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Farmers will need to increase crop yields to feed the world's growing population efficiently. The authors here investigate the effects of growing corn in the presence or absence of ragweed, an invasive weed found in many fields and gardens. Surprisingly, the authors found that corn grown in the presence of weeds grew taller and were more productive than corn that had weeds removed. This may help gardeners rethink the necessity of weeding, and may point a way to improve farm yields in the future.

This manuscript investigates the urban heat island (UHI) effect by utilizing two satellite datasets: Landsat (high spatial resolution, lower temporal resolution) and MODIS (lower spatial resolution, high temporal resolution). The authors hypothesized that Landsat would provide better spatial detail, while MODIS would better capture temporal variations. Their analysis in the Washington D.C.–Baltimore region supports these hypotheses, demonstrating that Landsat offers finer spatial details, whereas MODIS provides more consistent seasonal patterns and better detects heatwave frequencies.

The authors were interested in whether they could observe the effects of climate change by analyzing historical temperature data of two U.S. cities. They predicted that they should observe a warming trend in both cities. Their results showed that despite yearly variations, warming trends can be observed both in Rochester, NY and Seattle, WA which fit the predictions of climate change forecasts.

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.

While some believe that ride-hailing services offer reduced CO₂ emissions compared to individual driving, studies have found that driving without passengers on ride-hailing trips or "deadheading" prevents this. Here, with a mathematical model, the authors investigated if the use of electric vehicles as ride-hailing vehicles could offer reduced CO₂ emissions. They found that the improved vehicle efficiency and cleaner generation could in fact lower emissions compared to the use of personal gas vehicles.

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.

Ethinyl estradiol and progestin norgestrel are commonly present in contraceptive tablets and it is unknown how they affect the environment. In this study, the authors investigate the role that ethinyl estradiol and progestin norgestrel have on the growth of flowering plants. The percentage germination, embryonic and adventitious tissue proliferation, root length, and shoot length were measured in V. radiata and T. aestivum treated with each compound and results demonstrate that ethinyl estradiol and progestin norgestrel can induce growth in both plants at certain concentrations. These findings have important implications as societal use of chemicals increases and more make their way into the environment.

The authors looked at phytoremediation, the process by which plants are used to remove pollutants from our environment, and the ability of Lemna minor to perform phytoremediation in various simulated polluted environments. The authors found that L. minor could remove pollutants from the environment and that the addition of bacteria increased this removal.

The authors looked at how the addition of NaCl to crystalline nanocellulose capacitors could improve performance in transistor applications. They found that NaCl can improve performance, but that further work is needed to determine the optimal concentration used depending on the intended application.

The printing-related expenditure that is budgeted in 2014 for U.S. Federal agencies is $1.8 billion. A sample of five publically available documents produced by various federal agencies is analyzed and the cost savings arising from a change in font type are estimated. The analysis predicts that the Government’s annual savings by switching to Garamond are likely to be about $234 million with worst-case savings of $62 million and best-case savings of $394 million. Indirect benefits arising from a less detrimental impact on the environment due to lower ink production and disposal volumes are not included in these estimates. Times New Roman is not as efficient as Garamond, and the third federally-recommended font, Century Gothic, is actually worse on average than the fonts used in the sample documents.