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The effects of Helianthus Annuus on Amyotrophic Lateral Sclerosis using Drosophila Melanogaster

Srinivasan et al. | Oct 13, 2022

The effects of <em>Helianthus Annuus</em> on Amyotrophic Lateral Sclerosis using <em>Drosophila Melanogaster</em>

Amyotrophic lateral sclerosis (ALS) affects nearly 200,000 people worldwide and there is currently no cure. The purpose of the study was to determine if Helianthus annuus seeds helped reduce nerve degeneration and increase locomotion using Drosophila melanogaster as the model organism. Through this experiment, we found a general trend suggesting that H. annuus helped increase the mobility of the D. melanogaster suggesting it could be a viable supplement for patients with ALS.

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Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

Tota et al. | Mar 28, 2019

Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

One of the greatest challenges we face today is the sustainable production, storage, and distribution of electrical power. One emerging technology with great promise in this area is that of metal-air fuel cells—a long-term and reusable electricity storage system made from a reactive metal anode and a saline solution. In this study the authors tested several different types of metal to determine which was the most suitable for this application. They found that a fuel cell with a magnesium anode was superior to fuel cells made from aluminum or zinc, producing a voltage and current sufficient for real-world applications such as charging a mobile phone.

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Analysis of biofertilization impacts on Pisum sativum

Holden et al. | May 18, 2023

Analysis of biofertilization impacts on <i>Pisum sativum</i>
Image credit: David Boozer

This study explored the various effects of three different produce-based biofertilizers on pea plant growth, using red apple, pear, strawberry, and control treatments. It was hypothesized that the application of fruit biomatter would increase the growth of pea plants, with the application of strawberry biomatter having the most significant effect due to strawberries containing a higher nutrient content compared to pears and apples. Analysis confirmed the hypothesis. The application of strawberry biomatter could prove to be an effective way to increase plant growth in commercial agriculture.

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Using two-stage deep learning to assist the visually impaired with currency differentiation

Nachnani et al. | Jun 02, 2024

Using two-stage deep learning to assist the visually impaired with currency differentiation
Image credit: Omer Shahzad

Here, recognizing the difficulty that visually impaired people may have differentiating United States currency, the authors sought to use artificial intelligence (AI) models to identify US currencies. With a one-stage AI they reported a test accuracy of 89%, finding that multi-level deep learning models did not provide any significant advantage over a single-level AI.

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Enhancing the quantum efficiency of a silicon solar cell using one dimensional thin film interferometry

Ahuja et al. | May 03, 2024

Enhancing the quantum efficiency of a silicon solar cell using one dimensional thin film interferometry
Image credit: American Public Power Association

Here, recognizing the need to improve the efficiency of the conversion of solar energy to electrical energy, the authors used MATLAB to mathematically simulate a multi-layered thin film with an without an antireflective coating. They found that the use of alternating ZnO-SiO2 multilayers enhanced the transmission of light into the solar cell, increasing its efficiency and reducing the reflectivity of the Si-Air interface.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

Differential privacy in machine learning for traffic forecasting

In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

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Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Nguyen et al. | Jul 14, 2020

Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Understanding the techniques used to improve the adhesion strength of the epoxy resin is important especially for consumer applications such as repairing car parts, bonding aluminum sheeting, and repairing furniture or applications within the aviation or civil industry. Selleys Araldite epoxy makes specific strength claims emphasizing that the load or weight that can be supported by the adhesive is 72 kg/cm2. Nguyen and Clarke aimed to test the strength claims of Selley’s Araldite Epoxy by gluing two steel adhesion surfaces: a steel tube and bracket. Results showed that there is a lack of consideration by Selleys for adhesion loss mechanisms and environmental factors when accounting for consumer use of the product leading to disputable claims.

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Blockchain databases: Encrypted for efficient and secure NoSQL key-store

Mehrota et al. | Mar 18, 2023

Blockchain databases: Encrypted for efficient and secure NoSQL key-store
Image credit: Ayushi Mehrota & David Kim

Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.

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