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Sistemas agroflorestais e resiliência socioecológica da agricultura familiar na Amazônia Mato-grossense
(Universidade Federal de São Carlos, 2025-01-24) Lopes, Jessica Helena Christofoletti; Olival, Alexandre de Azevedo; Gervazio, Wagner; https://lattes.cnpq.br/1664844008759244; https://lattes.cnpq.br/0044300898154040; https://orcid.org/0000-0001-5080-3846; https://orcid.org/0000-0001-5731-878X; Oliveira, Renata Evangelista de; https://lattes.cnpq.br/6777223792862756; https://orcid.org/0000-0002-4410-7809; https://lattes.cnpq.br/7502767249594555; https://orcid.org/0009-0005-1361-847X
Socio-Ecological System (SES) is a term that reflects the complexity inherent in human-nature relationships. Assessing the resilience of these systems—generally understood as their capacity to adapt to shocks—is of critical importance within the context of Family Farming (FF), given the range of economic, social, and environmental challenges this sector continuously faces. The use of Agroforestry Systems (AFS) can provide several benefits in response to these challenges, such as increased agrobiodiversity, support in coping with climate change, improved soil conditions, income generation, and food sovereignty in rural communities, among others. One of the most recent shocks experienced by family farming was the Covid-19 pandemic, which brought new challenges and required adaptive responses within this SES. In this context, studies are needed to understand how AFS can serve as a strategy for increasing and/or strengthening resilience in the socio-ecological systems of family farming across different localities and cultural, socioeconomic, and environmental contexts. This research was conducted in the Portal da Amazônia Territory (TPA) in northern Mato Grosso, involving rural communities that implemented AFS aimed at forest restoration (in Permanent Preservation Areas and Legal Reserves) and food production (in agroforestry orchards). The study is organized into two chapters: the first presents the theoretical framework, and the second analyzes AFS as a factor of resilience for family farmers in the study area in response to the Covid-19 shock. To this end, semi-structured interviews with local family farmers and content analysis were employed. The findings indicate that the implemented AFS contributed to food security among the participants, and that alternative marketing strategies played a key role in strengthening family farming, in addition to providing environmental benefits for the region.
Modelagem hidrológica da bacia de contribuição da confluência dos rios Itapetininga e Paranapanema
(Universidade Federal de São Carlos, 2025-01-24) Galvão, Pedro Ramos; Fava, Maria Clara; https://lattes.cnpq.br/2972648262855239; https://orcid.org/0000-0002-8201-4339; Vasconcelos, Anaí Floriano; https://lattes.cnpq.br/6595801339743126; https://orcid.org/0000-0002-0596-8251; https://lattes.cnpq.br/5264110234293503
In the current context of climate change, maintaining existing development patterns would increase the exposure and vulnerability of ecosystems and populations to climate threats. Even if global warming is limited to 1.5 °C, historical extreme events will continue to occur. In Brazil, floods have already caused economic losses exceeding R$70 billion and 644 deaths between 1991 and 2023, highlighting the need to improve water management tools. In this context, hydrological modeling stands out as an essential strategy for disaster prediction and mitigation, though its effectiveness relies on reproducing complex patterns in river basins, particularly during climate extremes. This study applied the HEC-HMS model to the contributing basin of the confluence of the Itapetininga and Paranapanema rivers, a region historically impacted by floods, to evaluate its ability to adequately predict flows for this basin. Methods such as the SCS Curve Number for Loss, SCS Unit Hydrograph for Transform, Muskingum for Routing and Constant Monthly for Baseflow were adopted. The model was calibrated using the extreme precipitation event of 2004, and the obtained parameters were applied to simulate events from 2005, 2011, 2016, and 2017. At the outlet, calibration for 2004 resulted in a NSE of 0.700 and an R² of 0.84, reproducing general runoff patterns. However, in subsequent years, NSE values were negative or near zero, and R² values were mostly close to zero. The analysis revealed the basin’s complexity, marked by heterogeneity and dynamic interactions between fluvial systems and adjacent areas. The results underscore the inherent challenges of hydrological modeling, particularly in climate extremes, and emphasize the need for methodological refinements. Despite limitations, the study highlights opportunities for innovations capable of transforming risk mitigation strategies and strengthening resilience to climate change.
