Navegando por Data de Publicação, começando com "2024-07-16"

Filtrar resultados por ano ou mês

Agora exibindo 1 - 5 de 5

Programação em Python no ambiente educacional: uma proposta de ensino de modelagens algébricas
(Universidade Federal de São Carlos, 2024-07-16) Matias, Marcos José; Silveira, Graciele Paraguaia; https://lattes.cnpq.br/6251988404047002; https://orcid.org/0000-0002-8610-4841; https://lattes.cnpq.br/5166401513381950
This study investigates how programming in Python can assist in learning algebraic modeling. The central problem addressed is the difficulty of 8th-grade students at a rural school in the interior of São Paulo in formulating algebraic models to solve everyday mathematical problems. The objectives of this work were to develop the students’ ability to recognize, generalize, and create algebraic expressions to solve problem situations. The methodology included 10 Python programming lessons with various activities designed to stimulate the development of algebraic skills. The results, obtained through process based assessments, demonstrated a significant improvement in the students’ ability to solve problems algebraically. This study contributes to highlighting the importance of computer programming in Mathematics education from the early years. Future research may further explore the impact of computer programming on Mathematics education in Basic Education.
Chuva de sementes em remanescentes naturais, áreas de reflorestamento e agroflorestas inseridos em paisagens agrícolas: uma revisão sistemática global
(Universidade Federal de São Carlos, 2024-07-16) Lima, Juliana Aparecida de; Martins, Valéria Forni; https://lattes.cnpq.br/0686674300788674; https://lattes.cnpq.br/4618599895233798; Agostini, Kayna; Costa, Rafael Carvalho da; Martins, Valeria Forni; https://lattes.cnpq.br/5894768661755535; https://lattes.cnpq.br/8417166814904384; https://lattes.cnpq.br/0686674300788674
Vegetation fragments located in agricultural landscapes are important for the conservation of biodiversity and ecosystem functions. For the maintenance of such fragments, it is crucial that plant populations can regenerate naturally, especially via recently dispersed seeds (i.e. seed rain). Here we assessed the state-of-the-art knowledge on seed rain in fragments located in agricultural landscapes, focusing on the description of the seed rain, fragments, and matrixes where the fragments are immersed in. We conducted a systematic review of scientific papers published worldwide in English, Portuguese, and Spanish. We built a datasheet containing detailed information on publications, seed rain, fragments, and matrixes. Each line of the datasheet comprises information on a single fragment. We found 41 papers (161 fragments), of which 28 were conducted in Central and South America, especially in Brazil (20 papers and 78 fragments). Most fragments are composed of remaining natural vegetation (61%), show forest structure (96%), are located near other patches of natural vegetation (98%), and are immersed in pastures (50%). Only few papers informed the size of the fragments, regeneration stage of the vegetation, distance between the fragment and other patches of natural vegetation, and presence of ecological corridors. For most of the fragments, there are information on species richness (99%), diaspore abundance (98%), species composition (100%), species list (61%), and growth form of the species (39%). Only few papers reported on exotic species, dispersal syndromes, and seed size. There is floristic survey for 76% of the fragments, but the classification of species of the seed rain as autochthonous or allochthonous is reported for only 34% of the fragments with floristic survey. Our findings are a starting point for future studies aiming at biological conservation, especially by providing a detailed datasheet and identifying information still needed for a better understanding of natural regeneration via seed rain in fragments located at agricultural landscapes.
Sistemas químicos auto-organizados: morfogênese e formação de padrões
(Universidade Federal de São Carlos, 2024-07-16) Silva-Dias, Leonardo; López-Castillo, Alejandro; https://lattes.cnpq.br/2599181118729458; https://lattes.cnpq.br/2923386173329657; https://orcid.org/0000-0003-0535-6666
