism of action, a preliminary molecular docking study was performed focusing on the crystallographic structures of NFκB, iNOS, and sGCs. The computational study revealed satisfactory interaction energies with the selected targets, and the same peritonitis model was used to validate the involvement of the nitric oxide pathway and cytokine expression in the peritoneal exudate of mice pretreated with L-NAME or methylene blue. In the peritonitis assay, JR19 (10 and 20 mg/kg) reduced leukocyte migration by 59% and 52%, respectively, compared to the control group, with the 10 mg/kg dose used in subsequent assays. In the subcutaneous air pouch assay, the reduction in cell migration was 66%, and the response to intraplantar formalin was reduced by 39%, particularly during the inflammatory phase, suggesting that the compound lacks central analgesic activity. In addition, a reversal of the anti-inflammatory effect was observed in mice pretreated with L-NAME or methylene blue, indicating the involvement of iNOS and sGC in the anti-inflammatory response of JR19. The compound effectively and significantly decreased the levels of IL-6, TNF-α, IL-17, and IFN-γ, and this effect was reversed in animals pretreated with L-NAME, supporting a NO-dependent anti-inflammatory effect. In contrast, pretreatment with methylene blue only reversed the reduction in TNF-α levels. Therefore, these results demonstrate the pharmacological potential of the novel N-acylhydrazone derivative, which acts through the nitric oxide pathway and cytokine signaling, making it a strong candidate as an anti-inflammatory and immunomodulatory agent.

A one-dimensional numerical overland flow model based on the cascade plane theory was de-veloped to estimate rainfall-induced runoff and soil erosion on converging and diverging plane surfaces. The model includes three components: (i) soil infiltration using Horton’s infiltration equation, (ii) overland flow using the kinematic wave approximation of the one-dimensional Saint-Venant shallow water equations for a cascade of planes, and (iii) soil erosion based on the sediment transport continuity equation. The model’s performance was evaluated by comparing numerical results with laboratory data from experiments using a rainfall simulator and a soil flume. Four independent experiments were conducted on converging and diverging surfaces under var-ying slope and rainfall conditions. Overall, the numerically simulated hydrographs and sediment graphs closely matched the laboratory results, showing the efficiency of the model for the tested controlled laboratory conditions. The model was then used to numerically explore the impact of different plane soil surface geometries on runoff and soil loss. Seven geometries were studied: one rectangular, three diverging, and three converging. Constant soil surface area, rainfall intensity, and slope gradient were maintained in all simulations. Results showed that increasing convergence angles led to higher peak and total soil loss, while decreasing divergence angles reduced them.

The present work proposed a low-cost portable device as an enabling technology for Smart Farms using multispectral imaging and Machine Learning in soil texture. Clay is an important factor for the verification and monitoring of soil use due to its fast reaction to chemical and surface changes. The system developed uses the analysis of reflectance in wavebands for clay prediction. The selection of each wavelength is performed through an LED lamp panel. A NoIR microcamera controlled by a Raspberry Pi device is employed to acquire the image and unfold it in RGB histograms. Results showed an good prediction performance with R2 of 0.96, RMSEC of 3.66% and RMSECV of 16.87%. The high portability allows the equipment to be used in a field providing strategic information related to soil sciences.

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive MIMO scenario with favorable propagation, we derive analytical expressions for the sum-capacity. % Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high SNR regimes. % Furthermore, in the case of a high SNR regime, it is demonstrated that the Gamma PDF can approximate the PDF of the instantaneous channel sum-capacity as the number of BS antennas grows. A second important demonstration presented in this work is that a Gamma PDF can also be used to approximate the PDF of the summation of the channel's singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for LPWAN's as we show that the transmit power of each device can be made inversely proportional to the number of BS antennas.

In this brief letter we report our initial results on the application of deep-learning to the massive MIMO channel estimation challenge. We show that it is possible to estimate wireless channels and that the possibility of mitigating pilot-contamination with deep-learning is possible given that the leaning model underwent an extensive training-phase and that it has been presented with a large number of different channel conditions.

The Physical Random Access Channel (PRACH) plays an important role in LTE and LTE-A systems. It is through the PRACH channel that the user equipment (UE), based on eNodeB's timing estimates, aligns its uplink transmissions to the eNodeB's uplink and gain access to the network. One of the initial operations executed by the PRACH receiver at eNodeB side is the translation of the PRACH signal back to base band, $i.e.$, center the PRACH signal around DC. This operation is a necessary step for preamble detection and can be carried out through a time-domain frequency shift operation. Therefore, in this paper we present the hardware architecture and implementation details of a configurable and optimized FPGA-based time-domain frequency shifter. It is a hardware-efficient and accurate architecture for converting the relevant received PRACH signal into base band before further signal processing. The architecture is manly based on a customized Numerically Controlled Oscillator (NCO), which is used for generating complex exponentials employing only adders, a Look-Up Table (LUT) and plain logic resources. The main advantage of the proposed hardware architecture is that it completely eliminates the need for storing a large number of long complex exponential sequences by employing a single LUT and exploiting quarter wave symmetry of the basis waveform. Our simulation results show that the proposed customized NCO architecture provides high Spurious Free Dynamic Range (SFDR) signals using a minimal amount of FPGA resources. Moreover, the proposed architecture exhibits spur-suppression ranging from 62.13 to 153.58 dB without using Taylor Series correction.

This paper proposes the use of compressive sensing to tackle the Massive MIMO channel estimation problem. As our results show compressive sensing-based estimators perform as well as the optimum MMSE estimator.

In this letter, we advocate that it is possible to mitigate Pilot Contamination in Massive MIMO systems by scrambling the pilot sequences with a Base Station (BS) scrambling sequence. It is possible if a set of sequences is carefully designed to meet the orthogonality property defined in this letter. Each BS possesses its own scrambling sequence that can be reused the same way frequency reuse is applied to cell deployment. The main advantage of the prosed pilot generation scheme is that the frequency reuse factor can be set to 1, the most aggressive one, while the scrambling sequences can be reused with much less aggressive reuse factors (e.g. 4, 7, 9, 12, etc.), which in consequence results in pilot contamination mitigation and increased system's performance.

I present in this paper Diatomic, an open-source Excel application that calculates molar ther-modynamic properties for diatomic ideal gases. This application is very easy to use and requires only a limited number of molecular constants, which are freely available online. Despite its sim-plicity, Diatomic provides methodologies and results that are usually unavailable in general quantum chemistry packages. This application uses the general formalism of statistical mechanics, enabling two models to describe the rotational structure and two models to describe the vibra-tional structure. In this work, Diatomic was used to calculate standard molar thermodynamic properties for a set of fifteen diatomic ideal gases. Special emphasis was placed on the analysis of four properties (standard molar enthalpy of formation, molar heat capacity at constant pressure, average molar thermal enthalpy and standard molar entropy), which were compared with ex-perimental values. The results obtained lead to the following main conclusions: (i) the theoretical model used to describe rotational structure has a small effect on the accuracy of the results, (ii) at moderate and high temperatures, the Morse model gives better results than the harmonic model, and (iii) at the lowest temperatures both models give similar results.

This study was conducted with the objective of investigating the enrichment of weaned piglet diets with organic selenium (proteinate selenium) and inorganic selenium (sodium selenite) with two addition levels (0.15 and 0.30 mg/kg). A total of 40 piglets (20 castrated males and 20 females) weaned at 28 days of age with an average initial weight of 6.60±1.06 kg were used. The treatments were: Control diet (Control diet); Selenium-enriched control diet proteinate with 0.15 mg/kg of selenium added (SeOrg-0.15); Selenium-enriched control diet proteinate with 0.30 mg/kg of selenium added (SeOrg-0.30); Control diet enriched with sodium selenite with 0.15 mg/kg of selenium added (SeInorg-0.15); and Control diet enriched with sodium selenite with 0.30 mg/kg of selenium added (SeInorg-0.30). The presence of selenium in the control diet came from the ingredients and the mineral supplement. The following data were analyzed: productive performance; digestibility of nutrients and energy; morphometry and intestinal integrity; serum biochemical parameters; and gene expression of selenoproteins in intestinal epithelium and liver tissue of piglets. The SeOrg-0.30 treatment caused a reduction (P

The adoption of ADS-B in Latin America has been gradual but steady. Some countries, such as Brazil, Chile and Mexico, have made significant progress in the implementation of this system, while others are still in the early stages. It should be noted that the implementation of ADS-B is used in both military and civilian environments. For this reason, this research aims to provide information on the different characteristics that make up the surveillance systems. However, there are fundamental factors to promote the adaptation of ADS-B in Latin America, since they reduce the risk of collisions and air accidents by providing accurate and real-time information on the position and altitude of aircraft. On the other hand, it allows optimizing flight routes and reducing waiting time on the ground, which translates into fuel and cost savings for airlines. ADS-B increases the number of aircraft that can safely operate in the same airspace, which is especially important in regions with growing air traffic. ADS-B adoption in Latin America is expected to continue to grow in the coming years. The drivers for ADS-B adoption remain in place, and governments in the region are taking steps to accelerate its implementation.

