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Morfologia descritiva do crânio de Subulo gouazoubira e Mazama nana (Artiodactyla, Cervidae)
No full textOsteology plays an indispensable role in understanding the normal patterns of different species, serving as the foundation for zoological understanding. Mazama nana is well-known in Brazil; however, basic morphological descriptions of the species are scarce, while Subulo gouazoubira, currently revalidated as Mazama gouazoubira, is also prevalent in Brazil and has recently been the subject of various phylogenetic studies. In this respect, in the present study, 19 cervid heads (16 Subulo gouazoubira and three Mazama nana) were osteologically prepared. Next, computed tomographies (CTs) were performed to enhance the assessment of bone accidents, as well as internal structures and foramina through three-dimensional (3D) reconstruction techniques due to the difficult visibility in intact specimens. A comparison was then made between the reconstructions, digital photographs, and CT cross-sections of the skull, which enabled the visualization of anatomical peculiarities and exclusivities, such as nasolacrimal-maxillary fenestra, paranasal sinuses, and thin bone architecture, as well as the unique shape of cranial bones, compared to other species that exhibit a unique and genuine phenotype.Laboratório de Anatomia Veterinária Universidade Estadual do Centro Oeste do Paraná (UNICENTRO), PRUniversidade Estadual de São Paulo “Júlio Mesquita Filho” (UNESP), SPHospital Veterinário Santa Fé, PRUniversidade Estadual de São Paulo “Júlio Mesquita Filho” (UNESP), S
Exploring percolation features with polynomial algorithms for classifying Covid-19 in chest X-ray images
No full textCovid-19 is a severe illness caused by the Sars-CoV-2 virus, initially identified in China in late 2019 and swiftly spreading globally. Since the virus primarily impacts the lungs, analyzing chest X-rays stands as a reliable and widely accessible means of diagnosing the infection. In computer vision, deep learning models such as CNNs have been the main adopted approach for detection of Covid-19 in chest X-ray images. However, we believe that handcrafted features can also provide relevant results, as shown previously in similar image classification challenges. In this study, we propose a method for identifying Covid-19 in chest X-ray images by extracting and classifying local and global percolation-based features. This technique was tested on three datasets: one comprising 2,002 segmented samples categorized into two groups (Covid-19 and Healthy); another with 1,125 non-segmented samples categorized into three groups (Covid-19, Healthy, and Pneumonia); and a third one composed of 4,809 non-segmented images representing three classes (Covid-19, Healthy, and Pneumonia). Then, 48 percolation features were extracted and give as input into six distinct classifiers. Subsequently, the AUC and accuracy metrics were assessed. We used the 10-fold cross-validation approach and evaluated lesion sub-types via binary and multiclass classification using the Hermite polynomial classifier, a novel approach in this domain. The Hermite polynomial classifier exhibited the most promising outcomes compared to five other machine learning algorithms, wherein the best obtained values for accuracy and AUC were 98.72% and 0.9917, respectively. We also evaluated the influence of noise in the features and in the classification accuracy. These results, based in the integration of percolation features with the Hermite polynomial, hold the potential for enhancing lesion detection and supporting clinicians in their diagnostic endeavors.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)Faculty of Engineering University of Porto (FEUP)Federal Institute of Education Science and Technology of São Paulo (IFSP), SPScience and Technology Institute Federal University of São Paulo (UNIFESP), SPDepartment of Computer Science and Engineering (DISI) University of Bologna, FCDepartment of Computer Science and Statistics (DCCE) São Paulo State University (UNESP), SPFaculty of Computer Science (FACOM) Federal University of Uberlândia (UFU), MGDepartment of Computer Science and Statistics (DCCE) São Paulo State University (UNESP), SPCNPq: #132940/2019-1FAPESP: #2022/03020-1CNPq: #311404/2021-9CNPq: #313643/2021-0FAPEMIG: #APQ-00578-18FAPEMIG: #APQ-01129-2
