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Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance

Das et al. | Apr 19, 2021

Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance

Diagnosing of Autism Spectrum Disorder (ASD) using tools developed in the West is challenging in the Indian setting due to a huge diversity in sociocultural and economic backgrounds. Here, the authors developed a home-based, audiovisual game app (Autest) suitable for ASD risk assessment in Indian children under 10 years of age. Ratings suggested that the tool is effective and can reduce social inhibition and facilitate assessment. Further usage and development of Autest can improve risk assessment and early intervention measures for children with ASD in India.

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Pollination Patterns by Green-Backed Firecrown Hummingbirds

Freeland et al. | May 28, 2020

Pollination Patterns by Green-Backed Firecrown Hummingbirds

The Green-backed Firecrown hummingbird is an essential pollinator in the temperate rainforests of southern South America. However, little is known about the ecology of these birds. Authors examined the foraging patterns of these birds identifying interesting differences in foraging patterns among season, age and sex.

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Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Levy et al. | Oct 13, 2014

Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Coronary artery bypass grafts are a common technique to treat coronary heart disease. The authors compared the efficacy of suturing and stapling techniques using an artificial heart pump and silicone tubing and found that suturing, while more time and skill intensive, held pressure in the tubing better than stapling.

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Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Ganesa et al. | Jul 26, 2026

Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Large language models are increasingly used to solve math problems, but their ability to handle multi-step reasoning remains uncertain. In this study, students tested whether different prompting styles could improve LLM accuracy on challenging AIME math questions and found that detailed step-by-step solutions did not significantly outperform simpler prompts. These results suggest that improving LLM mathematical reasoning may require deeper model-level advances rather than changes in prompting style alone.

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