The civil construction industry is one of the sectors that most consume natural resources in the world and, consequently, one of that generate more waste. Thinking about constructive techniques that generate less impact on the environment is vital to ensure sustainable development. In this scenario, the Life Cycle Assessment (LCA) has been presented as an internationally recognized approach, that assesses the potential impact of products and services on human health and the environment, throughout its entire life cycle. Aimed to identify construction techniques and vertical closing systems that generate less impact and consumption of natural resources, the impacts generated by the life cycle of the three vertical closing systems most applied in construction sites in Brazil were compared: ceramic brick masonry system (CBr); concrete block masonry system (CBk); and structural blocks masonry system (SBk). The SBk proved to be the least impacting to the “Resource Scarcity”, “Damage to Human Health”, and “Damage to the diversity of Ecosystems” interesting areas. This performance is directly related to the use of cement CPIII type and also by the fact that the SBk consumes less concrete and mortar than the others. Already the "Water Consumption" area, the CBk was the least impacting due to the lower consumption of electricity during its life cycle. The reliability of the results was proven through a sensitivity analysis of the normalization and characterization factors, which consisted of comparing the results obtained by applying two different methodologies. It is believed that the LCA study carried out can assist in the decision-making process regarding the choice of the most sustainable construction method.

There are few results about the internal damping ratio of normal and high strength concretes. Hence, this paper presents the expansion of the investigation about internal damping ratio under undamaged and damaged conditions, for usual concretes (NSC) and high strength concretes (HSC). In this way, the study cover a strength range of 42 to 83 MPa. Cyclic load was employed by a servo-controlled hydraulic testing machine and for each cyclic step the dynamic elastic modulus (Ed) and internal damping ratio (ξ) were determinate by acoustic tests. Normal strength concretes (fc = 42MPa) presented undamaged internal damping ratio ξ = 0.5% and achieved the maximum value of ξ = 2.5 for a damage index equal to 0.8. High strength concretes mixtures (fc = 83MPa) presented an undamaged internal damping of ξ=0.29% and maximum internal damping equal to ξ=0.93% (under damage index of 0.32). Porosity and the transition zones were the responsible to the initial internal damping values and how the material behavior under each cyclic load. The progressive damage generates the increase of coulomb damping. There are few studies allowing the quantification and comprehension of internal damping ratio under damage cyclic loading and this approach will lead to improve the understanding of NSC and HSC under dynamical excitation subject to damage evolution, mainly in impact situations.

Verminosis causes great damage to the producer, with reduced milk production and decreased development of young animals. The use of bioproducts are an alternative to control worms. This study evaluated the effects of oral administration of one commercial formulations, based on the fungus Duddingtonia flagrans (Bioverm®) and experimental formulations D. flagrans associated with Pochonia chlamydosporia, on the control of worms in naturally infected cattle on February pasture to October 2021. Eighteen Holstein x Zebu cattle were divided into groups of six animals (group 1 Bioverm®, group 2 Association and control), separated into paddocks naturally infected with helminth larvae (L3). The parasite load was by means of fecal samples and pasture collection to determine L3 infestation. The study demonstrated low recovery of L3 in the pasture due to low rainfall during the experiment. The EPG was lower in groups 1 and 2 compared to the control in April, May and July, while in March the values were lower only in treatment 1 compared to the control. Individual or combined administration of fungal products reduced the presence of eggs and larvae in pastures at certain months of the year, indicating their effectiveness in the strategic control of gastrointestinal parasites in cattle.

While there are several ways to identify customer behaviors, few extract this value from information already in a database, much less extract relevant characteristics. This paper presents the development of a prototype using the recency, frequency, and monetary attributes for customer segmentation of a retail database. For this purpose, the standard K-means, K-medoids, and MiniBatch K-means were evaluated. The standard K-means clustering algorithm was more appropriate for data clustering than other algorithms as it remained stable until solutions with 6 clusters. The evaluation of the clusters’ quality was obtained through the internal validation indexes: Silhouette, Calinski Harabasz, and Davies Bouldin. Once consensus was not obtained, three external validation indexes were applied: global stability, stability per cluster, and segment-level stability across solutions. Six customer segments were obtained, identified by their unique behavior: Lost customers, disinterested customers, recent customers, less recent customers, loyal customers, and best customers. Their behavior was evidenced and analyzed, indicating trends and preferences.

“De-[Constructing] Growth” is offered as a deeper and more useful conceptualization that avoids the negative connotations of, and resistance to, “degrowth” by decoupling profit from unsustainable consumption, production, and inequality.

Preterm birth accounts for about 10% of births worldwide. Studying risk factors for perinatal brain damage is essential, as findings suggest that almost 20% of disabilities are linked to risks in the early stages of development. This research aimed to study longitudinal changes in intelligence from 6 to 8 years of age in a sample of 39 preterm children with a history of risk of brain damage and a control group of 35 children born at term. The Wechsler Intelligence Scale (WISC-IV) was used for cognitive measurement. The results showed that the preterm group obtained significantly lower scores than the control group. The working memory indicator significantly affected the interaction between age and prematurity. We consider that it is crucial to expand the knowledge we have about the neurocognitive development of premature infants both in specific cognitive domains and in age ranges so that the information obtained helps to predict the probability of presenting cognitive alterations from early stages and, therefore, to implement intervention strategies and programs based on scientific evidence and complemented in their design by clinical experience, empirical and theoretical knowledge of the different professionals involved in infant cognitive intervention.

Beans are the most widely used protein source in the world and their productivity is directly linked to nitrogen (N). The short crop cycle imposes the need for fast methodologies for N quantification. In this work, we evaluated the performance of four machine learning algorithms in nitrogen prediction using NIR spectroscopy. Increasing doses of nitrogen were applied to the plants and leaf reflectance was collected. Weka software was used to test the algorithms. The selection of the most effective spectral zones was made with the VIP. Considering predictions with the whole NIR, the best results were achieved with RF (R2 = 0,84 and RMSE = 2,69 g kg-1) and KNN (R2 = 0,77 and RMSE = 3,86 g kg-1). The intervals of 700-740 nm and 983-995 nm were considered the most important for the study of N. More efficient predictions were verified when only spectral regions screened by VIP were included, increasing the accuracy of the RF, KNN and M5 models by 6%, 4% and 8%, respectively. The efficiency of N prediction based on NIR reflectance combined with machine learning was verified. This approach can optimize the management of nitrogen fertilization, serving as an important tool in precision agriculture.

Melon (Cucumis melo L.) a member of family Cucurbitaceae is extensively cultivated for its fleshy fruits. Based on the specific agro-climatic zones of cultivation as well as concerning the regional preferences, melon displays significant variability phenotypic and biochemical attributes. Below, an effort is put forth to considerably evaluate the scope of achievements while in the growth as well as the enactment of melon breeding programs by employing the newest solutions. Melon breeding has achieved critical milestones throughout the previous century, and we hope this trend will go on to persist down the road. However, studies have to determine new genetic information for genes associated with the challenges imposed by climate change. The identification of valuable hereditary and also metabolic variability in the form of landraces and melon wild relatives will be useful for harvest diversification and also for the broadening of the cultivated melon genetic base. Whereas, considerable information on genomics, and melon metabolomics, is beneficial for dissecting the basis of the inheritance of important traits and their impact on the former characteristics. Overall, we hope the manuscript is going to serve as a crucial resource for the melon breeders.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

Data regarding the pandemic's impact on tilapia culture remain limited, but it is known that there was a significant decline in production and marketing since 2020. The post-pandemic challenges confronting tilapia farming necessitate prompt solutions, encompassing the management of bacterial infections and the adoption of more advanced technologies by small-scale producers in developing nations. Probiotics, acknowledged as a viable alternative, are presently extensively employed in tilapia aquaculture. Multiple studies have suggested that the application of diverse probiotics in tilapia culture has yielded favorable outcomes. Nonetheless, only a limited number of studies have employed statistical methods to evaluate such findings. To address this gap, a regression analysis was carried out to investigate the existence of a linear relationship between the probiotic dosage added to the feed and two key dependent variables: the specific growth rate (SGR) and the feed conversion ratio (FCR). Additionally, a hierarchical regression analysis was undertaken to ascertain the extent to which the variance observed in these responses could be explained by the variable "probiotic dosage in feed," after accounting for covariates such as initial weight, test duration, water temperature, and number of replicate tanks. Finally, two Pearson correlation matrices were constructed since different studies were included for the SGR and FCR analyses.