Chemical systems maintained far from equilibrium, with spatially extended reaction domains, and composed of chemicals that interact non-linearly with each other, can spontaneously evolve to organized states of low entropy, known as dissipative structures. These structures are commonly observed in living organisms, and the most notable are: periodic oscillations of chemical concentration, chemical chaos, chemical waves, and stationary patterns (Turing patterns). This class of self-organized chemical systems comprises a significant number of inorganic chemical reactions with well-known mechanisms. Due to this fact, along with the dynamical similarities of these reactions to living organisms' dynamics, and the complexity of reaction mechanisms in chemical-biological processes, inorganic chemical systems are often considered in studies of dynamical phenomena in different scenarios in order to obtain results that can be extrapolated to understanding similar phenomena in living systems. From this perspective, this thesis presents an investigation of morphogenesis and spatio-temporal pattern formation in conditions that are either relevant or motivated by biology. This is accomplished through four main works. In the first, we investigated the emergence of Turing patterns in the chlorine dioxide–iodine–malonic acid (CDIMA) reaction in a domain that continuously grows as a rotating spiral. From this study, we observed the formation of a new class of stationary spiral patterns with different multiplicities. In the second, we evaluated the effects of Faraday waves on the formation of chemical waves in the Belousov-Zhabotinsky reaction, aiming to discriminate acoustic frequencies through the spatio-temporal dynamics of the reaction. We noted that Faraday waves interfere with the local process of mixing, altering the speed and morphology of the chemical waves. However, this system was ineffective in discriminating the applied acoustic frequencies. In the third work, we developed a simple and practical procedure to obtain transient Turing patterns in a batch system from the CDIMA reaction. From such an experimental procedure, we obtained patterns with good resolution and stability. Finally, in the fourth one, we proposed a model based on the classical theory of phase separation and reaction-diffusion systems to describe morphogenesis in a system of synthetic chemical cells. Through numerical simulations, we were able to elucidate the physical-chemical mechanism of this process and to identify that the difference in osmotic pressure between two cells in different chemical states, due to the break of spatial symmetry caused by the emergence of a Turing state, triggers the physical morphogenesis.
Auto-treinamento com ruído utilizando data augmentations para tarefas de detecção de comentários ofensivos e discurso de ódio
(Universidade Federal de São Carlos, 2024-07-16) Leite, João Augusto; Silva, Diego Furtado; https://lattes.cnpq.br/7662777934692986; https://orcid.org/0000-0002-5184-9413; https://lattes.cnpq.br/2523889749935848; https://orcid.org/0000-0002-3587-853X
Online social media is rife with offensive and hateful comments, necessitating the development of automated detection systems to manage the vast volume of posts generated every second. Creating high-quality human-labeled datasets for this task is challenging and costly, primarily because non-offensive posts significantly outnumber offensive ones. In contrast, unlabeled data is abundant, more accessible, and cheaper to obtain. This thesis explores the application of self-training methods, which leverage weakly-labeled examples to augment training datasets, in the context of offensive and hate speech detection. The core of this thesis is the paper "Noisy Self-Training with Data Augmentations for Offensive and Hate Speech Detection Tasks", which investigates the efficacy of noisy self-training approaches incorporating data augmentation techniques to enhance prediction consistency and robustness against noisy data and adversarial attacks. Experiments are conducted with both default and noisy self-training using three different textual data augmentation techniques across five distinct pre-trained BERT architectures of varying sizes. The results indicated that noisy self-training with textual data augmentations, despite its success in similar settings, decreased performance in offensive and hate speech domains compared to the default method. This finding and reveals limitations of noisy self- training methods with data augmentations for domains such as offensive speech detection, where certain specific keywords cannot be modified without introducing semantic variations.
Comportamento assintótico para equações de placa fracionárias
(Universidade Federal de São Carlos, 2024-07-16) Picolli, Iago Aparecido da Silva; Nascimento, Marcelo José Dias; https://lattes.cnpq.br/7133572787875912; https://orcid.org/0000-0003-0192-3395; https://lattes.cnpq.br/1507534312171899; https://orcid.org/0009-0007-9228-4360
In this work, we consider two second-order fractional semilinear plate equations in time. In the first problem, we investigate an equation governed by a biharmonic operator, with clamped boundary conditions in a smooth bounded domain, modeling flight structures. In this context, we introduce a dissipative term that depends directly on the energy of the system. In the second problem, we add a memory term, resulting in a dissipative system that depends on energy and past memory. In both cases, we study local and global well-posedness and we prove the existence of a compact global attractor for the associated evolution semigroup. Additionally, we obtain the upper semicontinuity of the family of global attractors.