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Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Saha et al. | Feb 21, 2020

Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

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.

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Fluorescein or Green Fluorescent Protein: Is It Possible to Create a Sensor for Dehydration?

Joshi et al. | Dec 09, 2019

Fluorescein or Green Fluorescent Protein: Is It Possible to Create a Sensor for Dehydration?

Currently there is no early dehydration detection system using temperature and pH as indicators. A sensor could alert the wearer and others of low hydration levels, which would normally be difficult to catch prior to more serious complications resulting from dehydration. In this study, a protein fluorophore, green fluorescent protein (GFP), and a chemical fluorophore, fluorescein, were tested for a change in fluorescence in response to increased temperature or decreased pH. Reversing the pH change did not restore GFP fluorescence, but that of fluorescein was re-established. This finding suggests that fluorescein could be used as a reusable sensor for a dehydration-related pH change.

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Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Choudhary et al. | Jul 26, 2021

Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

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Spider Density Shows Weak Relationship with Vegetation Density

Ryon et al. | Jul 03, 2020

Spider Density Shows Weak Relationship with Vegetation Density

Evidence supports that spiders have many ecological benefits including insect control and predation in the food chain. In this study the authors investigate that whether the percent of vegetation coverage and spider density are correlated. They determine that despite the trend there is no statistically significant correlation.

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Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Levy et al. | Oct 13, 2014

Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Coronary artery bypass grafts are a common technique to treat coronary heart disease. The authors compared the efficacy of suturing and stapling techniques using an artificial heart pump and silicone tubing and found that suturing, while more time and skill intensive, held pressure in the tubing better than stapling.

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