Universidade do Vale do Itajaí (Univali)

In this review we highlight the relevance of biodiversity that inhabit coastal lagoons, emphasizing how species functions foster processes and services associated with this ecosystem. We identified 26 ecosystem services underpinned by ecological functions performed by bacteria and other microbial organisms, zooplankton, polychaetae worms, mollusks, macro-crustaceans, fishes, birds, and aquatic mammals. These groups present high functional redundancy but perform complementary functions that result in distinct ecosystem processes. Because coastal lagoons are located in the interface between freshwater, marine and terrestrial ecosystems, the ecosystem services provided by the biodiversity surpass the lagoon itself and benefit society in a wider spatial and historical context. The species loss in coastal lagoons due to multiple human-driven impacts affects the ecosystem functioning, influencing negatively the provision of all categories of services (i.e., supporting, regulating, provisioning and cultural). Because animals’ assemblages have unequal spatial and temporal distribution in coastal lagoons, it is necessary to adopt ecosystem-level management plans to protect habitat heterogeneity and its biodiversity, ensuring the provision of services for human well-being to multi-actors in the coastal zone.

Nicotiana azambujae is an endemic species from Santa Catarina state, southern Brazil, that was described in 1964 and has not been seen since then. During fieldwork, we found a population in Alto Matador, about 70 km from the presumable type collection, after 73 years of its last known collection. Thus, we bring the first in vivo pictures of this species, assess its conservation status, update the morphologic description and discuss its habitat preferences. Also, we discuss a possible mistake in the type of voucher label from the originally collected locality. Keywords: Atlantic Forest; Extinct species; Nicotianeae

The increase in life expectancy, according to the World Health Organization, is a fact, and with it rises the incidence of age-related neurodegenerative diseases. The most recurrent symptoms are those associated with tremors resulting from Parkinson’s disease (PD) or essential tremors (ETs). The main alternatives for the treatment of these patients are medication and surgical intervention, which sometimes have restrictions and side effects. Through computer simulations in Matlab software, this work investigates the performance of adaptive algorithms based on least mean squares (LMS) to suppress tremors in upper limbs, especially in the hands. The signals resulting from pathological hand tremors, related to PD, present components at frequencies that vary between 3 Hz and 6 Hz, with the more significant energy present in the fundamental and second harmonics, while physiological hand tremors, referred to ET, vary between 4 Hz and 12 Hz. We simulated and used these signals as reference signals in adaptive algorithms, filtered-x least mean square (Fx-LMS), filtered-x normalized least mean square (Fx-NLMS), and a hybrid Fx-LMS–NLMS purpose. Our results showed that the vibration control provided by the Fx-LMS–LMS algorithm is the most suitable for physiological tremors. For pathological tremors, we used a proposed algorithm with a filtered sinusoidal input signal, Fsinx-LMS, which presented the best results in this specific case.

This study covers the thermal simulation of an industrial furnace used to produce ceramic frits, a material requested for glazes and coatings of tiles and porcelains. The current production in the studied kiln is around 700 kg/h, and the furnace consumes around 1.0 MW by firing natural gas with pure oxygen. In this process, energy transfer by radiation is dominant, and species-like CO2 and H2O in the flue gas constitute a participant gas that interferes in the heat transfer. Eddy Dissipation Model, Weighted Sum of Gray Gases, and k-ϵ with a turbulence intensity of 5% are selected as models for combustion, absorption of participant media, and turbulence, respectively. A kinetic model WD 1-step is chosen for the reaction of CH4/O2 with a slight oxidizer’s excess. The combustion chamber and load domain are solved separately but coupled during iterations to improve stability and reduce computational cost. A simplified multiphase model is prescribed at the load based on thermodynamic properties as temperature functions. Experimental measurements of the furnace are used to validate numerical results. Two new positions of the chimney are proposed, and the furnaces’ performance is compared with the current operational model in the industry. Improvement in production is observed for a chimney in the front top of the furnace. With a chimney in the top back, the current case presents the second-best configuration tested, followed by the case with a chimney in the top center.

