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Forecasting air quality index: A statistical machine learning and deep learning approach

Pasula et al. | Feb 17, 2025

Forecasting air quality index: A statistical machine learning and deep learning approach
Image credit: Amir Hosseini

Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.

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Utilizing 25-Hydroxyvitamin D3 to prevent the appearance of diabetic-like phenotypes in Drosophila melanogaster

Zaverchand et al. | Sep 20, 2021

Utilizing 25-Hydroxyvitamin D3 to prevent the appearance of diabetic-like phenotypes in Drosophila melanogaster

This study aimed to assess the role of 25-hydroxyvitamin D3 solution, at varying concentrations, in protecting vertical transmission of diabetic-like phenotypes. We hypothesized that the highest concentration of vitamin D solution (55 ng/mL) would be most effective in having a protective role. The results indicated that the hypothesis was partially supported; overall, all three concentrations of the vitamin D solution administered to the flies reared on HSDs had a protective effect, to varying extents.

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A Data-Centric Analysis of “Stop and Frisk” in New York City

Bhat et al. | Apr 18, 2021

A Data-Centric Analysis of “Stop and Frisk” in New York City

The death of George Floyd has shed light on the disproportionate level of policing affecting non-Whites in the United States of America. To explore whether non-Whites were disproportionately targetted by New York City's "Stop and Frisk" policy, the authors analyze publicly available data on the practice between 2003-2019. Their results suggest African Americans were indeed more likely to be stopped by the police until 2012, after which there was some improvement.

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Comparing the Dietary Preference of Caenorhabditis elegans for Bacterial Probiotics vs. Escherichia coli.

Lulla et al. | Dec 18, 2020

Comparing the Dietary Preference of <i>Caenorhabditis elegans</i> for Bacterial Probiotics vs. <i>Escherichia coli</i>.

In this experiment, the authors used C. elegans as a simple model organism to observe the impact of probiotics on the human digestive system. The results of the experiments showed that the C. elegans were, on average, most present in Chobani cultures over other tested yogurts. While not statistically significant, these results still demonstrated that C. elegans might prefer Chobani cultures over other probiotic yogurts, which may also indicate greater gut benefits from Chobani over the other yogurt brands tested.

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A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Vangal et al. | Sep 28, 2020

A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Each year, over 100,000 patients die from Sudden Unexpected Death in Epilepsy (SUDEP). A reliable seizure warning system can help patients stay safe. This work presents a comprehensive, comparative analysis of three different signal processing algorithms for automated seizure/ictal detection. The experimental results show that the proposed methods can be effective for accurate automated seizure detection and monitoring in clinical care.

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