Microbial astaxanthin-encapsulated polymeric micelles from yeast Phaffia rhodozyma for personalized bioactive colored natural rubber latex bandages
No full textThis study explores the development of bioactive, colored natural rubber latex (NRL) bandages by incorporating astaxanthin (AXT), a carotenoid with potent antioxidant and anti-inflammatory properties. AXT is produced by the yeast Phaffia rhodozyma under various light conditions to improve AXT biosynthesis and encapsulated in polymeric micelles to enhance its solubility and stability. The encapsulated AXT is then integrated into NRL bandages, imparting a orange-red hue and potentially therapeutic benefits. Physicochemical characterizations, including UV–Vis spectroscopy and FTIR, reveal interactions between AXT and the micelle components. The bandages exhibit improved hydrophilicity and maintain their thermal stability post-AXT incorporation. Antioxidant capacity assessments show that the NRL bandages retain a significant portion of AXT's antioxidant properties, which can aid in wound healing. The release profile of AXT from the bandages demonstrates an initial burst followed by sustained release, indicating effective delivery of the carotenoid. This innovative approach combines aesthetic appeal with biomedical advantages, offering a personalized solution for wound care applications.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Escuela de Agronomía Facultad de Ciencias Agronómicas y de los Alimentos Pontificia Universidad Católica de ValparaísoSão Paulo State University (UNESP) School of Pharmaceutical Sciences Department of Bioprocesses and Biotechnology, SPSão Paulo State University (UNESP) School of Pharmaceutical Sciences Department of Drugs and Medicines, SPMessina Institute of Technology c/o Department of Chemical Biological Pharmaceutical and Environmental Sciences former Veterinary School University of Messina, Viale G. Palatucci sncChromaleont s.r.l. c/o Department of Chemical Biological Pharmaceutical and Environmental Sciences University of Messina, viale AnnunziataBioengineering & Biomaterials Group São Paulo State University (UNESP) School of Pharmaceutical Sciences, SPLaboratory of Magnetic Materials and Colloids Department of Analytical Chemistry Physical Chemistry and Inorganic Institute of Chemistry São Paulo State University (UNESP), SPFaculty of Philosophy Sciences and Languages of Ribeirão Preto University of São Paulo (USP), 3900 Bandeirantes Avenue, SPDepartment of Pharmaceutical-Biochemical Technology School of Pharmaceutical Sciences University of São PauloTerasaki Institute for Biomedical Innovation (TIBI), 11507 W Olympic BlvdSão Paulo State University (UNESP) School of Pharmaceutical Sciences Department of Bioprocesses and Biotechnology, SPSão Paulo State University (UNESP) School of Pharmaceutical Sciences Department of Drugs and Medicines, SPBioengineering & Biomaterials Group São Paulo State University (UNESP) School of Pharmaceutical Sciences, SPLaboratory of Magnetic Materials and Colloids Department of Analytical Chemistry Physical Chemistry and Inorganic Institute of Chemistry São Paulo State University (UNESP), SPFAPESP: 2015/11759–3FAPESP: 2021/06686–8FAPESP: 2023/17448–
Integrating autoencoders to improve fault classification with PV system insertion
No full textThe extensive integration of distributed generation (DG) units leads to significant changes in the operation of power distribution systems (PDS). Integrating DG units contributes to meeting the growing energy demand, diversifying the energy matrix, and reducing power grid losses. In contrast, they can affect conventional protection systems in power grids by altering current flow, which affects the characteristics, direction, and amplitude of short-circuit currents. Consequently, improper operation of protection equipment can cause false positives, negatively affecting the detection, classification, and reliability of the power grid. This study addresses fault classification in PDS, considering the extensive integration of DG units, specifically PV systems. PDS is evaluated at various levels of PV insertion using different fault scenarios modeled in the IEEE 34-bus test system. This includes five scenarios with variations in the PV system insertion. Autoencoders are applied during the pre-processing phase, while eleven different algorithms are used in the classification stage to identify fault types. They can improve the performance of the classification system by reducing the size of input signals and extracting the most relevant features. The results reveal that the K-nearest neighbor (KNN) and random forest (RF) algorithms demonstrate the best performance, maintaining a minimum accuracy of 95.42% in all scenarios.