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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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Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426

Còdol et al. | Oct 05, 2023

Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426
Image credit: Pixabay

This assessed the hypothesis that stars in wide binary systems are chemically homogeneous because of their shared origin. Abundances of the HIP 34407/HIP 34426 binary were obtained by analyzing high-resolution spectra of the system. Discrepancies found in the system’s elemental abundances might be an indicator of the presence of rocky planets around this star. Thus, the differences found in chemical composition might demonstrate limitations in the assumptions of chemical tagging.

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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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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

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The association between hunting and the feeding and vigilance times of American bison in North Dakota and Montana

McCandless et al. | Mar 30, 2022

The association between hunting and the feeding and vigilance times of American bison in North Dakota and Montana

This study hypothesized that feeding times of bison in the hunted populations would be significantly shorter than that of bison in the nonhunted population and vigilance times would be significantly longer than that of bison in the nonhunted population. Notably, the results found significant differences in feeding and vigilance times of bison in the hunted and non-hunted populations. However, these differences did not support the original hypothesis; bison in hunted populations spent more time feeding and less time vigilant than bison in the non-hunted population. Future studies investigating the association between hunting and bison behaviors could use populations of bison that are hunted more frequently, which may provide different results.

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Expressional correlations between SERPINA6 and pancreatic ductal adenocarcinoma-linked genes

Selver et al. | Oct 06, 2021

Expressional correlations between <em>SERPINA6</em> and pancreatic ductal adenocarcinoma-linked genes

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, with early diagnosis and treatment challenges. When any of the genes KRAS, SMAD4, TP53, and BRCA2 are heavily mutated, they correlate with PDAC progression. Cellular stress, partly regulated by the gene SERPINA6, also correlates with PDAC progression. When SERPINA6 is highly expressed, corticosteroid-binding globulin inhibits the effect of the stress hormone cortisol. In this study, the authors explored whether there is an inverse correlation between the expression of SERPINA6 and PDAC-linked genes.

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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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