Síntese e caracterização de complexos de Eu(III) com ligantes dicetona e diferentes fenantrolinas: aplicações antitumorais e interações com biomoléculas
(Universidade Federal de São Carlos, 2025-01-24) Rocha, Josias da Silveira; Rocha, Fillipe Vieira; https://lattes.cnpq.br/5841127259122766; https://lattes.cnpq.br/1157388662502143; https://orcid.org/0000-0003-4885-6070
In this work, four Eu(III)-based complexes were synthesized and characterized using the dibenzoylmethane (DBM) ligand and various phenanthrolines, PH (4,7 diphenyl-1,10-phenanthroline); NON [1,2,5]oxadiazolo[3',4':5,6]pyrazino[2,3f][1,10]phenanthroline); CN (pyrazino[2,3-f][1,10]phenanthroline-2,3-dicarboni trile); and BrF (10-bromo-12-fluorodipyrido[3,2-a:2',3'-c]phenazine). Characterization was performed using techniques such as X-ray diffraction, elemental analysis (CHN), molar conductivity, magnetic susceptibility, and spectroscopy (UV-Vis, IR, 1D and 2D NMR, and fluorescence). The cytotoxicity of the ligands and complexes was evaluated against tumor cell lines, including lung (A549), prostate (DU-145), triple-negative breast cancer (MDA-MB-231), and cisplatin-resistant ovarian cancer (A2780cis), as well as a non-tumor lung cell line (MRC-5). The complexes demonstrated high inhibitory activity, often comparable to or exceeding that of the standard drug cisplatin. Among the tested compounds, the Eu(DBM)3PH and Eu(DBM)3BrF complexes stood out, displaying remarkable IC50 values of 0.850 µM and 3.57 µM, respectively, in the A2780cis cell line, with selectivity indices of 59.0 and 14.0, respectively. The mechanism of cell death in the A2780cis cell line was characterized as apoptotic, supported by morphological, clonogenic, and flow cytometry assays. In 3D cytotoxicity assays, the complexes demonstrated the ability to inhibit the growth of tumor spheroids. The Eu(DBM)3PH complex showed cytostatic activity, preventing cellular growth even at the lowest tested concentration (0.78 µM). Conversely, the Eu(DBM)3BrF complex exhibited dose- and time-dependent behavior, inhibiting cell growth at 6.25 µM after 96 hours. To investigate potential biomolecular targets, interaction studies were conducted with classical biomolecules such as DNA and Topoisomerase enzymes. Regarding DNA, the complexes predominantly interacted with the minor groove, with Eu(DBM)3PH achieving an 84.4% suppression of the Hoechst 33258 dye. In Topoisomerase IIα (TOPOIIα) inhibition assays, all complexes except Eu(DBM)3CN showed inhibitory activity at 20 µM. Moreover, the observed selectivity suggested that these complexes act as potential catalytic inhibitors of TOPOII, distinguishing themselves from enzyme poisons like etoposide. The complexes also demonstrated the ability to be biologically transported, showing intermediate to strong binding constants (Kb) in the range of 10⁵–10⁶ with human serum albumin (HSA). The obtained results in this thesis demonstrate the promising potential of Eu(III) complexes with diketone and phenanthroline ligands in the field of antitumor applications, highlighting their selectivity and efficacy in tumor cell models
Sustentabilidade e a indústria de papel e celulose: uma análise dos indicadores ambientais de sustentabilidade das empresas Klabin e Suzano S.A
(Universidade Federal de São Carlos, 2025-01-24) Bonini, Gabriela Leandra Souza; Tiezzi, Rafael de Oliveira; https://lattes.cnpq.br/7979063304544915; https://orcid.org/0000-0001-8682-7807
Sustainability in the pulp and paper industry has gained prominence due to increasing pressure for responsible environmental practices. This study evaluates the environmental indicators of Klabin and Suzano S.A., leaders in the Brazilian sector, based on their 2023 sustainability reports. The research addresses energy consumption, water management, waste, and carbon emissions, as well as commitments related to the Sustainable Development Goals (SDGs). The main objective was to analyze the progress of environmental indicators and the disclosure and standardization of information. The specific objectives included: collecting and comparing the companies environmental indicators; evaluating the standardization