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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

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.

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Machine learning on crowd-sourced data to highlight coral disease

Narayan et al. | Jul 26, 2021

Machine learning on crowd-sourced data to highlight coral disease

Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.

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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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People’s Preference to Bet on Home Teams Even When Losing is Likely

Weng et al. | Mar 10, 2020

People’s Preference to Bet on Home Teams Even When Losing is Likely

In this study, the authors investigate situations in which people make sports bets that seem to go against their better judgement. Using surveys, individuals were asked to bet on which team would win in scenarios when their home team was involved and others when they were not to determine whether fandom for a team can overshadow fans’ judgment. They found that fans bet much more on their home teams than neutral teams when their team was facing a large deficit.

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The Effect of Cobalt Biomineralization on Power Density in a Microbial Fuel Cell

Bandyopadhyay et al. | Sep 07, 2015

The Effect of Cobalt Biomineralization on Power Density in a Microbial Fuel Cell

A microbial fuel cell is a system to produce electric current using biochemical products from bacteria. In this project authors operated a microbial fuel cell in which glucose was oxidized by Shewanella oneidensis in the anodic compartment. We compared the power output from biomineralized manganese or cobalt oxides, reduced by Leptothrix cholodnii in the cathodic compartment.

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Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Bhakar et al. | Sep 13, 2022

Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Here the authors investigated the motivation of a short squeeze of GameStop stock where users of the internet forum Reddit drove a sudden increase in GameStop stock price during the start of 2021. They relied on both qualitative and quantitative analyses where they tracked activity on the r/WallStreetBets subreddit in relation to mentions of GameStop. With these methods they found that while initially the short squeeze was driven by financial motivations, later on emotional motivations became more important. They suggest that social phenomena can be dynamic and evolve necessitating mixed method approaches to study them.

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Emotional and Psychological Effect of Music on People

Nolt et al. | Jan 03, 2019

Emotional and Psychological Effect of Music on People

Nolt and Elwonger examine how different types of music impact our emotional and physical states. They found that music can influence a subject's emotional state, with sad music inspiring sadness and exciting music bringing excitement. They were not able to find a clear relationship between heart rate and music type. Music's effect on emotional state can be useful when designing novel therapies for emotional and mental disorders.

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Physical Appearance and Its Effect on Trust

Ledesma et al. | Nov 09, 2020

Physical Appearance and Its Effect on Trust

Do different physical traits affect teenagers’ initial trust of an unknown person? Would they give greater trust to women and people of similar ethnicity? To test these hypotheses, the authors developed a survey to determine the sets of physical characteristics that affect a person's trustworthiness. They found that gender and expression were the main physical traits associated with how trustworthy an individual looks, while ethnicity was also important.

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