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Laboratory of Intelligent Systems Department of Electrical Engineering School of Engineering São Paulo State University (UNESP), São PauloEnvironmental Engineering Program Universidad Mariana, NariñoDepartment of Engineering School of Engineering and Sciences São Paulo State University (UNESP), São PauloLaboratory of Intelligent Systems Department of Electrical Engineering School of Engineering São Paulo State University (UNESP), São PauloDepartment of Engineering School of Engineering and Sciences São Paulo State University (UNESP), São PauloCNPq: 302896/2022-8CAPES: UNESP/PROPG 37/202
Evaluation of methods for estimating the growth of Nile tilapia raised in net cages
No full textA aquicultura é fundamental para suprir a demanda global por proteínas, com a tilápia-do-Nilo (Oreochromis niloticus) representando 68,36% da produção aquícola brasileira em 2024. Este estudo avaliou métodos para estimar o crescimento corporal dessa espécie em tanques-rede, comparando modelos empíricos clássicos - Coeficiente de Crescimento Linear (LNR), Coeficiente de Crescimento Específico (CCE), Coeficiente de Crescimento Diário (CCD) e Coeficiente de Crescimento Térmico (CCT) - com técnicas de aprendizado de máquina, como Máquinas de Vetores de Suporte (SVM - Support Vector Machines) e Redes Neurais Artificiais (RNA - Artificial Neural Networks). Utilizando dados de uma piscicultura no reservatório de Chavantes (SP), o CCT destacou-se entre os empíricos, com menor Raiz do Erro Quadrático Médio (RMSE - Root Mean Square Error: 16,69%) e alto índice de concordância (d: 0,97), enquanto o LNR não apresentou diferença estatisticamente significativa entre valores estimados e observados (t-test: t = 1,48). Já os modelos de aprendizado de máquina, principalmente o SVM com temperatura da água, superaram os empíricos (RMSE: 12,78%; Erro Médio de Viés - MBE - Mean Bias Error: 1,92%), mostrando maior precisão. Os resultados reforçam a importância de incluir variáveis ambientais, como temperatura, e sugerem que modelos híbridos (empíricos e inteligência artificial) podem otimizar a aquicultura moderna.Aquaculture plays a crucial role in meeting global protein demand, with Nile tilapia (Oreochromis niloticus) accounting for 68.36% of Brazilian aquaculture production in 2024. This study evaluated methods for estimating body growth of this species in cage farming systems, comparing classical empirical models - Linear Growth Rate (LNR), Specific Growth Rate (CCE), Daily Growth Rate (CCD), and Thermal Growth Coefficient (CCT) - with machine learning techniques, including Support Vector Machines (SVM) and Artificial Neural Networks (ANN). Using data from a fish farm in Chavantes reservoir (SP, Brazil), the CCT showed the best performance among empirical models with the lowest Root Mean Square Error (RMSE: 16.69%) and high agreement index (d: 0.97), while LNR showed no statistically significant difference between estimated and observed values (t-test: t = 1.48). Machine learning models, particularly SVM incorporating water temperature, outperformed empirical models (RMSE: 12.78%; Mean Bias Error - MBE: 1.92%), demonstrating higher accuracy. The results highlight the importance of including environmental variables like temperature and suggest that hybrid models (combining empirical and artificial intelligence approaches) could optimize modern aquaculture practices.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP: nº 2022/02756-4FAPESP: nº 2022/16545-5FAPESP: nº 2024/13914-5CNPQ: nº 101209/2024-
“Protecting the World's Crocodilians”—A review of Crocodiles of the World
No full textLaboratório de Paleontologia e Evolução de Ilha Solteira FEIS/UNESPPrograma de Pós-Graduação Em Biodiversidade IBILCE/UNESPLaboratório de Paleontologia e Evolução de Ilha Solteira FEIS/UNESPPrograma de Pós-Graduação Em Biodiversidade IBILCE/UNES
Epoxy as an Alternative Resin in Particleboard Production with Pine Wood Residues: Physical, Mechanical, and Microscopical Analyses of Panels at Three Resin Proportions
