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Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

Carroll et al. | Jul 10, 2020

Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

In this study, the authors investigate what metals make the most efficient electrochemical cells, which are batteries that use the difference in electrical potential to generate electricity. Calculations predicted that a cell made of iron and magnesium would have the highest efficiency. Construction of an electrochemical cell of iron and magnesium produced voltages close to the theoretical voltage predicted. These findings are important as work continues towards making batteries with the highest storage efficiency possible.

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Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Gupta et al. | Feb 04, 2014

Pancreatic Adenocarcinoma: An Analysis of Drug Therapy Options through Interaction Maps and Graph Theory

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

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The juxtaposition of anatomy and physics in the eye

Zhou et al. | Oct 25, 2023

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.

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Wound healing properties of mesenchymal conditioned media: Analysis of PDGF, VEGF and IL-8 concentrations

Prasad et al. | Dec 15, 2021

Wound healing properties of mesenchymal conditioned media: Analysis of PDGF, VEGF and IL-8 concentrations

Regenerative medicine has become a mainstay in recent times, and employing stem cells to treat several degenerative, inflammatory conditions has resulted in very promising outcomes. These forms of cell-based therapies are novel approaches to existing treatment modalities. In this study, the authors compared the concentrations of the cytokines PDGF, IL-8, and VEGF between conditioned and spent media of mesenchymal stem cells (MSCs) to evaluate their potential therapeutic properties for wound healing in inflammatory conditions. They hypothesized that conditioned media contains higher concentrations of wound healing cytokines compared to spent media. The authors found that while IL-8 and VEGF were present in highest concentrations in conditioned media, PDGF was present in maximal amounts in spent media.

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An analysis of the distribution of microplastics along the South Shore of Long Island, NY

Sanderson et al. | Sep 21, 2020

An analysis of the distribution of microplastics along the South Shore of Long Island, NY

This study is focused on the distribution of microplastics in Long Island, NY. Microplastics are plastic particles that measure less than 5 mm in length and pose an environmental risk due to their size, composition, and ubiquitous location in the marine environment. Focusing on the South Shore of Long Island, the authors investigated the locations and concentrations of microplastics at four locations along the shore line. While they did not find significant differences in the number of microplastics per location, there were microplastics at all four locations. This finding is important to drive future research and environmental policy as well.

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Exponential regression analysis of the Canadian Zero Emission Vehicle market’s effects on climate emissions in 2030

Ajay et al. | Feb 25, 2023

Exponential regression analysis of the Canadian Zero Emission Vehicle market’s effects on climate emissions in 2030
Image credit: Andrew Roberts

Here, the authors explored how the sale and use of electric vehicles could reduce emissions from the transport industry in Canada. By fitting the sale of total of electric vehicles with an exponential model, the authors predicted the number of electric vehicle sales through 2030 and related that to the average emission for such vehicles. Ultimately, they found that the sale and use of electric vehicles alone would likely not meet the 45% reduction in emissions from the transport industry suggested by the Canadian government

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Analysis of Technology Usage of Teens: Correlating Social Media, Technology Use, Participation in Sports, and Popularity

Düzgezen et al. | Mar 27, 2020

Analysis of Technology Usage of Teens: Correlating Social Media, Technology Use, Participation in Sports, and Popularity

Social media usage is predicted to impact teen well-being and emotional status. This study sought to assess the impact of teen technology usage on their social lives. Surveys of 8th and 9th graders were used to assess compare technology usage between males and females as well as and how social media usage impacts the perception of social environment at school.

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Recognition of animal body parts via supervised learning

Kreiman et al. | Oct 28, 2023

Recognition of animal body parts via supervised learning
Image credit: Kreiman et al. 2023

The application of machine learning techniques has facilitated the automatic annotation of behavior in video sequences, offering a promising approach for ethological studies by reducing the manual effort required for annotating each video frame. Nevertheless, before solely relying on machine-generated annotations, it is essential to evaluate the accuracy of these annotations to ensure their reliability and applicability. While it is conventionally accepted that there cannot be a perfect annotation, the degree of error associated with machine-generated annotations should be commensurate with the error between different human annotators. We hypothesized that machine learning supervised with adequate human annotations would be able to accurately predict body parts from video sequences. Here, we conducted a comparative analysis of the quality of annotations generated by humans and machines for the body parts of sheep during treadmill walking. For human annotation, two annotators manually labeled six body parts of sheep in 300 frames. To generate machine annotations, we employed the state-of-the-art pose-estimating library, DeepLabCut, which was trained using the frames annotated by human annotators. As expected, the human annotations demonstrated high consistency between annotators. Notably, the machine learning algorithm also generated accurate predictions, with errors comparable to those between humans. We also observed that abnormal annotations with a high error could be revised by introducing Kalman Filtering, which interpolates the trajectory of body parts over the time series, enhancing robustness. Our results suggest that conventional transfer learning methods can generate behavior annotations as accurate as those made by humans, presenting great potential for further research.

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