The highly adaptable parasite Trypanosoma cruzi undergoes complex developmental stages to exploit host organisms effectively. Each stage involves the expression of specific proteins and precise intracellular structural organization. These morphological changes depend on key structures that control intracellular components’ growth and redistribution. In trypanosomatids, the flagellar attachment zone (FAZ) connects the flagellum to the cell body and plays a pivotal role in cell expansion and structural rearrangement. While FAZ proteins are well-studied in other trypanosomatids, there is limited knowledge about specific components, organization, and function in T. cruzi. This study employed the CRISPR/Cas9 system to label endogenous genes and conduct deletions to characterize FAZ-specific proteins during epimastigote cell division and metacyclogenesis. In T. cruzi, these proteins exhibited distinct organization compared to counterparts in T. brucei. TcGP72 is anchored to the flagellar membrane, while TcFLA-1BP is anchored to the membrane lining the cell body. We identified unique features in the organization and function of the FAZ in T. cruzi compared to other trypanosomatids. Deleting these proteins had varying effects on intracellular structures, cytokinesis, and metacyclogenesis. This study reveals specific variations that directly impact the success of cell division and differentiation of this parasite.

Aerobic exercise training (AET) has been used in the management of heart disease. AET may, totally or partially, restore the activity and/or expression of proteins that regulate calcium (Ca2+) handling, optimize intracellular Ca2+ flow, and attenuate cardiac functional impairment in failing hearts. However, the literature presents conflicting data regarding the effects of AET on Ca2+ transit and cardiac function in rats with heart failure resulting from aortic stenosis. The objective of this study was to evaluate the effects of AET on calcium handling and cardiac function in rats with heart failure due to aortic stenosis. Wistar rats were distributed into two groups: control (Sham; n= 61) and aortic stenosis (AoS; n= 44). After 18 weeks, the groups were redistributed into: non-exposed to exercise training (Sham, n = 28 and AoS, n = 22) and trained (Sham-ET, n = 33 and AoS-ET, n = 22) for 10 weeks. Treadmill exercise training was performed with a velocity equivalent to the lactate threshold. Echocardiogram, isolated papillary muscle, and isolated cardiomyocyte analyzed cardiac function. During isolated papillary muscle assay and isolated cardimyocyte was evaluated Ca2+. The expression of regulatory proteins of diastolic Ca2+ was analyzed via Western Blot. AET attenuated the diastolic dysfunction and benefited the systolic function. AoS-ET animals presented better response to post-rest contraction, and SERCA2a and L-type Ca2+ channels blocked than the AoS. Furthermore, AET was able to improve aspects of the mechanical function and the responsiveness of the myofilaments to the Ca2+ of the AoS-ET animals. AoS animals presented alteration in the protein expression of the SERCA2a and NCX, and AET restored SERCA2a and NCX levels near normal values. Therefore, AET increased SERCA2a activity, improved the cellular Ca2+ influx mechanism, and increased myofilament responsiveness to Ca2+, attenuating cardiac dysfunction at cellular, tissue, and chamber levels in animals with aortic stenosis and heart failure.

The aim of this study was to explore the perceived impact of artificial intelligence (AI) on radiographers’ activities and profession in Switzerland. A survey conducted in the UK, translated into French and German, was disseminated through professional bodies and social media. The participants were Swiss radiographers (clinical/educators/ researchers/students) and physicians working within the medical imaging profession (radiology/nuclear medicine/radiation-oncology). The survey covered five sections: demographics, AI-knowledge, skills, confidence, perceptions about the AI impact. Descriptive, association statistics and qualitative thematic analysis were conducted. A total of 242 responses were collected (89% radiographers; 11% physicians). AI is being used by 43% of participants in clinical practice, but 63.8% of them did not feel confident with AI terminology. Participants viewed AI as an opportunity (57.2%), while 18.5% considered it as a threat. The opportunities were associated with streamlining repetitive tasks, minimizing errors, increasing time towards patient-centred care, research, and patient safety. The significant threats identified were reduction on work positions (22.6%), decrease of the radiographers’ expertise level due to automation bias (16.4%). Participants (68.3%) did not feel well trained/prepared to implement AI in their practice, highlighting the non-availability of specific training (87.6%). 93% of the participants mentioned that AI education should be included at undergraduate education program. Although most participants perceive AI as an opportunity, this study identified areas for improvement including lack of knowledge, educational supports/training, and confidence in radiographers. Customised training needs to be implemented to improve clinical practice and understanding of how AI can benefit radiographers.

In the recent years, tubular nanostructures have been related with immense advances in various fields of science and technology. Considerable research efforts have been centered on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the developing of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N), have received much research attention. In the present work, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride and thallium nitride nanotubes were numerically evaluated using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young´s and shear moduli, and Poisson´s ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs.

Atrial fibrillation (AF) is a cardiac arrhythmia caused by electrophysiological anomalies in the atrial tissue, tissue degradation, structural abnormalities, and comorbidities. A direct relation exists between AF and altered mitochondrial activity resulting from membrane potential loss, contractile dysfunction, or decreased ATP levels. This review aimed to elucidate the role of mitochondrial oxidative mechanisms in AF pathophysiology, the impact of mitochondrial oxidative stress on AF initiation and perpetuation, and current therapies. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews. PubMed, Excerpta Medica Database, and Scopus were explored until June 2023 using "MESH terms." Bibliographic references from relevant papers were also included. Oxidative stress is an imbalance that causes cellular damage from excessive oxidation, resulting in conditions such as AF. An imbalance in reactive oxygen species production and elimination can cause mitochondrial damage, cellular apoptosis, and cardiovascular diseases. Oxidative stress and inflammation are intrinsically linked, and inflammatory pathways are highly correlated with the occurrence of AF. AF is an intricate cardiac condition that requires innovative therapeutic approaches. The involvement of mitochondrial oxidative stress in the pathophysiology of AF introduces novel strategies for clinical treatment.

The architectural configuration of the space plays a crucial role in the acoustics of Neonatal Intensive Care Units (NICUs). The design of the environment, the materials used in construction, and the organisation of noise sources within the room significantly influence the noise levels present in these critical areas. For this research, noise levels found in two hospitals, with different architectural configurations and sizes but similar construction materials, have been analyzed. Data were recorded at 1-second intervals over a period of more than 24 hours. The data collected in these hospitals confirm the magnitude of the noise problem in NICUs, highlighting the urgent need to address it effectively to ensure an appropriate and safe environment for the recovery of neonates. Good architectural planning can help mitigate noise, while poor configuration can exacerbate acoustic problems, negatively affecting both patients and healthcare staff. It is crucial to involve architects, acoustic engineers, and healthcare staff in the design and renovation of NICUs to create spaces that not only meet medical needs but also consider the auditory well-being of neonates.

Sporothrix brasiliensis is the most pathogenic species, responsible for the Brazilian cat-transmitted sporotrichosis hyperendemics. In this scenario, investigation of pathogen-host interaction can provide relevant information for future treatment strategies. To this end, the invertebrate Galleria mellonella has proven to be a suitable alternative to evaluate the virulence of pathogenic fungi since the insect immune system is similar to the mammalian innate immune response. The aim of this work was to investigate phenotypic and molecular aspects of the immune response of G. mellonella throughout the S. brasiliensis infection. Hemocyte density and the evolution of the fungal load were evaluated. In parallel, RT- qPCR expression analysis of genes encoding antimicrobial peptides (Gallerimycin and Galiomycin) and stress management genes (C7 Contig 15362 and C8 Contig 1910) was conducted. Fungal load and hemocyte densities were proportionally increasing simultaneously to the deleterious morphological events and larvae mortality. Gallerimycin, C7 Contig 15362, and C8 Contig 19101 genes were positively regulated (p<0.05) at distinct moments of S. brasiliensis infection, characterizing a time-dependent and alternately modulated profile. Galiomycin gene expression remained unchanged. Our results contribute to the future proposal of potential alternative pathways to treat and, consequently, control S. brasiliensis zoonosis, a major public Health in Latin America.

Developing a low-cost wireless energy meter with power quality measurement for smart grid applications represents a significant advancement in efficient and accurate electrical energy monitoring.In increasingly complex and interconnected electrical systems, this device is essential in various applications, such as smart grids, enabling real-time energy usage monitoring. In such a context, smart meters expand the possibilities for sustainable and efficient energy use and promote better utilization of energy sources, especially non-renewable ones. According to the 2020 International Energy Agency (IEA) research, non-renewable energy sources represent 65% of the global total. The smart meter developed in this work is built based on the ESP32 microcontroller and easily accessible components, using a user-friendly development platform that offers a cost-effective solution while ensuring reliable performance. The main objective of the smart meter development was to enhance the software and simplify the hardware. Unlike traditional meters that perform electrical parameter calculations using complex hardware circuits, this project performed the calculations directly on the microcontroller. This approach reduced the complexity of the hardware, simplifying the meter’s design. With the high-performance processing capability of the microcontroller, efficient and accurate calculations of electrical parameters were achieved without the need for additional circuits. This software-driven approach with simplified hardware brought benefits such as reduced production costs, lower energy consumption, and increased meter development and updates flexibility. Furthermore, the integrated wireless connectivity in the microcontroller enables the transmission of collected data to remote monitoring systems for later analysis. The developed smart meter offers cost, energy efficiency, and flexibility benefits. It represents an innovative, efficient, and versatile solution for smart grid applications.