O presente artigo tem o objetivo de discutir os regimes socioeconômicos que permitem a realização da justiça como equidade, focando em especial nos dois regimes apontados por Rawls como capazes de constituir uma sociedade bem ordenada, a democracia de cidadãos proprietários (property-owning democracy ou POD) de um lado e o socialismo liberal do outro. Para tanto, em um primeiro momento serão considerados os argumentos de Rawls a respeito dos regimes socioeconômicos dentro da Uma teoria da justiça. Em seguida, com base em Justiça como equidade: uma reafirmação, serão discutidos os argumentos em favor da POD e do socialismo liberal e contra as outras três opções: capitalismo de laissez-faire, socialismo de Estado dirigido por um partido único e o Estado de bem-estar social. Em seguida, serão considerados os argumentos a favor da POD ou do socialismo liberal, procurando em grande medida traçar quais são as distinções entre ambos os regimes, a partir dos autores que buscam ir além de Rawls. Ao final, conclui-se que nos limites de uma teoria da justiça Rawls está correto ao não definir quem é o regime vencedor, a POD ou o socialismo liberal, mas no avanço atual do capitalismo liberal e no seu movimento de distanciamento das democracias liberais mostra-se necessário discutir qual é o regime mais adequado a partir das bases fornecidas pela justiça como equidade.

The increasing complexity of System-on-Chip (SoC) and the ongoing technology miniaturization on Integrated Circuit (IC) manufacturing processes makes modern SoCs more susceptible to Single-Event Effects (SEE) caused by radiation, even at sea level. To provide realistic estimates at a low cost, efficient analysis techniques capable of replicating SEEs are required. Among these methods, fault injection through emulation using Field-Programmable Gate Array (FPGA) enables campaigns to be run on a Circuit Under Test (CUT). This paper investigates the use of an FPGA architecture to speed up the execution of fault campaigns. As a result, a new methodology for mapping the CUT occupation on the FPGA is proposed, significantly reducing the total number of faults to be injected. In addition, a fault injection technique/flow is proposed to demonstrate the benefits of cutting-edge approaches. The presented technique emulates Single-Event Transient (SET) in all combinatorial elements of the CUT using the Internal Configuration Access Port (ICAP) of Xilinx FPGAs.

The literature reports the presence of multiresistant microorganisms in wastewater discharged from municipal and hospital wastewater treatment plants (WWTPs). This has led to questions concerning the disinfection efficiency of the treatments applied. Thus, this study aimed to assess the efficiency of different chemical oxidation methods to disinfect and to degrade bacterial plasmids present in hospital wastewaters, to avoid the dispersion of antibiotic resistance genes in the environment. The methods tested were UV254nm alone or associated with an Ag or Ti-photocatalyst in photo-peroxonization (UV254 nm/H2O2/O3/Ag2O/Ag2CO3@PU or UV254 nm/H2O2/O3/TiO2@PU) under different pH conditions (4, 7, and 10). The application of plasmid DNA electrophoresis to hospital wastewater treated using an advanced oxidation process (AOP) achieved the total structural denaturation of microorganism plasmids at the three pH values tested. Also, UV254 nm alone was partially efficient in the disinfection of hospital wastewater. AOPs performed with the two functionalized catalysts resulted in 100% disinfection after 10 min at the three pH values tested. No intact plasmids were observed after 20 min of treatment with photocatalysis. This study could contribute to the development and improvement of wastewater treatment aimed at mitigating the spread of multiresistant microorganisms in the environment.

The cost of electricity and gas has a direct influence on the everyday routines of people who rely on these resources to keep their businesses running. However, the value of electricity is strongly related to spot market prices, and the arrival of winter and increased energy use owing to the demand for heating can lead to an increase in energy prices. Approaches to forecasting energy costs have been used in recent years, however, existing models are not yet robust enough due to competition, seasonal changes, and other variables. More effective modeling and forecasting approaches are required to assist investors in planning their bidding strategies and regulators in ensuring the security and stability of energy markets. In the literature, there is considerable interest in building better pricing modeling and forecasting frameworks to meet these difficulties. In this context, this work proposes combining seasonal and trend decomposition utilizing LOESS (locally estimated scatterplot smoothing) and Facebook Prophet methodologies to perform a more accurate and resilient time series analysis of Italian electricity spot prices. This can assist to enhance projections and better understanding the variables driving the data, while also including additional information like holidays and special events. The combination of approaches improves forecast accuracy while lowering the mean absolute percentage error (MAPE) performance metric by 18% compared to the baseline model.

