Attachment-related avoidance and anxiety have repeatedly been associated with poorer adjustment in various social, emotional, and behavioral domains. We examined 2 domains in which avoidant individuals might be better equipped than their less avoidant peers to succeed and be satisfied--professional singles tennis and computer science. These fields may reward self-reliance, independence, and the ability to work without proximal social support from loved ones. In study 1, we followed 58 professional singles tennis players for 16 months and found that scores on attachment-related avoidance predicted a higher ranking, above and beyond the contributions of training and coping resources. In study 2, we sampled 100 students and found that those who scored higher on avoidance were happier with their choice of computer science as a career than those who scored lower on avoidance. Results are discussed in relation to the possible adaptive functions of certain personality characteristics often viewed as undesirable.
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JMIR Form Res
January 2025
ICMR-National Institute for Research in Digital Health and Data Science, Ansari Nagar, New Delhi, 110029, India, 91 7840870009.
Background: Verbal autopsy (VA) has been a crucial tool in ascertaining population-level cause of death (COD) estimates, specifically in countries where medical certification of COD is relatively limited. The World Health Organization has released an updated instrument (Verbal Autopsy Instrument 2022) that supports electronic data collection methods along with analytical software for assigning COD. This questionnaire encompasses the primary signs and symptoms associated with prevalent diseases across all age groups.
View Article and Find Full Text PDFGenes Chromosomes Cancer
January 2025
Institute of Human Genetics, Ulm University and Ulm University Medical Center, Ulm, Germany.
Mature aggressive B-cell lymphomas, such as Burkitt lymphoma (BL) and Diffuse large B-cell lymphoma (DLBCL), show variations in microRNA (miRNA) expression. The entity of High-grade B-cell lymphoma with 11q aberration (HGBCL-11q) shares several biological features with both BL and DLBCL but data on its miRNA expression profile are yet scarce. Hence, this study aims to analyze the potential differences in miRNA expression of HGBCL-11q compared to BL and DLBCL.
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June 2025
School of Computer Science and Engineering, Vellore Institute of Technology, Vandalur - Kelambakkam Road, Chennai, 600 127 Tamil Nadu, India.
This study introduces a framework that integrates AI-driven Game-Based Language Teaching (GBLT) with advanced neuroscience to transform language education for visually impaired learners. Built on the principles of neuroplasticity and epigenetics, the approach leverages educational psychology with the help of adaptive AI to deliver personalized, gamified learning experiences that reshape neural pathways, improve memory retention, and strengthen emotional resilience. By fostering low-stress, immersive environments, it triggers positive epigenetic changes, enhancing long-term cognitive flexibility.
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June 2025
Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune 411044, India.
Recent advancements in artificial intelligence (AI) have increased interest in intelligent transportation systems, particularly autonomous vehicles. Safe navigation in traffic-heavy environments requires accurate road scene segmentation, yet traditional computer vision methods struggle with complex scenarios. This study emphasizes the role of deep learning in improving semantic segmentation using datasets like the Indian Driving Dataset (IDD), which presents unique challenges in chaotic road conditions.
View Article and Find Full Text PDFJ Pathol Inform
January 2025
Department of Computer Science, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya-shi, Aichi 466-8555, Japan.
We propose a method of to improve an attention mechanism in a whole slide image (WSI) classifier. Generally, only some regions in a WSI are useful for lesion classification, and the WSI classifier is required to find and focus on such regions for the classification. Multiple instance learning and hierarchical representation learning are widely employed for WSI processing and both use attention mechanisms to automatically find the useful regions and then conduct the class prediction.
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