This work presents a multi-start algorithm for solving the capacitated vehicle routing problem with two-dimensional loading constraints (2L-CVRP) allowing for the rotation of goods. Researches dedicated to graph theory and symmetry considered the vehicle routing problem as a classical application. This problem has complex aspects that stimulate the use of advanced algorithms and symmetry in graphs. The use of graph modeling of the 2L-CVRP problem by undirected graph allowed the high performance of the algorithm. The developed algorithm is based on metaheuristics such as the Constructive Genetic Algorithm (CGA), to construct promising initial solutions; a Tabu Search (TS), to improve the initial solutions on the routing problem; and a Large Neighborhood Search (LNS), for the loading subproblem. Although each one of these algorithms allowed to solve parts of the 2L-CVRP, the combination of these three algorithms to solve this problem was unprecedented in the scientific literature. In our approach, a parallel mechanism for checking the loading feasibility of routes was implemented using multi-threading programming to improve the performance. Additionally, memory structures, like hash-tables, were implemented to save time by storing and querying previously evaluated results for the loading feasibility of routes. For benchmarks, tests were done on well-known instances available in the literature. The results proved that the framework matched or outperformed most of the previous approaches. As the main contribution, this work brings higher quality solutions for large-size instances of the pure CVRP. This paper involves themes related to the symmetry journal, mainly complex algorithms, graphs, search strategies, complexity, graph modeling, and genetic algorithms. In addition, the paper especially focuses on topic-related aspects of special interest of the community involved in symmetry studies, such as, graph algorithms and graph theory.

Artificial Intelligence (AI) models are expected to have a great impact in the manufacturing industry, optimizing time and resource cost by enabling applications such as predictive maintenance (PM) of production machines. A necessary condition for this is the availability of high quality data collected as close as possible to the process in question. With the advent of 5G equipped multi sensor platforms (MSPs), high sampling rate data can be collected and transmitted for processing in real time. This poses a data security challenge, since this data may give valuable insight into confidential business information of companies. Federated learning (FL) enables the training of AI models with data from multiple sources without it leaving the shop floor, by utilizing distributed computing resources available on premise. This paper introduces an architecture of FL based on data collected from 5G MSPs for enabling PM in industrial environments and discusses its potential benefits and challenges.

Hydrogels are water-absorbing polymers that can hydrate forage plants in the soil. The objec-tive was to evaluate the replacement of synthetic hydrogels derived from petroleum by biode-gradable hydrogels in Mombaça grass pastures (Megathyrsus maximum). The experimental treat-ments consisted of: No hydrogel (NH); Synthetic commercial hydrogel (CH), made from a syn-thetic polyacrylamide product; and Biodegradable test hydrogel (TH), obtained from cashew gum (Anacardium occidentale). The experimental design was randomized blocks with five replica-tions and three treatments. Morphogenesis, production, chemical and mineral composition of the Mombaça grass pasture were assessed. The data was subjected to analysis of variance and mean comparison by the Snott-Knott test at 5% probability. Leaf elongation rate was 42.3 mm day-1 in the TH treatment, which was higher (P<0.05) than NH (35.0 mm day-1). Green leaf mass yield was higher in TH in comparison to NH and CH. On the other hand, there was no effect of hydration on chemical composition. The mineral composition of Mombaça grass showed more Zn when TH was used. It can be concluded that biodegradable hydrogels can replace synthetic commercial hydrogels in pastures.

Circular RNAs (circRNAs) are single-stranded RNA molecules often circularized by backsplicing. Growing evidence implicates circRNAs in the underlying mechanisms of various diseases, such as Alzheimer's and Parkinson's disease (PD) - the first and second most prevalent neurodegenerative disorders. Several circRNAs are associated with brain damage, including circSNCA, circHIPK2, circHIPK3, and circSLC8A1. Gain-of-function and loss-of-function studies on circRNAs have shed light on their roles in the pathobiology of various diseases. Gain-of-function approaches typically employ viral or non-viral vectors that hyperexpress RNA sequences capable of circularizing to form the specific circRNA under investigation. In contrast, loss-of-function studies utilize CRISPR/Cas systems, antisense oligonucleotides (ASOs), or RNAi techniques to knockdown the target circRNA. Given that aberrantly expressed circRNAs have been associated with brain pathologies, a critical question arises: could circRNAs serve as viable targets for neuroprotective treatments? Translating any oligonucleotide-based therapy, including those targeting circRNAs, involves developing adequate brain delivery systems, minimizing off-target effects, and addressing the high costs of treatment. Nonetheless, RNAi-based FDA-approved drugs have entered the market, and circRNAs have attracted significant attention and investment from major pharmaceutical companies. Spanning from bench to bedside, circRNAs present a vast opportunity in biotechnology for oligonucleotide-based therapies designed to slow or even halt the progression of neurodegenerative diseases.

Artisanal cheeses made with raw milk are highly appreciated products in Brazil. Most of these cheeses are produced in small properties across different production regions in the country, many of which have been granted a protected designation of origin. The most prominent state that manufactures these products is Minas Gerais, but production is also gaining strength in other Brazilian states. This text presents an overview of the many types of artisanal cheeses produced in the country, grouped by geographical regions, and reviews the current challenges faced by producers and government considering the safety of these cheeses.

Background: Manoeuvres esbarrada and volta sobre patas are fundamental movements in equestrian activities, yet their kinematics remain largely unexplored. Objectives: This observational study aimed to kinematically describe the movements of esbarrada and volta sobre patas in Criollo breed horses. Methods: Kinematic analysis was conducted on 31 Criollo horses executing esbarrada and volta sobre patas manoeuvres. Results: The esbarrada maneuver covered a distance of 4.28 ± 0.99m in 1.15 ± 0.11s at a velocity of 3.77 ± 0.55m/s. Angular kinematic variables revealed specific joint angles during the maneuver. In volta sobre patas, significant differences were found in spin duration and thoracic limb suspension between the first and second spins. Conclusions: Volta sobre patas demonstrated prolonged spinning duration and increased thoracic limb suspension in the second spin. Additionally, static conformation did not correlate with limb protraction angles during esbarrada.

Injuries of repetitive efforts constitute one of the prime causes of absenteeism in the workplace, have bear a considerable cost for the public health system and can cast doubt on the sustainability of a company. The objective of this paper is to build, in the researchers, the needed knowledge to choose a set of relevant scientific articles about repetitive strain injuries in the poultry meat industry, aiming identify characteristics in those scientific publications that have the potential to contribute on the topic of this paper. The research is characterized as exploratory-descriptive, draws on primary and secondary data sources. The study involves the application of a method for selection and analysis of the selected articles. To this end, the method utilized was the Knowledge Development Process – Constructivist (Proknow-C) as theoretical intervention instrument. Within the process development, it was obtained a portfolio of 16 articles aligned to the research and scientifically recognized with the main periodicals, papers, authors and keywords. The ProKnow-C process allowed identify opportunities in the literature about injuries in the poultry meat industry and showed opportunities for research future. This paper, under the constructivist perspective, presents a structured process to build, in the researcher, the necessary knowledge to identification, selection and analysis of relevant scientific articles relating to research context and, for these articles, find prominences and opportunities for a research theme without similar publications.

Abstract: (1) Background: tuberculosis presents an epidemiological trend towards inequality, especially among people in social exclusion and situations of vulnerability. To analyze territories where there is a concentration of people diagnosed with tuberculosis, in a street situation, and who make chronic use of alcohol, tobacco, and illicit drugs. We will also analyze trends in this health condition in southern Brazil; (2) Methods: Ecological study, developed in the 399 municipalities of Paraná, Southern Brazil, with all tuberculosis cases in the homeless population registered in the Information System of Notifiable Diseases between 2014 to 2018. For data analysis, we used descriptive statistics, for the time series, the Prais-Winsten autoregression method, whereas for spatial analysis, we used the Getis-Ord Gi technique*; (3) Results: in total, 560 cases were reported. We found a predominance of alcohol, smoking, and illicit drugs users, with an increasing trend in the state and clusters of spatial risk in the East health macro-region; (4) Conclusions: We observed territories with critical levels of highly vulnerable people who use psychoactive substances and are in a street situation. The results highlight the importance of incorporating public policies of social protection to these individuals and resolutive health services that receive and assist in eradicating TB.