Context social media have an immense amount of information, being a space for its dissemination. Individuals, online connections, are able to filter or give visibility to certain information, to the detriment of others. The central problem lies in monitoring posts and reactions aimed at corporate actions and strategies. In addition to this monitoring, companies can make decisions based on the data collected. Objective to develop and structure a social media management tool. Methods to achieve the general objective, the article was developed in three main steps. The first was to suggest a free software script for capturing and initial analysis of Twitter posts. The second step was to categorize this analysis and identify resources and competencies needed by companies. Finally, actions to be taken by companies for social media management were suggested. Results the developed script enabled the automated extraction of data, which were stored in a database for analysis and management of online interactions. The actions were proposed based on the case study developed. Conclusions in the practical field, this study contributes to the process of extracting data from Twitter by proposing a new script for capturing data, identifying the main categories of influence of digital activists and monitoring social media through strategic actions. By demonstrating that the script is effective in extracting data, it is possible to carry out further studies and implement the social media management monitoring process. Keywords: on-line social activism; social media monitoring; Twitter data extraction; secondary data

In southern Brazil, the biodiversity is great and the traditional use of medicinal plants for wound healing has been documented in ethnobotanical studies and pharmacological studies have assessed their wound properties and phytochemistry. Therefore, this study evaluated ethnobotanical surveys regarding medicinal plants used in southern Brazil for wound healing and studies about the healing properties of these plants published between 2000 and 2022. To retrieve articles related to the study, Web of Science, PubMed (NLM), Open Access Journals, Scielo, Lilacs, and Google Scholar, with keywords including medicinal plants, wound healing, and South of Brazil, have been used. As a result, 73 medicinal plants belonging to 39 families were found in ethnobotanical surveys as a traditional resource used for wound healing in southern Brazil, 15 of which were cited more than once. Besides, 14 of these 15 plants were also used as healing agents worldwide. The most cited plant with healing actions in southern Brazil was Symphytum officinale L. (comfrey). From 2000 to date, 44 articles scientifically demonstrated the wound‐healing effects of the southern Brazilian plants found in ethnobotanical surveys reviewed. The folk medicine of southern Brazil presents a variety of medicinal plants for wound‐healing purposes, and scientific data were found for some of those plants. However, the wound‐healing properties of many plants have yet to be investigated, and the current literature still needs more phytochemical information about the plants studied. Aside from this, the future focus should be on the standardization of herbal extracts, and further research is required to investigate the pharmacological mechanisms. Clinical research in this area remains in its infancy and warrants more robust further clinical studies.

Ocean ecosystems are at the forefront of the climate and biodiversity crises, yet we lack a unified approach to assess their state and inform sustainable policies. This blueprint is designed around research capabilities and cross-sectoral partnerships. We highlight priorities including integrating basin-scale observation, modelling and genomic approaches to understand Atlantic oceanography and ecosystem connectivity; improving ecosystem mapping; identifying potential tipping points in deep and open ocean ecosystems; understanding compound impacts of multiple stressors including warming, acidification and deoxygenation; enhancing spatial and temporal management and protection. We argue that these goals are best achieved through partnerships with policy-makers and community stakeholders, and promoting research groups from the South Atlantic through investment and engagement. Given the high costs of such research (€800k to €1.7M per expedition and €30–40M for a basin-scale programme), international cooperation and funding are integral to supporting science-led policies to conserve ocean ecosystems that transcend jurisdictional borders.

O objetivo desse estudo é desenvolver um framework de accountability, para a governança nos Parques Estaduais Rio Negro – Setores Norte e Sul. A Amazônia, por sua singularidade, tornou-se elemento de discussões globais sobre alternativas de desenvolvimento socioeconômico, ajustadas ao meio ambiente natural e cultural dessa região. Nesse sentido, justifica-se a análise da atividade turística, potencialmente geradora de progresso social e econômico, quando administrada sob os princípios da sustentabilidade – social, ambiental e econômica. A pesquisa de natureza qualitativa, de caráter exploratório e descritivo foi desenvolvida através de ciclos adaptativos. Os achados da investigação empírica foram obtidos por meio de entrevistas com um painel de especialistas, um gestor público e dois convidados e aplicou-se a técnica de análise de conteúdo. Como implicação gerencial deste estudo tem-se que, havendo a implementação adequada do framework de accountability, que consiste em um conjunto de orientações que auxiliam na gestão e na boa governança aos Parques Estaduais na Amazônia, será potencializada de forma a atender aos anseios dos atores que interagem nesses espaços.