No full textGiven the construction challenges and the impacts of industrial waste generation and the implications of using chemical adhesives, this study aims to evaluate epoxy as an alternative resin, whose application in the production of wood particleboards is still underexplored. In this regard, its results were compared with those of widely used adhesives, such as urea-formaldehyde (UF). Pine wood particles were used, and epoxy resin was applied as a binder in 5%, 10%, and 15% proportions. Panels were manufactured under pressing parameters of 5 N/mm2 for 10 min at 110 °C. Physical and mechanical properties of panels were evaluated using Brazilian, European, and American standards. The results showed that epoxy resin is potentially convenient for the particleboard industry, as the 15% trait panels met the P4 class criteria in the Brazilian and European standards and D-2 for the American code, and the 10% trait panels achieved the M-3i class for the American document. Although 5% adhesive was insufficient to envelop wood particles, these traits with greater percentages reached high enveloping ratings in the scanning electron microscopy (SEM) test, making epoxy resin viable for the panel industry as a potential alternative to formaldehyde-based adhesives.Department of Civil Engineering Federal University of São Carlos (UFSCar), 235 km Washington Luis Highway, São CarlosDepartment of Civil Engineering São Paulo State University (UNESP) Ilha Solteira, 56 Brasil Sul AvenueDepartment of Architecture and Urbanism Federal University of Rio Grande do Norte (UFRN), Campus Universitário—Lagoa NovaDepartment of Civil Engineering Federal University of Rondônia (UNIR), 9.5 km BR 364 Highway, Porto VelhoFederal Institute of Education Science and Technology of Rondônia (IFRO), RO-257 Highway, AriquemesDepartment of Civil Engineering São Paulo State University (UNESP) Ilha Solteira, 56 Brasil Sul Avenu
Influence of aeration on the growth and cultivation parameters of different strains of lactobacillus in simulated vaginal fluid aiming at vaginal probiotic potential
No full textO câncer cervical é o tipo mais frequente de câncer ginecológico e envolve a divisão celular descontrolada e invasiva na cérvix do útero. Mais de 99% dos tumores de colo de útero apresentam sequências de DNA viral, e por isso, a infecção por vírus do papiloma humano (HPV) é considerada o principal agente etiológico dessa neoplasia. A microbiota vaginal saudável tem sido associada à predominância de diferentes espécies de Lactobacillus, sendo considerada uma situação de eubiose. A disbiose é a alteração da comunidade microbiana, com redução de Lactobacillus e aumento de outras espécies de bactérias anaeróbicas, condição associada muitas vezes a doenças ginecológicas, incluindo vaginoses, a infecção por HPV e, consequentemente, câncer cervical. A microbiota bacteriana é responsável pela síntese de ácido láctico e produção de H₂O₂, que juntos atuam como antissépticos, criando uma barreira contra agentes patogênicos. Ainda assim, existem muitos fatores a serem elucidados tanto em relação ao efeito protetor desses microrganismos, a sua ação em lesões pré-cancerígenas e cancerígenas, e seus fatores fisiológicos e de cultivo. O presente trabalho teve como objetivo avaliar a influência da aeração no crescimento de 5 espécies de Lactobacillus com potencial probiótico vaginal (L. crispatus, L. gasseri, L. johnsonii, L. acidophilus e L. rhamnosus), em fluido vaginal simulado (FVS). As cepas foram cultivadas em frascos Erlenmeyers de 125 mL contendo 25 mL de meio MRS (De Man, Rogosa e Sharpe) ou FVS, estático ou agitados (180 rpm) por até 72 h. A influência de diferentes carboidratos no meio de cultivo foi realizada pela adição de amido, glicose, galactose, frutose e lactose, a 5 g/L. Os resultados indicaram que as espécies de Lactobacillus apresentaram diferenças significativas em crescimento e metabolismo, influenciadas pelo meio de cultura e pelas condições de cultivo. O consumo de glicose foi intenso nas primeiras 24 horas, sendo maior no meio MRS. L. rhamnosus destacou-se pelo maior crescimento e eficiência na utilização de açúcares, especialmente em cultivos estáticos. L. crispatus gerou maior acidez, enquanto L. johnsonii cresceu melhor com frutose sob agitação. Todas as cepas consumiram mais de 90% dos monossacarídeos testados, mas não metabolizaram amido. O efeito da agitação variou conforme a cepa, mas, na maioria dos casos, não influenciou significativamente o consumo de açúcar e o pH final.Cervical cancer is the most common type of gynecological cancer and involves uncontrolled and invasive cell