The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
Read More...Floor level estimation using MEMS pressure sensors
The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
Read More...Investigating the impact of electrocardiography biofeedback on POTS symptom management
The authors test electrocardiography biofeedback as a treatment for individuals with Postural Orthostatic Tachycardia Syndrome.
Read More...The impact of genetic analysis on the early detection of colorectal cancer
Although the 5-year survival rate for colorectal cancer is below 10%, it increases to greater than 90% if it is diagnosed early. We hypothesized from our research that analyzing non-synonymous single nucleotide variants (SNVs) in a patient's exome sequence would be an indicator for high genetic risk of developing colorectal cancer.
Read More...Collaboration beats heterogeneity: Improving federated learning-based waste classification
Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.
Read More...A spatiotemporal analysis of OECD member countries on sugar consumption and labor force participation
In this article the authors look at sugar consumption and the relationship to productivity in the work/labor force.
Read More...Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections
The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.
Read More...Administration of Stephania tetrandra to Drosophila melanogaster to create obsessive compulsive disorder model
In this study the authors looked at the extract of Stephania tetrandra and its impact on symptoms related to obsessive compulsive disorder in fruit flies.
Read More...Evaluating the feasibility of SMILES-based autoencoders for drug discovery
The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.
Read More...Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.
Read More...Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism
The Wnt signaling pathway, known to coordinate important aspects of cellular homeostasis ranging from differentiation, proliferation, migration, and much more, is dysregulated in many human diseases. This study demonstrates that aminomethylphosphonic acid, which is the main metabolite found in the common herbicide Glyphosate, is toxic to planaria and capable of binding to canonical Wnt proteins.
Read More...Search articles by title, author name, or tags