of disclosed data; and examining long-term commitments and their alignment with the SDGs. The study employed a descriptive qualitative analysis based on the 2023 sustainability reports. Data were organized into spreadsheets and analyzed comparatively. Inclusion criteria considered companies featured in sustainability rankings, such as the Corporate Sustainability Index (ISE) and the Carbon Disclosure Project (CDP). The results highlighted that Klabin stood out for its progress in energy efficiency, while Suzano maintained stability and self-sufficiency in energy generation. Regarding water management, Klabin reduced consumption in water-stressed areas by 20.72%, while Suzano achieved a 99.99% reduction due to the reclassification of areas and initiatives like the Nascentes do Mucuri program. In waste management, Suzano made 90.3% progress toward its goal of reducing industrial waste sent to landfills by 70% by 2030. Klabin achieved a 99.3% total waste reuse rate, reinforcing its circular economy model. Another key topic was carbon emissions: Suzano committed to removing 40 million tons of CO₂ by 2025, while Klabin aims to capture 45 million tons by 2030. Both companies demonstrated significant advances in mitigating climate change. The analyzed companies show leadership in integrating sustainable practices into their operations. Klabin excelled in reducing water consumption and advancing renewable energy, while Suzano showed greater progress in waste management and climate initiatives. Despite the positive results, the lack of standardization in reporting methods complicates direct comparisons. The adoption of stricter national standards would enhance transparency and comparability in the sector.
Utilização de machine learning e algoritmo genético no design de ligas de titânio para aplicações biomédicas
(Universidade Federal de São Carlos, 2025-01-24) Nogueira, Luís Guilherme Santagnelo; Stoco, Caroline Binde; https://lattes.cnpq.br/2458026380104524; https://orcid.org/0000-0002-6856-7519; Otani, Lucas Barcelos; https://lattes.cnpq.br/2519980413159984; https://orcid.org/0000-0002-2831-2335
The production of metastable beta titanium alloys for biomedical applications has grown over the last decade, aiming to meet the demand for materials with an elastic modulus more compatible with bone tissue. This contributes positively to biocompatibility and improves mechanical performance. Alloys such as Ti–29Nb–13Ta–4.6Zr (TNZT), Ti–12Mo–6Zr–2Fe (TMZF), and Ti–35Nb–7Zr–5Ta (TiOsteum) are widely used for their properties, such as high specific mechanical strength and corrosion resistance. These alloys also incorporate beta-phase stabilizing and biocompatible elements, such as Zr, Ta, Nb, and Mo, avoiding elements toxic to humans, such as V, Co, Cr, and Cu. A fundamental challenge in using these alloys for orthopedic implants is reducing the difference between their elastic modulus and that of human bone, minimizing the phenomenon of stress shielding, which can cause bone fragility over time. This discrepancy is governed by the final microstructure formed during alloy processing and heat treatment, which includes parameters such as average grain size, alpha phase volume fraction, martensite volume fraction, and omega phase volume fraction, all of which affect mechanical properties. The integration of machine learning, especially through genetic algorithms, can optimize the development of these alloys. This methodology helps identify compositions that minimize the elastic modulus by adjusting parameters and identifying more efficient combinations. Thus, this study aims to apply machine learning combined with genetic algorithms to obtain chemical compositions of titanium alloys with predominantly beta-phase microstructures and the lowest possible elastic modulus. To this end, both experimental data described in the literature and mathematical models were used to optimize parameters such as E, Moeq (molybdenum equivalent), Bo (bond order), and Md (mean d orbital energy level). Using genetic algorithm codes, a list of chemical compositions with potentially desirable microstructures and properties was obtained.