division in the cervix. More than 99% of cervical tumors contain viral DNA sequences, making human papillomavirus (HPV) infection the main etiological agent of this neoplasm. A healthy vaginal microbiota is associated with the predominance of different Lactobacillus species and is considered a state of eubiosis. Dysbiosis refers to an imbalance in the microbial community, with a reduction in Lactobacillus and an increase in other anaerobic bacterial species—a condition often linked to gynecological diseases, including vaginosis, HPV infection, and, consequently, cervical cancer. The bacterial microbiota is responsible for the synthesis of lactic acid and the production of H₂O₂, which together act as antiseptics, creating a barrier against pathogens. Nonetheless, many factors regarding the protective effect of these microorganisms remain to be elucidated, including their role in pre-cancerous and cancerous lesions, as well as their physiological and cultivation characteristics. This study aimed to evaluate the influence of aeration on the growth of five Lactobacillus species with vaginal probiotic potential (L. crispatus, L. gasseri, L. johnsonii, L. acidophilus, and L. rhamnosus) in simulated vaginal fluid (SVF). The strains were cultured in 125 mL Erlenmeyer flasks containing 25 mL of MRS (De Man, Rogosa, and Sharpe) medium or SVF, under static or shaken (180 rpm) conditions for up to 72 hours. The influence of different carbohydrates in the culture medium was assessed by adding starch, glucose, galactose, fructose, and lactose at 5 g/L. The results showed that the Lactobacillus species exhibited significant differences in growth and metabolism, influenced by the culture medium and cultivation conditions. Glucose consumption was intense during the first 24 hours, especially in the MRS medium. L. rhamnosus stood out for its higher growth and sugar utilization efficiency, particularly in static cultures. L. crispatus produced greater acidity, while L. johnsonii grew better with fructose under agitation. All strains consumed more than 90% of the tested monosaccharides but did not metabolize starch. The effect of agitation varied depending on the strain, but in most cases, it did not significantly affect sugar consumption or final pH.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CAPES: 00
Learning mathematics in EJA with the use of technology
No full textAs Tecnologias Digitais de Informação e Comunicação (TDIC) incorporadas à educação, diversifica e oportuniza melhorias para os processos de ensino e aprendizagem, por meio de diversas ferramentas e aplicações que estimulam e propiciam o desenvolvimento cognitivo e biopsicossocial nos diversos níveis e modalidades de ensino. As TDIC, em alguns sistemas e modalidades de ensino, possuem relevância a ponto de serem incorporadas ao currículo como conteúdos didáticos, de modo transversal ou também por meio da inserção de uma disciplina, como componente específico na matriz curricular. Tal situação é encontrada em municípios de uma microrregião do interior do Estado de São Paulo, nos quais a disciplina de tecnologia faz parte da matriz curricular do segmento da Educação de Jovens e Adultos (EJA) em suas respectivas redes públicas municipais de ensino. Esta pesquisa, de mestrado profissional em Docência para Educação Básica, objetivou analisar o impacto da utilização e acesso de tecnologias digitais no processo de aprendizagem matemática, bem como investigar a percepção dos estudantes da EJA em relação a aprendizagem com o desenvolvimento do produto educacional GOTEJA – que avalia o quanto as tecnologias digitais influenciam na aprendizagem da EJA – e, por conseguinte, desenvolver a autonomia do aluno da EJA por meio de ferramentas digitais e sistemas operacionais do computador. Sua metodologia aborda uma pesquisa qualitativa que elenca as percepçoes e relações sociais desses estudantes. A coleta de dados foi realizada por meio de questionários com estudantes e professores da EJA. O presente estudo está estruturado em etapas: 1) Estudos teóricos e documentais; 2) Coleta de dados inicial com docentes de Informática, professores polivalentes das unidades de ensino e discentes; 3) Análise qualitativa dos dados; 4) Desenvolvimento da versão preliminar do Guia de Atividades Tecnológicas da EJA; 5) Avaliação da versão preliminar do material pelos docentes das unidades; 6) Aplicação do Guia de Atividades; 7) Desenvolvimento da versão final do Guia. Conclui-se