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Síntese multicomponente de piperidinas densamente funcionalizadas e estudos sobre atividade fungicida
(Universidade Federal de Lavras, 2026-01-30) Souza, Stefany Amorim de; Thomasi, Sérgio Scherrer; Farias, Otília Ricardo de; Oliveira, Lyege Magalhães; Thomasi, Sérgio Scherrer
Multicomponent synthesis (MCR) constitutes a versatile and efficient methodological approach for the construction of complex molecules, standing out in the preparation of densely functionalized piperidines, which present high relevance in the pharmaceutical field due to their potential as bioactive compounds. In addition, this strategy is aligned with the principles of green chemistry, as it promotes the reduction of waste generation, as well as the decrease in time and resource consumption during the synthetic process. In the present study, a synthetic route was developed aiming at the preparation of the molecule ethyl-(2S,6R)-1,2,5,6- tetrahydro-1,2,6-triphenyl-4-phenylamine-3-pyridine carboxylate and its halogenated derivatives. The target molecule presents pharmacological relevance by incorporating structural features associated with potential biological activities, such as anti-inflammatory, antitumor, and antimicrobial actions. The methodology employed involved the use of benzaldehydes substituted with chlorine and fluorine atoms in different positions, allowing the evaluation of the electronic and steric effects of these substitutions on the biological activity of the compounds, since halogenated groups can positively influence interactions with biological targets. In total, five molecules were synthesized, named AB, B1, B2, B5, and B6, with yields of 78%, 82%, 83%, 81%, and 79%, respectively. All obtained structures were properly characterized by nuclear magnetic resonance spectroscopy (NMR), Fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC), confirming the formation of the desired products. The antifungal activity of the compounds was evaluated against the phytopathogen Rhizoctonia solani, responsible for significant losses in agricultural crops of great importance to Brazil. Molecules B1, B2, B5, and B6 showed excellent antifungal activity, promoting complete inhibition of fungal growth, with no visible growth observed. In contrast, molecule AB did not show significant antifungal activity. Overall, the results indicate that the insertion of chlorine and fluorine groups into the synthesized structures contributed positively to antifungal activity, highlighting the potential of these molecules as promising candidates for the development of new antifungal agents.
Ayana e a condição migrante feminina em A bagagem da imigração, de Patrícia Moreira
(Universidade Federal de Lavras, 2026-02-26) Domingos, Aleízy Aparecida Barati; Assis, Roberta Guimarães Franco Faria de; Jorge, Silvio Renato; Barbosa, Rodrigo Garcia
Migratory transits have gained new perspectives as a result of decolonization processes, especially when the direction of displacements changes, often from former colonies to former metropolises, which generates a new perspective from society on the subject in transit, or migrant. New implications for the subjects’ identities, their experiences in the migratory scenario, and the hostility that seems to be related to this process are aggravated when also crossed by the issue of gender. Thus, this paper presents an analysis of the migratory experience of Ayana, the central character in the novel A bagagem da Imigração (2024), by Patrícia Moreira. Ayana is Cape Verdean and decides to leave her country for Europe to improve her living conditions and those of her family and to close the gap that separated her from Samuel, her love interest. The process is planned illegally and, despite having France as her final destination, she uses Portugal as a gateway to European territory. In the Portuguese lands, Ayana still spends a short period of time visiting some relatives who had lived there for many years. In these two spaces in which the narrative unfolds, the protagonist witnesses and suffers countless acts of violence, which seem to affect her doubly because she is an immigrant woman. Thus, the general objective of this study is to examine, in the light of Comparative Literature and based on the work A Bagagem da Imigração (2024), by Patrícia Moreira, how to understand specificities in the female migrant condition. Other specific objectives include investigating how the migrant condition impacts the perception and expression of identity; analyzing how the theme of violence is presented in the context of migratory transit; and studying whether, for women, the different types of disturbed experiences in the migratory transit scenario are considerably accentuated. This analysis, seen as a portrait of the social configurations of Portugal today, will also be carried out with a transdisciplinary character, since elements dear to Sociology and History are essential for the relationship between literary representation and the social context to be critically established.
Aspectos teóricos, simulação e aplicações da estimação sequencial bayesiana em distribuições multinomiais
(Universidade Federal de Lavras, 2026-02-06) Lima, Isabela da Silva; Brighenti, Carla Regina Guimarães; Santos, Deodoro Magno Brighenti dos; Ferreira, Eric Batista; Giarola, Luciane Teixeira Passos; Fernandes, Tales Jesus
Sequential sampling is a statistical technique in which the sample size is not fixed. Observations are successively incorporated into the process, and at each new observation, the established stopping criterion is evaluated. The procedure is interrupted when the criterion is met, and the total number of observations made up to that point defines the sample size. The main advantage of this sampling method is that it generally results in smaller sample sizes compared to fixedsize samples, reducing costs and time. The Bayesian decision theory, associated with sequential sampling, constitutes an approach for estimating parameters of interest, which allows the inclusion of prior information that assists the sampling plan. However, the implementation of this approach presents challenges arising from the recursion involved and the definition of the stopping criterion, which become even more complex in multivariate models. Due to the inherent difficulty of the procedure, most studies in literature have been developed for discrete and univariate distributions, notably the binomial distribution. There is a gap in the development and application of sequential Bayesian estimation for multivariate distributions, such as the multinomial distribution, used to estimate proportions in problems with more than two response categories. Given this gap, this thesis aims to propose the estimation of multinomial distribution parameters through Bayesian inference using sequential sampling, exploring theoretical aspects and applications. To this end, through simulation studies, the behavior of the sequential Bayesian estimation of multinomial distribution parameters was analyzed under different scenarios. Subsequently, a Shiny application was developed in the R software, aiming to broaden the accessibility and applicability of the approach. Furthermore, the approach was applied in two real-world practical situations: in population genetics, where allele and genotype proportions were estimated, and in beekeeping, where the proportions of honeycomb cell content were estimated. In general, the results obtained demonstrate that Bayesian sequential estimation for multinomial distribution parameters is an efficient and economically advantageous alternative, capable of producing accurate estimates with smaller sample size, compared to fixed-size sampling. Furthermore, the applied studies reinforce the potential of the approach for real-world problems in different areas.
