Browsing by Issue Date, starting with "2025-01-17"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Medicines, the haute couture of pharmacy: a summer camp for high school studentsPublication . Fonseca, CustódiaSince ancient times, man has prepared medicines and used them in healing practices. Therefore, there has always been a great interest in the part of people in general and students in particular about medicines. The "Medicines, the Haute Couture of Pharmacy" summer camp has the objective to promote and improve the literacy in medicines and make participants aware of, and become interested in, pharmaceutical sciences. It is a five-day summer camp where high-school students learn about medicines, how they are constituted, how they work, and how they are formulated. This occurs through hands-on synthesis and isolation of bioactive molecules, namely, acetylsalicylic acid, ibuprofen, and limonene, and subsequent formulation of pharmaceutical forms such as tablets, capsules, suppositories, and creams. Participant survey responses showed that they are very satisfied with this summer camp and the knowledge acquired, which may help them make their future career choices.
- GLAC-Unet: global-local active contour loss with an efficient u-shaped architecture for multiclass medical image segmentationPublication . Trinh, Minh Nhat; Tran, Thi-Thao; Nham, Do-Hai-Ninh; Lo, Men-Tzung; Pham, Van-TruongThe field of medical image segmentation powered by deep learning has recently received substantial attention, with a significant focus on developing novel architectures and designing effective loss functions. Traditional loss functions, such as Dice loss and Cross-Entropy loss, predominantly rely on global metrics to compare predictions with labels. However, these global measures often struggle to address challenges such as occlusion and nonuni-form intensity. To overcome these issues, in this study, we propose a novel loss function, termed Global-Local Active Contour (GLAC) loss, which integrates both global and local image features, reformulated within the Mumford-Shah framework and extended for multiclass segmentation. This approach enables the neural network model to be trained end-to-end while simultaneously segmenting multiple classes. In addition to this, we enhance the U-Net architecture by incorporating Dense Layers, Convolutional Block Attention Modules, and DropBlock. These improvements enable the model to more effectively combine contextual information across layers, capture richer semantic details, and mitigate overfitting, resulting in more precise segmentation outcomes. We validate our proposed method, namely GLAC-Unet, which utilizes the GLAC loss in conjunction with our modified U-shaped architecture, on three biomedical segmentation datasets that span a range of modalities, including two-dimensional and three-dimensional images, such as dermoscopy, cardiac magnetic resonance imaging, and brain magnetic resonance imaging. Extensive experiments demonstrate the promising performance of our approach, achieving a Dice score (DSC) of 0.9125 on the ISIC-2018 dataset, 0.9260 on the Automated Cardiac Diagnosis Challenge (ACDC) 2017, and 0.927 on the Infant Brain MRI Segmentation Challenge 2019. Furthermore, statistical significance testing with p-values consistently smaller than 0.05 on the ISIC-2018 and ACDC datasets confirms the superior performance of the proposed method compared to other state-of-the-art models. These results highlight the robustness and effectiveness of our multiclass segmentation technique, underscoring its potential for biomedical image analysis.
- Psychometric examination of the proposed specifiers for conduct disorder self-report (PSCD) among an adult community sample from BrazilPublication . Pechorro, Pedro; Bonfá-Araujo, Bruno; Baptista, Makilim Nunes; Nunes, Cristina; DeLisi, Matt; Salekin, Randall T.The Proposed Specifiers for Conduct Disorder (PSCD) is a promising novel scale that measures psychopathic traits and includes an additional conduct disorder factor that taps the antisocial dimension of psychopathy. The current study sought to broaden the application of PSCD by examining the factor structure, convergent and discriminant validity, and connections to delinquency in a young adult sample ( N = 450; M = 31.91 years, SD = 13.02 years) obtained from the Brazilian community. Participants completed a self-report version of the PSCD along with other theoretically meaningful psychometric measures. Results supported a four-factor intercorrelated factor structure, with male participants scoring significantly higher than female participants on the PSCD total, grandiose-manipulative (GM), callous-unemotional (CU), daring-impulsive (DI), and conduct disorder (CD) factors. The four factors of the PSCD mainly presented positive, moderate to high significant inter-correlations and adequate reliability. The convergent validity with measures of the dark tetrad of personality, difficulties in emotion regulation, and self-reported delinquency also revealed positive moderate significant associations. Our findings support the use of the PSCD as a promising short, time-effective self-report measure of psychopathic traits in young adults.