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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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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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Automated classification of nebulae using deep learning & machine learning for enhanced discovery

Nair et al. | Feb 01, 2024

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

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Starts and Stops of Rhythmic and Discrete Movements: Modulation in the Excitability of the Corticomotor Tract During Transition to a Different Type of Movement

Lim et al. | Aug 27, 2018

Starts and Stops of Rhythmic and Discrete Movements: Modulation in the Excitability of the Corticomotor Tract During Transition to a Different Type of Movement

Control of voluntary and involuntary movements is one of the most important aspects of human neurological function, but the mechanisms of motor control are not completely understood. In this study, the authors use transcranial magnetic stimulation (TMS) to stimulate a portion of the motor cortex while subjects performed either discrete (e.g. throwing) or rhythmic (e.g. walking) movements. By recording electrical activity in the muscles during this process, the authors showed that motor evoked potentials (MEPs) measured in the muscles during TMS stimulation are larger in amplitude for discrete movements than for rhythmic movements. Interestingly, they also found that MEPs during transitions between rhythmic and discrete movements were nearly identical and larger in amplitude than those recorded during either rhythmic or discrete movements. This research provides important insights into the mechanisms of neurological control of movement and will serve as the foundation for future studies to learn more about temporal variability in neural activity during different movement types.

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Determining the Effects of Fibroblast Growth Factor 2 on the Regenerative Abilities of Echinometra lucunter Sea Urchins

Kisling et al. | Feb 12, 2019

Determining the Effects of Fibroblast Growth Factor 2 on the Regenerative Abilities of Echinometra lucunter Sea Urchins

As humans, not all our body organs can adequately regenerate after injury, an ability that declines with age. In some species, however, regeneration is a hallmark response that can occur limitless numbers of time throughout the life of an organism. Understanding how such species can regenerate so efficiently is of central importance to regenerative medicine. Sea urchins, unlike humans, can regenerate their spinal tissue after injury. Here the authors study the effect of a growth factor, FGF2, on sea urchin regeneration but find no conclusive evidence for a pro-regenerative effect after spinal tissue injury.

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Zinc-related Treatments Combined with Chloroquine and Gemcitabine for Treating Pancreatic Cancer

Ma et al. | Sep 11, 2021

Zinc-related Treatments Combined with Chloroquine and Gemcitabine for Treating Pancreatic Cancer

Pancreatic cancer is one of the deadliest cancers, with a 10% 5-year survival rate. The authors studied various dosages of TPEN and zinc in combination with Chloroquine and Gemcitabine as treatments to reduce cell proliferation. Results showed that when combined with Chloroquine and Gemcitabine, zinc and TPEN both significantly lowered cell proliferation compared to Gemcitabine, suggesting a synergistic effect that resulted in a more cytotoxic treatment. Further research and clinical trials on this topic are needed to determine whether this could be a viable treatment for pancreatic cancer.

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