2,004 research outputs found

    In the Footsteps of Monsieur Vincent: Diary of an Ordinary Professor

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    Annalisa Sacca is a professor of Italian language and literature who uses her classroom to introduce her students to “a culture of awareness.” Her goal is to “educate [her] students’ hearts and minds and also to empower them.” She explains how Vincent de Paul’s method of empowering and training people to work against global poverty is still relevant today and how she tries to follow his example. She describes the many forms of service she and her students have undertaken. She also discusses “language of the heart,” her term that encompasses Vincent’s affective love and Vincentian values. She tries to instill it in students through ordinary classroom practice, service components to courses, internships, and a special degree program, the Master in Global Development. This program is a joint project of St. John’s University and Caritas in Rome

    A novel and alternative in vitro method using microwave to study the epithelial-stromal interactions

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    The goal of the present work was to obtain a simple and reproducible experimental model that would maintain the characteristics of the extracellular physiological environment of breast epithelial cells, both in factors as well as stromal structure, on which we could grow and evaluate changes of normal and tumor breast cells. 3T3-L1 pre-adipocytes (breast stromal cell model) were cultured and irradiated in a microwave oven at different times and potencies. In order to lose their proliferation ability, cells had to be irradiated twice at 650 Watts with a two-minute pulse each. The characteristics of the treated stromal support were analyzed for cell morphology, presence of DNA and proteins. We then evaluated on this support the effect on proliferation and migration of both normal and tumor - murine and human - breast epithelial cells. Both cell types increased their proliferation, while only tumor cells increased migration, thus improving their metastatic capacity. We believe this is a new and simple experimental method of studying epithelial-stromal cell interaction.Fil: Sacca, Paula Alejandra. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental. FundaciĂłn de Instituto de BiologĂ­a y Medicina Experimental. Instituto de BiologĂ­a y Medicina Experimental; ArgentinaFil: Pistone Creydt, Virginia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental. FundaciĂłn de Instituto de BiologĂ­a y Medicina Experimental. Instituto de BiologĂ­a y Medicina Experimental; ArgentinaFil: Tesone, Amelia Julieta. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental. FundaciĂłn de Instituto de BiologĂ­a y Medicina Experimental. Instituto de BiologĂ­a y Medicina Experimental; ArgentinaFil: Calvo, Juan Carlos. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental. FundaciĂłn de Instituto de BiologĂ­a y Medicina Experimental. Instituto de BiologĂ­a y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de QuĂ­mica BiolĂłgica; Argentin

    Data Augmentation and Transfer Learning Approaches Applied to Facial Expressions Recognition

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    The face expression is the first thing we pay attention to when we want to understand a person's state of mind. Thus, the ability to recognize facial expressions in an automatic way is a very interesting research field. In this paper, because the small size of available training datasets, we propose a novel data augmentation technique that improves the performances in the recognition task. We apply geometrical transformations and build from scratch GAN models able to generate new synthetic images for each emotion type. Thus, on the augmented datasets we fine tune pretrained convolutional neural networks with different architectures. To measure the generalization ability of the models, we apply extra-database protocol approach, namely we train models on the augmented versions of training dataset and test them on two different databases. The combination of these techniques allows to reach average accuracy values of the order of 85\% for the InceptionResNetV2 model.Comment: The 11th International Conference on Artificial Intelligence, Soft Computing and Applications (AIAA 2021
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