Insulin infusion patches are a common way for diabetics to receive medication. The durability of two different patch adhesives was compared on artificial skin with and without artificial sweat.
Read More...Durability of the Continuous Subcutaneous Insulin Infusion (CSII) Patch Adhesive
Insulin infusion patches are a common way for diabetics to receive medication. The durability of two different patch adhesives was compared on artificial skin with and without artificial sweat.
Read More...Characterization and Phylogenetic Analysis of the Cytochrome B Gene (cytb) in Salvelinus fontinalis, Salmo trutta and Salvelinus fontinalis X Salmo trutta Within the Lake Champlain Basin
Recent declines in the brook trout population of the Lake Champlain Basin have made the genetic screening of this and other trout species of utmost importance. In this study, the authors collected and analyzed 21 DNA samples from Lake Champlain Basin trout populations and performed a phylogenetic analysis on these samples using the cytochrome b gene. The findings presented in this study may influence future habitat decisions in this region.
Read More...The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil
Environmental disasters such as the Deepwater Horizon oil spill can be devastating to ecosystems for long periods of time. Safer, cheaper, and more effective methods of oil clean-up are needed to clean up oil spills in the future. Here, the authors investigate the ability of natural ocean algae to process crude oil into less toxic chemicals. They identify Coccochloris elabens as a particularly promising algae for future bioremediation efforts.
Read More...A machine learning approach for abstraction and reasoning problems without large amounts of data
While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.
Read More...A Data-Centric Analysis of “Stop and Frisk” in New York City
The death of George Floyd has shed light on the disproportionate level of policing affecting non-Whites in the United States of America. To explore whether non-Whites were disproportionately targetted by New York City's "Stop and Frisk" policy, the authors analyze publicly available data on the practice between 2003-2019. Their results suggest African Americans were indeed more likely to be stopped by the police until 2012, after which there was some improvement.
Read More...Optimizing tennis strategy: a data-driven analysis of point importance
The authors looked at the importance of different point breakdowns needed to win in a game of tennis.
Read More...Effects of data amount and variation in deep learning-based tuberculosis diagnosis in chest X-ray scans
The authors developed and tested machine learning methods to diagnose tuberculosis from pulmonary X-ray scans.
Read More...Locating sources of a high energy cosmic ray extensive air shower using HiSPARC data
Using the data provided by the University of Twente High School Project on Astrophysics Research with Cosmics (HiSPARC), an analysis of locations for possible high-energy cosmic ray air showers was conducted. An example includes an analysis conducted of the high-energy rain shower recorded in January 2014 and the use of Stellarium™ to discern its location.
Read More...Comparing model-centric and data-centric approaches to determine the efficiency of data-centric AI
In this study, three models are used to test the hypothesis that data-centric artificial intelligence (AI) will improve the performance of machine learning.
Read More...Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification
The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.
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