The activity of prioritizing software requirements should be done as efficiently as possible. Selecting the most stable requirements for the most important customers for the development company can be a positive factor when we consider that the available resource does not always encompass the implementation of all requirements. Quantitative methods for reaching software prioritization in releases are many in the field of Search-Based Software Engineering (SBSE). However, we show that it is possible to use qualitative Verbal Decision Analysis (VDA) methods to solve this same type of problem. Moreover, we will use the ZAPROS III-i methods to prioritize requirements considering the opinion of the decision-maker, who will participate in this process. Finally, the results obtained in the VDA structured methods were quite satisfactory when compared to the methods using SBSE. A comparison of results between quantitative and qualitative methods will be made and discussed later.

Sour waters are one of the main aqueous byproducts generated during petroleum refining and require processing in Sour Water Treatment Units (SWTUs) to remove contaminants such as H₂S and NH₃ in compliance with environmental legislations. Therefore, monitoring the composition of SWTU effluents, including acid gas, ammoniacal gas, and treated water, is essential. This study aims to present an AI (artificial intelligence) hybrid-based methodology to develop soft sensors capable of real-time prediction of H₂S and NH₃ mass fractions in the effluents of SWTUs and validate them using real data from industrial units. Initially, a new database based on the dynamic simulation of a two stripping columns SWTU phenomenological model, developed in Aspen Plus Dynamics® V10, was generated, aiming at non-faulty runs, unlike our previous work [1]. Ensemble methods (Decision Trees), such as Gradient Boosting and Random Forest, and Support Vector Machines were compared for soft sensor creation using these simulated data. The best outcome was the development of six soft sensors based on Random Forest with R² greater than 0.87, MAE less than 0.12, MSE less than 0.17, and RMSE less than 0.41. Variable importance analysis revealed that the temperature of the second stage of Column 1 significantly influences the thermodynamic equilibrium of H₂S and NH₃ separation from sour waters, being critical for five of the six soft sensors. After this initial stage using data from the phenomenological model, data from an industrial-scale SWTU were used to develop real soft sensors. The results proved the effectiveness of the conjugated use of physical model and industrial data approach in the development of soft sensor for two-column SWTUs.

This paper, based on the "Unified Theory of Forces," rigorously proves the formula of de Broglie's wave function. This helps us better understand the following important issues: 1) Theoretically prove and understand the essence of de Broglie's wave function; 2) Prove that when the particle's momentum P is determined, the greater the mass of the particle, the more concentrated its wave function distribution, and the weaker the interference effect; 3) Correct the spatial distribution of the wave function of free particles, proving that the wave function of free particles is strictly constrained within a finite spatial range, which is consistent with the facts we observe.

The objective of this study was to evaluate the effect of the addition of a phytogenic compounds blend (PHA) containing hydrolyzable tannins, carvacrol and cinnamaldehyde oil in the mineral salt or energy supplement on the rumen microbiota and nitrogen metabolism of grazing Nellore cattle. Eight castrated Nellore steers were distributed in a double Latin square 4 × 4 design, with a 2 × 2 factorial arrangement (two type supplements and the addition or not of PHA) as follows: energy supplement without PHA addition (EW); energy supplement with PHA addition (EPHA); mineral supplement without the addition of PHA (MW); and mineral supplement with PHA addition (MPHA). Steers that received supplements with PHA have a lower ruminal proportion of Valerate (with PHA 1.06%; without PHA 1.15%), a lower ruminal abundance of Verrucomicrobia and a tendency for lower DM digestibility (with PHA 62.8%; without PHA 64.8%). Energy supplements allowed higher ammonia concentrations (+2.28 mg of NH3-N/dL), increased the propionate proportion (+0.29% of total VFA), and showed a tendency to have a higher abundance of Bacteroidetes and a lower abundance of Firmicutes in the rumen. The PHA addition in the supplement did not improve the use of nitrogen in grazing cattle, but negatively affected the diet digestibility.

Considering the various problems caused by infiltration in civil construction, this study aimed to identify the most appropriate waterproofing methods for different types of surfaces. A study was conducted on the mechanisms of water infiltration on surfaces and the waterproofing methods available on the market, focusing on asphalt blankets, in addition to a literature review highlighting state-of-the-art on this topic. A case study was also conducted in residence in Nova Lima, Brazil, analyzing different waterproofing techniques, including their characteristics and stages. Among the conclusions, it is highlighted that the implementation of adequate project, installation, inspection, and maintenance techniques can significantly reduce the waterproofing failure rate and repair costs and that the excellent choice of materials, along with the skill of the labor force in the application, is fundamental to guarantee the adequate performance of these materials in buildings.

Technological innovations and the expansion of Internet access have produced significant changes in the configurations of organizations and, consequently, in the relationships between employees and employers. This new scenario generates the need for greater monitoring in the workplace in order to control inappropriate behavior or situations that may generate misfortunes. Two important problems faced are the dissemination of hate through networks and data leakage that can have social, psychological, and financial impacts. Thus, monitoring tools can be incorporated to assist in surveillance, and thus ensure the achievement of organizational objectives. This paper presents a workplace computer monitoring solution that integrates Spyware techniques, and text sentiment classification, along with a distributed microservices architecture, which aims to collect a range of information and generate alerts to managers regarding hate speech and vulnerabilities. Preliminary tests have been conducted to evaluate the performance of Spyware integrated with prediction models.

Ménière's disease (MD) has an unclear cause. The microvascular dysregulation of the inner ear has been increasingly pointed as a potential contributor. This study investigates the prevalence of cardiovascular risk factors (CVRFs) in MD patients compared to those with posterior circulation cerebral infarction (POCI). CVRFs like hypertension, diabetes, dyslipidemia, obesity, coronary heart disease, and smoking were assessed in both MD and POCI patients. Brain MRI identified POCI etiology as "small vessel occlusion" (SVO) or "other etiology" (OE). The study included 64 MD and 84 POCI patients. Compared to MD, POCI OE showed a higher prevalence of CVRFs across various age groups, including hypertension, diabetes, dyslipidemia, and smoking. Notably, the odds of having POCI OE were significantly higher for individuals with hypertension and smoking. On the other hand, POCI SVO showed similar prevalence of CVRFs compared to MD. This study reveals no significant difference in CVRF prevalence between MD and smaller vessel POCI. However, a clear distinction emerges when comparing MD to POCI with involvement of larger blood vessels. Further research is needed to confirm these findings and explore potential shared risk factors between POCI (SVO) and MD.

Fires in houses are inevitable and they cause loss of life and major repair costs for the damage structure and contents. There is a clear need to prevent its ignition and spread to adjacent areas. This article presents the steps taken, namely: contacts, data collection, tests, analysis and conclusions regarding the accident resulting from the outbreak and spread of a fire, on December 25, 2020, in a traditional Portuguese house in Arganil, Portugal. The owners and the court requested to carry out an expert opinion by a person with specialized technical-scientific knowledge, which led to this work as an expert. the work consists of carrying out observations and data analysis. Then, the observed and analysed data were laboratory tested in order to consistently identify characteristics that lead to the ignition and propagation of the fire. This work identified construction problems, materials used and heat sources that are responsible for the accident. The conclusions may be used to avoid future incidents or accidents with houses of same construction type.

(1) Background: This study evaluated the spatial position and anatomical characteristics related to impacted third molars by map-reading strategy using cone beam computed tomography (CBCT). (2) Methods: To determine the positioning of impacted third molars on CBCT it was used Winter's and Pell &amp; Gregory's classifications, and the presence of external root resorption in mandibular second molars were based on Herman´s classification. The relationship between the mandibular third molar root apex and the mandibular canal was also analyzed. Fisher’s exact test was used to comparative statistical analysis. The significance level considered was 5%. (3) Results: The results showed that according to Winter's classification, 48.06 % of impacted teeth were in the mesioangular position. Using Pell &amp; Gregory's classification, 43.22% of the impacted molars were in the position B and C, and 54.2% of the teeth were class II. 69.7% of teeth showed an absence of contact between the root apex and the mandibular canal and there was no occurrence of external root resorption in the distal of second molar in 88.7%. (4) Conclusions: The map-reading strategy using CBCT scans for anatomical positions and characteristics of impacted third molars increases professional confidence and establishes a parameter of quality and safety in the surgical procedure for the patient.

(1) Background: Obesity and its comorbidities can cause burdens and limitations. Bariatric surgery (BS) is indicated as a safe procedure to reduce body mass and improve present comorbidities. Yet, several complications were reported, like vitamin D [25(OH)D] deficiency. We evaluated if 25(OH)D serum levels relate to clinical characteristics, symptoms, or habits in women after their BS and whether the vitamin D receptor (VDR) gene's TaqI and FokI polymorphisms affected 25(OH)D levels and the total body bone mineral density (TBBMD). (2) Methods: This cohort cross-sectional comparative analytical prospective study consisted of 27 women, 61.6 ± 5.0 years, submitted to BS one year prior at a public reference hospital, DF-Brazil. All participants were asked to follow the physical and dietary activity recommendations and received vitamin D3 supplements. Their anthropometric, biochemical, and immunological measurements and blood samples were obtained. (3) Results: 73.3% of participants had low 25(OH)D levels, and their levels correlated positively with TBBMD and negatively with systolic pressure. VDR TaqI did not affect 25(OH)D levels, whereas VDR FokI's allele f presence correlated to a median rise in 25(OH)D levels. Neither polymorphism correlated to TBBMD. (4) Conclusions: 25(OH)D levels were positively correlated with TBBMD, negatively with systolic blood pressure, and were higher in those with the VDR FokI allele f.