Planejamento otimizado da colheita florestal: modelagem para projeção de sortimentos da indústria e agendamento sequencial da colheita
(Universidade Federal de Lavras, 2025-12-03) Silva, Nivandilmo Luiz da; Calegario, Natalino; Gomide, Lucas Rezende; Leite, Helio Garcia
The planning of forest harvesting aligned with industrial production is essential to optimize the use of timber resources, reduce economic losses, and increase the profitability of forestry companies. In this context, this study aimed to integrate two main approaches to harvest management and planning: (i) modeling the diameter distribution for volumetric projection of assortments and (ii) optimization of sequential harvest scheduling through mathematical programming in operations research. In the first stage, two fitting methods for the threeparameter (3P) Weibull probability density function were compared: maximum likelihood estimation (MLE) and method of moments (MM), combined with two projection methods: Parameter Prediction Method (PPM) and Parameter Recovery Method (PRM), thereby generating four diameter projection flows (F). In the second stage, a Integer Linear Programming (ILP) model was developed, integrating Production Regulation (R) constraints with Harvest Sequencing (S) constraints to maximize Net Present Value (NPV). In the modeling section, the analyses of the Weibull function included the quotient Kolmogorov–Smirnov test (KSq) and prediction error statistics for each plot, as well as the projections of each flow (F) applied to the final production of industrial assortments. In the harvest optimization phase, analyses were performed through simulations of three scenarios defined by the constraints: C1 (R), C2 (R+S), and C3 (control: company standard). For both parts of the study, information from commercial plantations supplying a sawmilling industry in the state of Alagoas was used. The data were processed in R, and optimization was solved using the Gurobi solver. The results indicated that the moments-based method combined with the parameter recovery projection (F4 = MM + PRM) showed the highest statistical accuracy in predicting industrial assortments. At harvest age, F4 presented the best results for both the highest-value assortment (0.04%) and the sum of products from sawmills I + II (–7.45%) and total volume (–9.56%). In terms of harvest sequencing, scenario C2 showed the best performance, with a 5.6% increase in multiproduct volume and gains of up to R$ 750.00 per hectare compared to the company’s current practice (C3). Therefore, it is concluded that combining MM fitting with PRM projection improves volumetric prognosis, and the use of this information in the proposed ILP optimization model constitutes a complete and accurate approach to optimizing harvest sequencing by synchronizing forest production with industrial demand.
A prevalência da dengue em um município do Sul de Minas Gerais sob a lente do racismo ambiental: perspectivas e desafios
(Universidade Federal de Lavras, 2026-02-12) Miranda, Aline da Cunha; Mafra, Flávia Luciana Naves; Rezende, Ana Flávia; Amâncio, Julia Moretto
This research examines the prevalence of dengue fever in a municipality in southern Minas Gerais, analyzing territorial and social factors through the lens of environmental racism. The study is situated within the context of the Anthropocene, an era defined by the significant impact of human activities on the planet which intensifies and normalizes historical structural inequalities. In Brazil, dengue has emerged as a recurring public health crisis, currently exacerbated by climate change and the unequal distribution of risks driven by structural and environmental racism. A qualitative methodology was adopted, employing an interpretive approach and constructivist epistemology. Data collection strategies included documentary research, semi-structured interviews with residents of the most affected neighborhood, and nonsystematic field observations. Data was analyzed using thematic content analysis, identifying recurring categories and themes within the participants' narratives. The discussion highlights that dengue prevalence is intrinsically linked to territorial inequalities and environmental racism, manifesting through the disparate provision of public services and differential exposure to risk. This research proposes integrated actions for prevention, communication, and social participation, emphasizing the need for public policies sensitive to local specificities. Results reveal that the neighborhood with the highest percentage of dengue cases in 2024 is a peripheral area classified as a Special Zone of Social Interest (ZEIS). Interviews demonstrate that the impacts of dengue extend beyond physical symptoms, affecting the routines, labor, income, and psychological well-being of residents, particularly women. Participants' perceptions point to risk factors such as vacant lots, waste accumulation, and a lack of adequate disposal infrastructure, alongside a tendency to normalize the disease and shift responsibility onto others rather than collective or governmental action. It is concluded that analyzing dengue through environmental racism provides theoretical and practical relevance for deconstructing the social determinants of the disease, highlighting the urgency of interventions tailored to specific territorial contexts. Finally, the study reinforces the importance of disaggregated data, community engagement, and intersectoral municipal management to effectively tackle dengue and other pathologies.