O humano é um ser simbólico que busca explicar os fenômenos que surgem diante de si, os fenômenos visuais. Para isso a semiótica o auxilia nesse caminho da interpretação. No universo turístico, as fotografias emergem como contributo para a evolução no modo de representar, registrar, documentar o que está ao alcance dos olhos ou além. Nesse sentido, esta pesquisa busca demonstrar como a semiótica do turismo contribui para adensar as análises visuais no campo do turismo. Para tanto, visa-se conferir sua usabilidade, assim como a aplicação desse método, suas categorias e uso na produção de sentido. Esta pesquisa, de natureza qualitativa, realizou uma análise visual em fotos do Cristo Redentor extraídas do Instagram. Dentre os principais resultados, foi possível constatar o papel da semiótica do turismo como aporte metodológico junto as pesquisas com teor visual. Essa aplicabilidade possibilitou, por meio de categorias, elementos e composição, identificar três interpretações mediante as fotos do Cristo Redentor: (i) como representação (sentido semiótico); (ii) como um pano de fundo (tela semiótica); (iii) como cenário na dinâmica com os turistas.

In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.

Este caso para ensino relata o dilema da empresa AC COMEX, que atua desde 2003 no ramo de consultorias e soluções para empresas de comércio internacional. A partir de 2012 seu principal serviço se tornou o registro de SISCOSERV. No entanto, em 2020, foi suspensa a obrigatoriedade de as empresas alimentarem o SISCOSERV com dados de importações e exportações, comprometendo a gestão da AC COMEX e sua sustentabilidade no mercado. As fontes primárias foram entrevistas e comunicação direta com os sócios da AC COMEX. Como fonte secundária foram utilizados o site oficial da empresa e documentos fornecidos pelos sócios. O presente caso é plataforma para a avaliação de estratégias utilizadas e para diversificação de negócios internacionais que minimizem o impacto das ameaças do ambiente externo, trazendo sustentabilidade financeira à empresa. Após o período de debate, é esperado que a classe direcione as melhores decisões, e o que a empresa poderia ter feito. Os integrantes da classe deverão analisar as estratégias propostas e poderão configurar uma decisão final mais correta.

CubeSats must endure the extreme temperature and radiation changes that are a result of the environment in orbit. The power system of CubeSats, which produces the electrical energy required to carry out the activities, is a crucial component. The photovoltaic effect, a phenomenon whose maximum power point decreases as temperature rises while the peak rises with solar radiation intensity rises, is used by the majority of satellites, including CubeSats, to convert solar radiation into electrical energy. High temperatures should be avoided since they decrease the effectiveness of this photovoltaic phenomenon, whereas high solar radiation levels are required to produce more energy. This study evaluates a simulation of a CubeSat 1U with solar panels mounted on all of its faces to examine the impact of orbit, attitude, and temperature management on power generation. The outcomes show that higher performance may be obtained by carefully choosing these factors.

Hyperspectral images contain tens to hundreds of bands, implying a high spectral resolution. This high spectral resolution allows for obtaining a precise signature of structures and compounds that make up the captured scene. Among the types of processing that may be applied to Hyperspectral Images, classification using machine learning models stands out. The classification process is one of the most relevant steps for this type of image. It can extract information using spatial and spectral information and spatial-spectral fusion. Artificial Neural Network models have been gaining prominence among existing classification techniques. They can be applied to data with one, two, or three dimensions. Given the above, this work evaluates Convolutional Neural Network models with one, two, and three dimensions to identify the impact of classifying Hyperspectral Images with different types of convolution. We also expand the comparison to Recurrent Neural Network models, Attention Mechanism, and the Transformer architecture.. Furthermore, a novelty pre-processing method is proposed for the classification process to avoid generating data leaks between training, validation, and testing data. The results demonstrated that using 1 Dimension Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM), and Transformer architectures reduces memory consumption and sample processing time and maintain a satisfactory classification performance up to 99% accuracy on larger datasets. In addition, the Transfomer architecture can approach the 2D-CNN and 3D-CNN architectures in accuracy using only spectral information. The results also show that using two or three dimensions convolution layers improves accuracy at the cost of greater memory consumption and processing time per sample. Furthermore, the pre-processing methodology guarantees the disassociation of training and testing data.