que a proposta da pesquisa foi alcançada uma vez que foi elaborado um produto educacional voltado para ação tecnológica de aprendizagem, além de que as ações educativas também foram contempladas por meio do levantamento de habilidades da matemática presentes na Base Nacional Comum Curricular (BNCC).Digital Information and Communication Technologies, incorporated into education, diversify and provide opportunities for improvements in teaching and learning processes through a variety of tools and applications that stimulate and foster cognitive and biopsychosocial development at various levels and modalities of education. In some educational systems and modalities, digital technologies are so relevant that they are incorporated into the curriculum as teaching content, either cross-curricularly or through the inclusion of a specific subject as a component of the curriculum. This situation is found in municipalities in a microregion in the interior of the state of São Paulo, where technology is part of the curriculum for Youth and Adult Education in their respective municipal public school systems. This professional master's degree in Basic Education Teaching aimed to analyze the impact of the use and access to digital technologies on the mathematical learning process, as well as to investigate the perceptions of Youth and Adult Education students regarding learning through the development of the educational product GOTEJA—which assesses the extent to which digital technologies influence learning—and, consequently, to develop student autonomy through digital tools and computer operating systems. Its methodology is a qualitative research that lists the perceptions and social relationships of these students. Data collection was conducted through questionnaires with Youth and Adult Education students and teachers. This study is structured in stages: 1) Theoretical and documentary studies; 2) Initial data collection with IT teachers, multidisciplinary teachers from the teaching units, and students; 3) Qualitative data analysis; 4) Development of a preliminary version of the Technological Activities Guide; 5) Evaluation of the preliminary version of the material by the unit teachers; 6) Application of the Activities Guide; 7) Development of the final version of the Guide. It is concluded that the research proposal was achieved since an educational product focused on technological learning action was developed, in addition to the fact that educational actions were also contemplated through the survey of mathematics skills present in the National Common Curricular Base
Redescription of Tachardiella ourinhensis Hempel, 1937 (Hemiptera: Kerriidae) and its transfer to Neotachardiella gen. nov., with descriptions of two new species of Neotachardiella on Myrtaceae from Brazil and Uruguay
No full textThe lac insect, Tachardiella ourinhensis Hempel, 1937 (Hemiptera: Coccomorpha: Kerriidae), is redescribed and illustrated based on type material, and transferred to Neotachardiella Kondo, Peronti & Pacheco da Silva, gen. nov. as Neotachardiella ourinhensis (Hempel), comb. nov. Additionally, two new species, Neotachardiella charruarum Kondo, Peronti & Pacheco da Silva, sp. nov. and Neotachardiella nangapire Kondo, Peronti & Pacheco da Silva, sp. nov., are described and illustrated based on adult females collected in Uruguay and Brazil, respectively, on various species of Myrtaceae. In addition, the first-instar nymph of N. charruarum is described and illustrated. A lectotype is designated for T. ourinhensis based on slides mounted from type material deposited at the Instituto Biológico de São Paulo, Brazil. A taxonomic key to separate all known genera of the family Kerriidae and a key to separate the species of Neotachardiella are provided.Corporación Colombiana de Investigación Agropecuaria-Agrosavia Centro de Investigación Palmira, Diagonal a la intersección de la Carrera 36A con Calle 23, ValleInstituto Biología Sección Entomología Facultad de Ciencias Universidad de la República, IguáDepartamento de Protección Vegetal Unidad de Entomología Facultad de Agronomía Universidad de la República, GarzónEmbrapa Trigo, RSDepartamento de Fitossanidade Faculdade de Ciências Agrárias e Veterinárias-FCAV Universidade Estadual Paulista “Júlio de Mesquita” Filho-UNESP, SPDepartamento de Fitossanidade Faculdade de Ciências Agrárias e Veterinárias-FCAV Universidade Estadual Paulista “Júlio de Mesquita” Filho-UNESP, S