This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.

Abstract: Building Information Modelling (BIM) methodology has been empowering the quality of the construction activity in all sectors: multidisciplinary designs development; construction planning and monitoring; building management and maintenance. A BIM environment aggre-gates several disciplines and different professional skillsets and in order to control and improve the quality of a BIM project, a BIM manager is required. The BIM manager has the responsibility to coordinate all tasks involved in a building design and associated activities usually workout over the project documents. This professional can access to the distinct discipline models, located in a shared platform, and request for amendments if inconsistencies are detected. The topic of the present study is illustrated with three building cases were distinct specific projects, disciplines and tasks were elaborated: collaboration between disciplines (architecture, structures and con-struction); structural analyses and reinforcement details; quantity take-off of materials and cost estimation; construction scheduling and simulation. Although there are still limitations in the implementation of BIM methodology in all sectors and stages, within the construction industry, BIM has been bringing an important improvement in the quality of a building design, reflected in the quality of the final product. The present study put in evidence the BIM manager role in pro-jects that aggregates several disciplines and experts, bringing an important contribution in the quality of a building design. BIM methodology is a current demand in the construction industry supported on advanced technology and in an adequate management of projects.

The integration of the Internet of Things (IoT) and Distributed Computer Systems (DCS) is transforming business models across industries. IoT devices enable real-time monitoring of equipment and processes, reducing downtime and enhancing efficiency. In the case, manufacturing companies use IoT sensors to monitor machinery, predict failures, and schedule maintenance. Also, automation via IoT, reduces manual intervention, resulting in boosted productivity in smart factories and automated supply chains. IoT devices generate thus vast amounts of data, which businesses analyze to gain insights into customer behavior, operational inefficiencies, and market trends. In turn, distributed computer systems process this data, providing actionable insights and enabling advanced analytics and machine learning for future trend predictions. While, IoT facilitates personalized products and services by collecting data on customer preferences and usage patterns, enhancing satisfaction and loyalty, IoT devices support new customer interactions, like wearable health devices, and enable subscription-based and pay-per-use models in transportation and utilities. Conversely, real-time monitoring enhances security, as distributed systems quickly respond to threats, ensuring operational safety. It also aids regulatory compliance by providing accurate operational data. In this way, this study, through a Bibliometric Literature Review (LRSB) of 91 screened pieces of literature, aims at ascertaining to what extent the aforementioned capacities enhance business models. The study concludes that those systems leverage businesses, promoting competitive edge, continuous innovation, and adaptability to market dynamics. A review of 91 academic documents from the Scopus database highlights these impacts.

The increasing adoption of student-centred learning environs by the institutions of higher education in business, has led to new mechanisms and methodologies such as the Simulation-Based Learning (SBL), Problem-Based Learning (PBL) and Challenge-Based Learning (CBL). Literature has shown evidence of raising interest in these methodologies towards a more experiential paradigm with regard to upcoming events from the surrounding real-world context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the integration and application of these innovative and collaborative methodologies in higher education. It aimed to identify its relevant advantages, challenges, and consequences for the future of business education. Bibliographic databases were searched for documents published up to May 2024 to categorize key topics discussed in the literature on SBL, PBL and CBL. The review process identified 89 empirical and non-empirical papers on SBL, PBL and CBL, business related paperwork, which resulted from the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. PRISMA is a framework with evidence-based data designed to help authors perform a systematic literature review. Data analysis revealed diverse subthemes for those methodologies uses in business higher education institutions. The research questions “What are the advantages, challenges and implications of SBL, PBL and CBL altogether, in the training of business students?” guided the study. The central output of the research is the discovery of the varying uses of SBL, PBL and CBL overall, to cope with diverse demands arising within environmental context. Future research directions are suggested.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

Since people spend most of their time in indoor environments, the objective of this work was to study indoor air quality perception and its effects on users’ thermal comfort. Based on previous data from a building with a central air-conditioning system and two mixed-mode buildings located in the humid subtropical climate of Florianópolis, southern Brazil, statistical analyses were performed. Each user subjective answer obtained through a questionnaire was combined with the corresponding environmental conditions – measured using microclimate stations, a portable thermo-anemometer and a CO2 analyser. Results showed that improvement in air quality was associated with the reduction of air temperature and humidity ratio. Also, there was a significant influence of thermal, air movement and humidity sensation and acceptability of air quality perception. Users felt more satisfied or neutral with air quality for being in thermal comfort, and not because of the CO2 level – which means that air quality perception is influenced by factors other than CO2. This study recommends the implementation of an air exchange device in split air-conditioners with air recirculation used in mixed-mode buildings in Brazil. It is important to provide suitable indoor ventilation to reduce pollutants concentration, ensure good air quality and prevent respiratory diseases.

A two-factor account has been proposed as an explanatory model for the formation and maintenance of delusions. The first factor refers to a neurocognitive process leading to a significant change in subjective experience; the second factor has been regarded as a failure in hypothesis evaluation characterized as an impairment of metacognitive ability. This study was focused on the assessment of metacognition in patients with schizophrenia. The aims of the study were to measure the overconfidence in metacognitive judgments through the prediction of word list recall; and to analyze the correlation between basic neurocognition: memory and executive function and metacognition through a metamemory test and the severity of psychotic symptoms. Method: 51 participants with diagnosis the of Schizophrenia were evaluated. The PANNS was used to assess the severity of psychiatric symptoms and the subtest of Metamemory included in the BANFE Battery was used to evaluate overconfidence and underestimations errors, intrusion and perseverative response, and total volume of recall. Results. The strongest correlation are observed between overconfidence errors and the positive factor of the PANSS (r= 0.774, p

(1) Background: The aim of the present study was to evaluate the effect of different types of warm-ups on the strength and skin temperature of Paralympic powerlifting athletes; (2) Methods: The participants were 15 male Paralympic powerlifting athletes. It was analyzed the effects of three different types of warm-up (without warm-up (WW), traditional warm-up (TW), or stretching warm-up (SW)) on static and dynamic strength tests as well as in the skin temperature, which was monitored by thermal imaging; (3) Results: show no differences in the dynamic and static indicators of the force in relation to the different types of warm-up. No significant differences were found in relation to the Peak Torque (p = 0.055, F=4.560, η2p= 0.246 medium effect), and 1-Repetition Maximum (p = 0.139, F=3.191, η2p = 0.186, medium effect) between the different types of warm-up. In the thermographic analysis, there was a significant difference only in the Pectoral muscle clavicular portion between the TW (33.04 ± 0.71ºC) and the WW (32.51 ± 0.74ºC) (p = 0.038). The TW method also presented slightly higher values than the SW and WW in the Pectoral Muscles Sternal portion and in the Deltoid anterior portion, but with p-value &gt; 0.05; (4) Conclusions: that the types of warm-up studied do not seem to interfere with the performance of Paralympic Powerlifting athletes. However, the thermal images showed that traditional warm-up best meets the objectives expected for this preparation phase.

Building Information Modelling (BIM) methodology have been optimizing the construction activity in all sectors: multidisciplinary designs development; construction planning and monitoring; building management and maintenance. A BIM environment aggregates several disciplines and different skillsets and in order to control and improve the quality of a BIM project, a BIM manager is required. The BIM manager has the responsibility to coordinate all tasks involved in a building design and associated activities usually workout over the project documents. The professional can access to various discipline models, located in a shared board, and request for amendments if inconsistencies are detected. The present study issue is illustrated with three building cases were distinct specific projects, disciplines and tasks were elaborated: collaboration between disciplines (architecture, structures and construction); structural analyses and reinforcement details; quantity take-off of materials and cost estimation; construction scheduling and simulation. Although there are limitations in the implementation of BIM methodology in all sectors and stages, within the construction industry, BIM have been bringing an important improvement in the quality of a building design, reflected in the quality of the final product. BIM methodology is a current demand in the construction industry supported on advanced technology and in an adequate management of projects, were the BIM manager has an important role.

In the last decades we have experienced great social, cultural, and educational changes, spending more time performing tasks in near vision and less hours in outdoor activities, having more overexposure to digital screens, especially the youngest and increasingly from younger ages. It is common to see cases when performing tasks in near vision the posture or position of the head is not adequate, especially the youngest, being essential to have a correct posture of the head to avoid visual, muscular, or articular problems. We present a procedure to try to control the correct position of the head in real time when performing close-up activities. The aim is to detect the inclination of the head and to know if a bad position is adopted due to a visual problem or simply to inadequate visio-postural habits, warning us of the postural anomaly to correct it.

