The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
Read More...Floor level estimation using MEMS pressure sensors
The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
Read More...A land use regression model to predict emissions from oil and gas production using machine learning
Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO2), volatile organic compounds (VOCs), and ozone (O3) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO2, NOx, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.
Read More...Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.
Read More...Ribosome distribution affects stalling in amino-acid starved cancer cells
In this article, the authors analyzed ribosome profiling data from amino acid-starved pancreatic cancer cells to explore whether the pattern of ribosome distribution along transcripts under normal conditions can predict the degree of ribosome stalling under stress. The authors found that ribosomes in amino acid-deprived cells stalled more along elongation-limited transcripts. By contrast, they observed no relationship between read density near start and stop and disparities between mRNA sequencing reads and ribosome profiling reads. This research identifies an important relationship between read distribution and propensity for ribosomes to stall, although more work is needed to fully understand the patterns of ribosome distribution along transcripts in ribosome profiling data.
Read More...Expressional correlations between SERPINA6 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.
Read More...Dispersing Agents Prevent Negative Impact of Oil on Uptake of Zinc by Duckweed (Lemna minor)
Duckweed plays an important role in its aquatic environment by removing pollutants, such as zinc, from the water. In this study, the authors demonstrate that uptake of zinc by duckweed is inhibited by the presence of oil in the water, but this effect can be reversed with the addition of a dispersing agent.
Read More...The Effects of Micro-Algae Characteristics on the Bioremediation Rate of Deepwater Horizon Crude Oil
Environmental disasters such as the Deepwater Horizon oil spill can be devastating to ecosystems for long periods of time. Safer, cheaper, and more effective methods of oil clean-up are needed to clean up oil spills in the future. Here, the authors investigate the ability of natural ocean algae to process crude oil into less toxic chemicals. They identify Coccochloris elabens as a particularly promising algae for future bioremediation efforts.
Read More...Biofortification of Raphanus sativus through irrigation with Ca2+ solutions does not increase calcium content
This study is centered around developing biofortification methods: the authors test whether the amount of calcium available to growing crops translates into more calcium present in the crops.
Read More...A novel bioreactor system to purify contaminated runoff water
In this study, the authors engineer a cost-effective and bio-friendly water purification system using limestone, denitrifying bacteria, and sulfate-reducing bacteria. They evaluated its efficacy with samples from Eastern PA industrial sites.
Read More...String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction
Cystic fibrosis is a genetic disease caused by mutations in the CFTR gene. In this paper, the authors attempt to identify variations in stretches of up to 8 nucleotides in the protein-coding portions of the CFTR gene that are associated with disease development. This would allow screening of newborns or even fetuses in utero to determine the likelihood they develop cystic fibrosis.
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