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Using economic indicators to create an empirical model of inflation

Kasera et al. | Dec 01, 2022

Using economic indicators to create an empirical model of inflation

Here, seeking to understand the correlation of 50 of the most important economic indicators with inflation, the authors used a rolling linear regression to identify indicators with the most significant correlation with the Month over Month Consumer Price Index Seasonally Adjusted (CPI). Ultimately the concluded that the average gasoline price, U.S. import price index, and 5-year market expected inflation had the most significant correlation with the CPI.

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Effects of Photoperiod Alterations on Stress Response in Daphnia magna

Kelly et al. | Mar 10, 2022

Effects of Photoperiod Alterations on Stress Response in <em>Daphnia magna</em>

Here, seeking to better understand the effects of altered day-night cycles, the authors considered the effects of an altered photoperiod on Daphnia magna. By tracking possible stress responses, including mean heart rate, brood size, and male-to-female ratio they found that a shorter photoperiod resulted in altered mean heart rates and brood size. The authors suggest that based on these observations, it is important to consider the effects of photoperiod alterations and the stress responses of other organisms.

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Prediction of molecular energy using Coulomb matrix and Graph Neural Network

Hazra et al. | Feb 01, 2022

Prediction of molecular energy using Coulomb matrix and Graph Neural Network

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

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Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Anand et al. | Nov 14, 2020

Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Oil spills are one of the most devastating events for marine life. Finding ways to clean up oil spills without the need for harsh chemicals could help decrease the negative impact of such spills. Here the authors demonstrate that using a combination of several biodegradable substances can effectively adsorb oil in seawater in a laboratory setting. They suggest further exploring the potential of such a combination as a possible alternative to commonly-used non-biodegradable substances in oil spill management.

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Combating drug resistance in cancer cells: Cooperative effect of green tea and turmeric with chemotherapeutic drug

Nair et al. | Jul 27, 2020

Combating drug resistance in cancer cells: Cooperative effect of green tea and turmeric with chemotherapeutic drug

The major drawback of chemotherapy regimens for treating cancer is that the cancerous cells acquire drug resistance and become impervious to further dose escalation. Keeping in mind the studied success of herbal formulations with regard to alternative treatments for cancer, we hypothesized that the use of a chemotherapeutic drug and proprietary herbal formulation, HF1, would combat this phenomenon when administered with common chemotherapeutic drug 5FU. Results demonstrated a cooperative effect between HF1 and 5FU on the drug resistant cell line, implying that administration of HF1 with 5FU results in cell death as measured by MTT assay.

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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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