Music perception in foetuses has been explored under different theoretical paradigms such as habituation, categorical perception, sound preferences and recall. This study investigated the temporal dimension of music perception through the habituation and sensitization paradigm. Foetuses of 41 pregnant women, mean gestational age of 34.7 weeks (±2.4), were observed during ultrasound exams. Foetuses’ reaction to two different tempos (Allegro vs Adagio) and sources (internal vs external) of music stimuli was registered by heart rate variability (HR) and motor response according to the Assessment of Preterm Infants Behaviour scale (APIB) by its factors of movement (MOV) and organization (ORG). A folkloric lullaby, sung and played live with a stringed instrument by a musician, was presented in three stages that were compared to baseline: 1) slow tempo (Adagio), 2) fast tempo (Allegro); and 3) now sung by mother at slow tempo (Adagio). Exploratory analyses showed that all factors increased from baseline to first stage. HR and ORG varied significantly among stages, with HR being the strongest factor. MOV merely detected change from baseline to first stage. ORG decreased for Allegro but increased for maternal Adagio, while HR decreased to near baseline values. ANOVA-repeated measures with gestational age as covariate showed that all measures were sensitive to first music presentation (Adagio), although only HR and ORG differed among stages. Considering estimated marginal means, adjusted for gestational age, HR presented a sensitization pattern throughout stages, but ORG kept habituating to external source and increased to maternal Adagio, suggesting foetal discrimination by sound source. We conclude that foetuses showed different behavioural and physiological responses to external versus internal sound source and musical tempo. The combined use of a behavioural scale (APIB) and HR in foetuses proved to be a valid multidimensional instrument.

Background This study aimed to examine the acute effects of different pre-ST strategies on muscular performance and blood pressure (BP) responses in recreationally strength-trained women. Methods: Twelve overweight women with normal-to-elevated BP were recruited and performed six exper-imental protocols in a randomized order: 1) control protocol (CC) – BP assessed without exercises performed, 2) strength training (ST), 3) foam rolling warm-up followed by strength training (FR+ST), 4) specific warm-up followed by strength training (SW+ST), 5) aerobic exercise followed by strength training (AE+ST), and 6) stretching exercises followed by strength training (SE+ST). Strength training consisted of three sets at 80% of 10RM with a self-suggested rest interval between sets for bench press, back squat, bench press 45º, front squat, lat pull-down, leg press, shoulder press, and leg extension. Results: All experimental protocol had a lower total training volume, fa-tigue index, and repetitions performance in relation to ST (p

The cultivation of sunflower (Helianthus annuus L.) as a cut flower stands out in floriculture due to its aesthetic beauty and commercial value. Understanding how cut sunflower genotypes adapt to different edaphoclimatic regions and management practices is essential to optimize flower quality and productivity. This study aimed to evaluate the effect of plant density and location on the development, growth, and quality of cut sunflower in tropical and subtropical environments. Plant densities of 10, 20, 30, 40, and 50 plants/m² were evaluated in tropical climate and subtropical climate using a randomized block design in a factorial scheme. Results showed significant differences between locations for plant height, capitulum and stem diameter, final number of leaves, leaf area, leaf area index, phyllochron, and the developmental cycle. Plant density significantly influenced these variables except for plant height and developmental cycle. The interaction between location and plant density was significant only for capitulum diameter and final leaf number. The findings indicate that both planting density and location significantly influence the developmental cycle of cut sunflowers, with lower densities favoring more robust plants at harvest. A density of 30 plants/m² is recommended for efficient space use without significantly compromising floral stem quality. All produced stems are marketable, suggesting that adjusting planting density can optimize production without compromising quality, adapting to specific regional conditions.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions. Python, a versatile programming language, holds vast potential for Sentiment Analysis (SA). Leveraging the Requests and TextBlob libraries, we have crafted a user-friendly code that enables Industrial Engineers (IE) and managers, particularly those who are new to Python, to extract and analyze sentiment efficiently. We aim to provide IE/managers in service companies requiring SA capabilities with a simple yet effective Python solution. While machine learning resources like PyTorch/TensorFlow are commonly utilized in SA, offering pre-built algorithms and tools for training, and implementing machine learning models, we sought to exploit Python's versatility by integrating additional web-scraping libraries. Thus, by using a lexicon-based approach, we intend to deliver an informative and practical article. The code in this article is twofold; firstly, it can be easily adapted by IE/managers possessing basic Python skills; secondly, we aim to inspire junior IE/managers to develop their own customized coding solutions tailored to specific organizational needs.

Background: The last-mile delivery phase, the final stage where goods move from a distribution center to customers, is pivotal but faces significant inefficiencies and high costs due to its complexity. Recent advancements in Edge AI or Edge Intelligence (EI) offer promising solutions to these challenges. Methods: This study explores how AI-driven technologies and real-time data processing, combined with EI, can enhance last-mile delivery operations. A thorough literature review was conducted to assess technological advancements, and a Delphi method was used to systematically and empirically assess the impact of EI solutions on both operational efficiency and customer satisfaction. Results: Although EI technologies offer substantial benefits, EU companies are hesitant to adopt these innovations due to high implementation costs. However, firms that have embraced these technologies report significant improvements, including better route optimization, reduced delivery times, and enhanced service reliability. These findings highlight the need for a culture of innovation and the recruitment of experts with advanced qualifications to drive technological advancement in last-mile logistics. Conclusions: The integration of EI represents a significant step towards more efficient, cost-effective, and customer-focused last-mile delivery solutions. Future research should aim to refine these technologies and explore their long-term impacts on the logistics industry.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

The plague caused by the Yersinia pestis bacterium is primarily a flea-transmitted zoonosis of rodents that can also be conveyed to humans and other mammals. In this work, we analyzed the spatial and temporal distribution of rodents’ populations during active and quiescent periods of the plague in the municipality of Exu, northeastern Brazil. The geospatial analyses had shown that all rodent species occurred through the whole territory of the municipality with different hotspots for the risk of occurrence of the different species. Important fluctuation in the rodent populations was observed with a reduction in the wild rodent fauna following the end of a plague epidemic period, mostly represented by Necromys lasiurus and increase of the commensally species Rattus rattus. A higher abundance of rats might lead to an increased exposure of humans populations, favoring spillovers of plague and other rodent-borne diseases. Our analysis contributed to further highlight the role of the wild rodent species as the amplifier hosts and of the commensally rats (Rattus rattus) as the preserver hosts on the quiescent period on that transmission infection area.

The objective of this study was to determine the chemical composition of sugarcane spirits and commercial cachaças, comparing them with the limits established by national legislation and with studies conducted in previous periods. Previous studies have shown that 50% of the samples of this distillate were above the contaminant limits allowed by national legislation, which was one of the main factors responsible for the low volume of exports. Volatile compounds and contaminants established by current Brazilian legislation were evaluated in 531 samples of commercial sugarcane brandy and cachaça. Among the samples analyzed, approximately 90% met the Brazilian standards of identity and quality. These results suggest that Brazilian producers have faced fewer difficulties related to the use of Good Manufacturing Practices, ensuring good quality during the production process and standardization of these beverages compared to previous studies.

The augmenting commitment in the entrepreneurial learning process, both at academic and industry level, has led to new mechanisms and methodologies. Entrepreneurship literature has shown evidence of raising interest in the problem-based learning (PBL) methodology with regard to upcoming events from the surrounding learning context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the application of PBL throughout distinct entrepreneurial processes either in higher education, or in industry. It aimed to identify relevant entrepreneurial opportunities for PBL. Bibliographic databases were searched for documents published between 2002 and May 2024 to categorize key topics discussed in the literature on PBL and entrepreneurship. The review process identified 142 empirical and non-empirical papers on entrepreneurship related PBL. Data analysis revealed diverse subthemes for PBL uses in entrepreneurship in both higher education institutions and industry. The research questions “What is the interplay of problem-based learning methodology with entrepreneurship?” guided the study. The central output of the research is the discovery of the varying uses of PBL to cope with diverse events arising within entrepreneurship context. Future research directions are suggested.

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.

