5 results on '"Idalia Vargas-Maya Naurú"'
Search Results
2. Intellectual Curve Scene Text Detection from Natural Images Using MSER Descriptor Based Region Segmentation Approach
- Author
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C. Teixeira Samuel, Kalita Jahnabi, Wang Huayuan, Qin Weiwei, Shi Yingying, Xia Mingrong, Kumar Deepak, Yang Miaomiao, Páramo-Pérez Itzel, Elizabeth Reyes-Martínez Juana, Chandra Remya, S. Lopes Daiana, SIngh Ramandeep, Padilla-Vaca Felipe, Tamayo-Nuñez Jessica, Anaya-Velázquez Fernando, de Melo Rodrigues Veridiana, Chetia Dipak, Idalia Vargas-Maya Naurú, Li Gai, Franco Bernardo, Zhang Jiewen, Sun Ruihua, Liliana España-Sánchez Beatríz, Zhang Haohan, Zhao Jing, Abdizadeh Tooba, Vijayan Dileep, N.C. Gimenes Sarah, Sun Yajing, Banerjee Rintu, de la Mora Javier, Abdizadeh Rahman, Jiménez-Charris Eliécer, Rangel-Serrano Ángeles, Ma Limin, Solano-Redondo Luis, Rudrapal Mithun, Hadizadeh Farzin, and Montealegre-Sánchez Leonel
- Subjects
Control and Optimization ,Computer Networks and Communications ,Computer science ,business.industry ,Natural (music) ,Segmentation ,Pattern recognition ,Text detection ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Computer Science Applications - Abstract
Background: A novel method to detect the text region from the natural image using the discriminative deep feature of text regions is presented with deep learning concept in this manuscript. Objective: Curve Text Detection (CTD) from the natural image is generally based on two different tasks: learning of text data and text region detection. In the learning of text data, the goal is to train the system with a sample of letters and natural images, while, in the text region detection, the aim is to confirm whether the detected regions are text region or not. The emphasis of this research is on the development of deep learning algorithm. Methods: A novel approach has been proposed to detect the text region from natural images which simultaneously tackles three combined challenges: 1) pre-processing of the image without losing text region; 2) appropriate segmentation of text region using their strokes, and 3) training of data. In pre-processing, image enhancement and binarization are done then morphological operations are defined with the Maximally Stable Extremal Region (MSER) based segmentation technique which operates on the basis of stroke region of text and then finds out the (Speed Up Robust Feature) SURF key point from those regions. Results: Based on the SURF feature, text region is detected from the images using a trained structure of Artificial Neural Network (ANN) which is based on deep learning mechanism. Conclusion: CTW-1500 dataset is used to simulate the proposed work and the parameters like Precision, Recall, F-Measure (H-mean), Execution time, Accuracy and Error Rate are computed and are compared with the existing work to depict the effectiveness of the work.
- Published
- 2021
- Full Text
- View/download PDF
3. Catalases in the pathogenesis of Sporothrix schenckii research.
- Author
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Idalia Vargas-Maya, Naurú, Olmedo-Monfil, Vianey, Humberto Ramírez-Prado, Jorge, Reyes-Cortés, Ruth, Padilla-Vaca, Felipe, and Franco, Bernardo
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REACTIVE oxygen species ,PATHOGENIC fungi ,CATALASE ,STARTLE reaction ,MYCOSES ,DRUG efficacy ,ECHINOCANDINS - Abstract
Pathogenic fungal infection success depends on the ability to escape the immune response. Most strategies for fungal infection control are focused on the inhibition of virulence factors and increasing the effectiveness of antifungal drugs. Nevertheless, little attention has been focused on their physiological resistance to the host immune system. Hints may be found in pathogenic fungi that also inhabit the soil. In nature, the saprophyte lifestyle of fungi is also associated with predators that can induce oxidative stress upon cell damage. The natural sources of nutrients for fungi are linked to cellulose degradation, which in turn generates reactive oxygen species (ROS). Overall, the antioxidant arsenal needed to thrive both in free-living and pathogenic lifestyles in fungi is fundamental for success. In this review, we present recent findings regarding catalases and oxidative stress in fungi and how these can be in close relationship with pathogenesis. Additionally, special focus is placed on catalases of Sporothrix schenckii as a pathogenic model with a dual lifestyle. It is assumed that catalase expression is activated upon exposure to H
2 O2 , but there are reports where this is not always the case. Additionally, it may be relevant to consider the role of catalases in S. schenckii survival in the saprophytic lifestyle and why their study can assess their involvement in the survival and therefore, in the virulence phenotype of different species of Sporothrix and when each of the three catalases are required. Also, studying antioxidant mechanisms in other isolates of pathogenic and free-living fungi may be linked to the virulence phenotype and be potential therapeutic and diagnostic targets. Thus, the rationale for this review to place focus on fungal catalases and their role in pathogenesis in addition to counteracting the effect of immune system reactive oxygen species. Fungi that thrive in soil and have mammal hosts could shed light on the importance of these enzymes in the two types of lifestyles. We look forward to encouraging more research in a myriad of areas on catalase biology with a focus on basic and applied objectives and placing these enzymes as virulence determinants. [ABSTRACT FROM AUTHOR]- Published
- 2022
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- View/download PDF
4. Escherichia coli transcription factors of unknown function: sequence features and possible evolutionary relationships.
- Author
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Duarte-Velázquez, Isabel, de la Mora, Javier, Humberto Ramírez-Prado, Jorge, Aguillón-Bárcenas, Alondra, Tornero-Gutiérrez, Fátima, Cordero-Loreto, Eugenia, Anaya-Velázquez, Fernando, Páramo-Pérez, Itzel, Rangel-Serrano, Ángeles, Rodrigo Muñoz-Carranza, Sergio, Eduardo Romero-González, Oscar, Rafael Cardoso-Reyes, Luis, Alberto Rodríguez-Ojeda, Ricardo, Manuel Mora-Montes, Héctor, Idalia Vargas-Maya, Naurú, Padilla-Vaca, Felipe, and Franco, Bernardo
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TRANSCRIPTION factors ,ESCHERICHIA coli ,BINDING sites ,POINT set theory ,GENE expression - Abstract
Organisms need mechanisms to perceive the environment and respond accordingly to environmental changes or the presence of hazards. Transcription factors (TFs) are required for cells to respond to the environment by controlling the expression of genes needed. Escherichia coli has been the model bacterium for many decades, and still, there are features embedded in its genome that remain unstudied. To date, 58 TFs remain poorly characterized, although their binding sites have been experimentally determined. This study showed that these TFs have sequence variation at the third codon position G+C content but maintain the same Codon Adaptation Index (CAI) trend as annotated functional transcription factors. Most of these transcription factors are in areas of the genome where abundant repetitive and mobile elements are present. Sequence divergence points to groups with distinctive sequence signatures but maintaining the same type of DNA binding domain. Finally, the analysis of the promoter sequences of the 58 TFs showed A+T rich regions that agree with the features of horizontally transferred genes. The findings reported here pave the way for future research of these TFs that may uncover their role as spare factors in case of lose-of-function mutations in core TFs and trace back their evolutionary history. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
5. Escherichia coli as a Model Organism and Its Application in Biotechnology
- Author
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Idalia, Vargas-Maya Naurú and Bernardo, Franco
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education ,natural sciences ,humanities - Published
- 2017
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