One-third of the world's people do not have access to clean drinking water. Nadella and Nadella tackle this issue by testing a low-cost filtration system for removing heavy metal and bacteria from water.
Read More...Heavy metal and bacterial water filtration using Moringa oleifera and coconut shell-activated carbon
One-third of the world's people do not have access to clean drinking water. Nadella and Nadella tackle this issue by testing a low-cost filtration system for removing heavy metal and bacteria from water.
Read More...Statistical models for identifying missing and unclear signs of the Indus script
This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.
Read More...Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation
The authors looked at renewable energy generators and the ability to utilize green roofs as a solution to climate change.
Read More...Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study
Here, recognizing that the immune response to cancer results in biomarkers that can be used to assess the immune status of cancer patients, the authors investigated the concentrations of key cytokines (TH1 and TH2 cytokines) in healthy controls and cancer patients. They identified significant changes in resting and activated cytokine profiles, suggesting that data of biomarkers such as these could serve as a starting point for further treatment with regard to a patient's specific immune profile.
Read More...Can the nucleotide content of a DNA sequence predict the sequence accessibility?
Sequence accessibility is an important factor affecting gene expression. Sequence accessibility or openness impacts the likelihood that a gene is transcribed and translated into a protein and performs functions and manifests traits. There are many potential factors that affect the accessibility of a gene. In this study, our hypothesis was that the content of nucleotides in a genetic sequence predicts its accessibility. Using a machine learning linear regression model, we studied the relationship between nucleotide content and accessibility.
Read More...Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.
Read More...Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules
Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.
Read More...Examining the Growth of Methanotrophic Bacteria Immersed in Extremely Low-Frequency Electromagnetic Fields
Scientist are investigating the use of methane-consuming bacteria to aid the growing problem of rising greenhouse gas emissions. While previous studies claim that low-frequency electromagnetic fields can accelerate the growth rate of these bacteria, Chu et al. demonstrate that this fundamental ideology is not on the same wavelength with their data.
Read More...Changing public opinions on genetically modified organisms through access to educational resources
Genetically modified organisms (GMOs) are crops or animals that have been genetically engineered to express a certain physical or biological characteristic and have various benefits that have made them become increasingly popular. However, the public has had mixed reactions to the use of GMOs, with some skeptical of their safety. The purpose of this study was to evaluate how opinions on genetically modified foods can change from exposure to small amounts of information
Read More...An analysis of junior rower performance and how it is affected by rower's features
In this study, with consideration for the increasing participation of high school students in indoor rowing, the authors analyzed World Indoor Rowing Championship data. Statistical analysis revealed two key features that can determine the performance of a rower as well as increasing competitiveness in nearly all categories considered. They conclude by offering a 2000-meter ergometer time distribution that can help junior rowers assess their current performance relative to the world competition.
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