Feline sporotrichosis is an endemic disease with high occurrence in Brazil. Itraconazole (ITZ), remains the drug of choice for treating this disease in cats, despite the increasing reports of therapeutic failure. A controlled, randomized clinical trial was performed on 166 naive cats with sporotrichosis to assess the effectiveness and safety of the combination therapy (ITZ+KI) com-pared with ITZ monotherapy. Cats were randomly allocated in two treatment groups: G1 - ITZ 100 mg/cat/day and G2 - ITZ 100mg/cat/day + KI 2.5-20 mg/kg/day. Cats treated in G2 presented 77% more risk of reaching clinical cure (a positive effect) than those treated in G1, even when controlled by negative predictors. The survival curves of the two treatment protocols indicates that clinical cure was achieved faster in G2. An increase in the KI dose was necessary in 28 cats due to persistence of clinical signs. Adverse reactions were equally frequent in both groups and manageable with a temporary drug suspension and/or a hepatoprotective therapy. The combination therapy was associated with a higher cure rate and a shorter treatment time, suggesting that ITZ+KI arises as a better option for treating feline sporotrichosis and should be considered as the first-line treatment in the presence of negative predictors.

In this paper we establish information theoretical bridges between 1) Thermal Heisenberg uncertainties $\Delta x \Delta p$ (at temperature $T$), and 2) LMC structural quantifiers. After having achieved such purpose, we determine to what an extent our bridges can be extended to both the semi classical and classical realms. Also, we find a strict bound relating a special LMC structural quantifier to quantum uncertainties.

The mining industry is known for the intense environmental impacts it triggers, especially when it is developed in an open environment. Pit lakes are formed in depleted deposits and may be promising opportunities for use by society as well as troubling environmental liabilities. While these artificial basins are increasing numerically in many parts of the world, they are still little known researchers in the Environmental Sciences, which makes their environmental management challenging. The main objective of this study was to evaluate the environmental quality of sediments from three deactivated open-pit gold mines, located in the Mara Rosa, Brazil, through chemical, ecotoxicological and genotoxicology analyses. For this purpose, we collected samples in the dry season boom, and subsequently, we analysed metals. In sequence, acute ecotoxicological and a genotoxicology test (comet assay) were developed with Danio rerio fishes, in concentrations of 3.12%; 6.25%; 12.5%; 25%; 50% and 100%, in addition to the control group. The results indicated that the three lakes are environmentally compromised, especially Lago Azul, whose waters and sediments are undergoing an intense process of geological conditioning. Our results did not verify the ecotoxicity of the sediments of any of the lakes, only behavioural alterations in the test organisms exposed to the concentrations of 25%, 50% and 100% of the samples obtained in the Lago Azul. About the sediments, DNA damage at Danio rerio was detected in the three investigated environments, although fishes kept in the water sampled at Lago Azul presented the most extension of DNA damages.

The advances mobile communications has seen in recent years has rendered the radio spectrum a limited and, hence, an expensive resource. Therefore, technologies that support unlicensed access to spectrum are needed. Therefore, the adoption of novel modulation schemes becomes of utmost importance to obtain better spectral-localization and reduce the OOBE (\textit{Out of Band Emission}) inherent to OFDM (\textit{Orthogonal Frequency Division Multiplexing}) and, consequently, mitigating the interference between secondary (\textit{unlicensed}) and primary users. In this scenario, we assess the gain in the bit error probability using f-OFDM (\textit{filtered-OFDM}) in MIMO systems, both used in the 5G RANGE project.

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes.

This article presents the implementation of a model to estimate the future price of commodities in the Brazilian market from time series of short-term technical evaluation. For this, data from two databases were used, one referring to the foreign market (opening values, maximum, minimum, closing, closing adjustment and volume) and the other, from the Brazilian market (the price of the day), considering commodities, sugar, cotton, corn, soybean and wheat. Subsequently, the technical indicators were calculated from the TA-Lib technical analysis library. Pearson’s correlation coefficient was applied, records with low correlation were removed, and then the database was consolidated. From the pre-processed data, Long Short-Term Memory (LSTM) recurrent neural networks were used to perform data prediction at the one and three day interval. These models were evaluated using the mean square error (MSE), obtaining results between 0.00010 and 0.00037 on test data one day ahead, and from 0.00017 to 0.00042 three days ahead. However, based on the results obtained, it was observed that the developed model obtained a promising forecasting performance for all the commodities evaluated. As a main contribution, there is the consolidation of databases that can be used in future scientific research. Furthermore, based on its interpretation, it can assist in decision making regarding the buying and selling of commodities to increase financial gains.

This paper presents the development and implementation of a machine learning model to estimate the future price of commodities in the Brazilian market from technical analysis indicators. For this, two databases were obtained regarding the commodities sugar, cotton, corn, soybean and wheat, which were submitted to the steps of data cleaning, pre-processing and subdivision. From the pre-processed data, recurrent neural networks of the long short-term memory type were used to perform the prediction of data in the interval of 1 and 3 days ahead. These models were evaluated using mean squared error, obtaining an accuracy between 0.00010 and 0.00037 on the test data for 1 day ahead and 0.00015 to 0.00041 for 3 days ahead. However, based on the results obtained, it can be stated that the developed model obtained a good prediction performance for all commodities evaluated.

Among the leading immersive technologies, Augmented Reality is one of the most promising and empowering to support designers in production environments. This research investigates the application of mobile augmented reality, based on the Web, as a mediation tool focused on cognitive activities of reading and understanding of Technical Drawings in the production and assembly for Tailor Made projects of the scenographic industry. In this context, the research presents a method to use the WebAR to improve the reading of technical drawings, seeking efficiency on the visualization of models and the exchange of information between professionals, involved in the processes of design, production and assembly of products, in the scope of scenography. This mediation tool was developed using Web AR platforms, compatible with native libraries (ARCore and ARKit) to ensure, first, compatibility with commonly used devices that workers or businesses can access, and secondly, to leverage hybrid tracking techniques that combine vision and sensors to improve the reliability of augmented reality viewing. The proposed solution adopts multiple tracking and navigation techniques in order to expand Space Skills components to provide greater exploratory freedom to users. The research process took place in the light of the Design Science Research Methodology and the DSR-Model, since it aimed to develop a solution to a practical problem, as well as to produce knowledge from this process. Field experiments were conducted in two real companies, with end users on their respective mobile devices, in order to evaluate usability and behavioral intent, through the Acceptance, Intent and Use of Technology questionnaires; and perceived mental workload, NASA-TLX. The experimental results show that the adoption of this tool reduces the cognitive load in the process of reading technical drawings and project´s understanding. In general, it´s usability and intent to use provide significant levels of satisfaction, being positively accepted by all participants involved in the study.

This work presents a novel compact CMOS potentiostat designed circuit for electrochemical cell. The proposed topology functions as a circuit interface, controlling the polarization of voltage signals at the sensor electrodes and facilitating current measurement during the oxidation-reduction process of a analyzed solution. The potentiostat, designed for CMOS technology, comprises a two-stage amplifier, two current mirror blocks coupled to this amplifier, and a CMOS push-pull output stage. It employs the electrochemical method of cyclic voltammetry, operating within voltage range of ±0.8 V and scan rates of 10mV/s, 25mV/s, 100mV/s and 250 mV/s. The circuit is capable of reading currents ranging from 10 µA to 500 µA. Experimental results were obtained using a potassium ferrocyanide (K3(FeCN)6) redox solution with concentrations of 10, 15 and 20 mmol/L, and their corresponding voltammograms were evaluated. The experimental results from a discrete circuit demonstrate that the proposed potentiostat topology produces outcomes consistent with those of classical topologies presented in the literature and industrial equipment.

The performance of modern wireless communication systems is highly dependent on the adoption of multiple antennas and the associated signal processing. In 5G and 6G networks, beamforming and beam management become challenging tasks due to aspects such as user mobility, increased number of antennas, and the adoption of higher frequencies. Artificial intelligence, and more specifically, machine learning, are efficient tools to reduce the complexity involved in generating beams and the overhead associated with beam management without sacrificing system performance. Therefore, AI-aided beamforming and beam management have received a lot of attention recently. This article presents a complete survey on this topic, emphasizing open problems and promising directions. The discussion includes architectural and signal processing aspects of modern beamforming and beam management. The article presents communication problems and respective solutions using centralized/decentralized, supervised/unsupervised, semi-supervised, active, federated, and reinforcement learning.

Dengue is one of the most important arboviruses worldwide, with currently approximately 2.5 billion people at risk of becoming infected, mainly in tropical countries. The present study evaluated the influence of climatic variables on the incidence of dengue fever in an endemic urban area. A time series study of cases was carried out with all confirmed cases of dengue fever in the municipality of Belo Horizonte from 2001 to 2021. The climatic explanatory variables were obtained from the National Institute of Meteorology. The analysis was performed using a generalized linear regression model with three scenarios: a no-lag model, 1-month lag model (1 month earlier) and 2-month lag model (2 months earlier). In the no-lag model, the maximum temperature was associated with an increase in the monthly incidence of dengue (IRR: 1.5). In the 1- and 2-month lag models, the monthly average temperature was associated with an increase in incidence (IRR: 1.9 in both). Our results suggest that temperature contributed to the increase in the incidence of dengue, and an increase of 1 °C could increase the incidence of the disease by approximately 90%. Thus, temperature monitoring can direct efforts towards prevention and control of the disease.