In this study, the authors conduct a series of experiments within an elevator traveling on an angle to determine if Einstein's Equivalency Principle and motion vector decomposition can be used to calculate the angle of inclination.
Read More...Extending Einstein’s elevator thought experiment to multiple spatial dimensions at the Luxor Hotel & Casino
In this study, the authors conduct a series of experiments within an elevator traveling on an angle to determine if Einstein's Equivalency Principle and motion vector decomposition can be used to calculate the angle of inclination.
Read More...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.
Read More...Differences in the effect of copper sulfate on the mortality rate of Ostracod and Daphnia
Chemical pollution can have significant effects on freshwater organisms. In this study, the effect of copper sulfate on the survival of Daphnia pulex and Ostracoda was investigated.
Read More...Pruning replay buffer for efficient training of deep reinforcement learning
Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.
Read More...Effects of different synthetic training data on real test data for semantic segmentation
Semantic segmentation - labelling each pixel in an image to a specific class- models require large amounts of manually labeled and collected data to train.
Read More...A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting
Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.
Read More...The extent to which storefront alcohol advertising differs by community profile in Michigan
Here, recognizing that alcohol manufacturers may target ethnic minorities and youths with specific forms of advertisements based on previous studies, the authors considered how alcohol storefronts differ depending on the community they are located in. Specifically, they looked at differences between Metro-Dtroit suburban communities of high- and low-incomes. They found that alcohol stores in the low-income areas had more and larger alcohol and malt liquor advertisements per store along with being within 1,000 feet of a school.
Read More...Friend or foe: Using DNA barcoding to identify arthropods found at home
Here the authors used morphological characters and DNA barcoding to identify arthropods found within a residential house. With this method they identified their species and compared them against pests lists provided by the US government. They found that none of their identified species were considered to be pests providing evidence against the misconception that arthropods found at home are harmful to humans. They suggest that these methods could be used at larger scales to better understand and aid in mapping ecosystems.
Read More...The analysis of the viral transmission and structural interactions between the HIV-1 envelope glycoprotein and the lymphocyte receptor integrin α4β7
The Human Immunodeficiency Virus (HIV) infects approximately 40 million people globally, and one million people die every year from Acquired Immune Deficiency Syndrome (AIDS)-related illnesses. This study examined the interactions between the HIV-1 envelope glycoprotein gp120 and the human lymphocyte receptor integrin α4β7, the putative first long-range receptor for the envelope glycoprotein of the virus in mucosal tissues. Presented data support the claim that the V1 loop is involved in the binding between α4β7 and the HIV-1 envelope glycoprotein through molecular dockings.
Read More...Evaluating TensorFlow image classification in classifying proton collision images for particle colliders
In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.
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