The authors test how the size-segregation theory applies to the behavior of hollow and irregular-shaped objects.
Read More...The effect of circumference on the segregation of objects in a mixture
The authors test how the size-segregation theory applies to the behavior of hollow and irregular-shaped objects.
Read More...The juxtaposition of anatomy and physics in the eye
People are quick to accept the assumption that a light will appear dimmer the farther away they are, citing the inverse square relationship that illuminance obeys as rationale. However, repeated observations of light sources maintaining their brightness over large distances prompted us to explore how the brightness, or perceived illuminance of a light varies with the viewing distance from the object. We hypothesized that since both the illuminance of the light source and image size decrease at the same rate, then the concentration, or intensity of the image remains unchanged, and subsequently the perceived illuminance.
Read More...A comparison of use of the mobile electronic health record by medical providers based on clinical setting
The electronic health record (EHR), along with its mobile application, has demonstrated the ability to improve the efficiency and accuracy of health care delivery. This study included data from 874 health care providers over a 12-month period regarding their usage of mobile phone (EPICĀ® Haiku) and tablet (EPICĀ® Canto) mEHR. Ambulatory and inpatient care providers had the greatest usage levels over the 12-month period. Awareness of workflow allows for optimization of mEHR design and implementation, which should increase mEHR adoption and usage, leading to better health outcomes for patients.
Read More...Identifying Neural Networks that Implement a Simple Spatial Concept
Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.
Read More...One-step photochemical crosslinking of native proteins is feasible in tyrosine-rich bovine serum albumin
In this study, the authors develop a new hydrogel using photochemical crosslinking with bovine serum albumin and methylene blue. They find that this new hydrogel has some useful applications!
Read More...Caffeine: Does Drinking Coffee Alter Performance and RPE Levels of a Teenage Athlete in both Aerobic and Anaerobic Exercises?
Caffeine is widely consumed across the globe and is most appreciated for its effects as a stimulant. Here the authors investigate whether caffeine consumption affects performance during endurance or strength training. Their results suggest that caffeine consumption enhances endurance training, but not strength training.
Read More...The Effects of L-glutamate, L-glutamine, and L-aspartic Acid on the Amylase Production of E. coli Transformed With pAmylase
Human amylase is important to digestion and has broad applications for therapeutic use in patients with pancreatic insufficiency. The authors present a method to increase amylase production in E. coli by adding the amino acids L-glutamate and L-glutamine.
Read More...Mitigating open-set misclassification in a colorectal cancer detecting neural network
The authors develop a machine learning method to reduce misclassification of objects in safety-critical applications such as medical diagnosis.
Read More...Calculating the dynamic viscosity of a fluid using image processing of a falling ball
The authors measure changes in the viscosity of glycerol with increasing temperature using the falling ball approach.
Read More...The effect of activation function choice on the performance of convolutional neural networks
With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.
Read More...